system

Abstract

We provide the system. [Solution] A means for receiving user input information from a communication device, A means for obtaining existing intellectual property rights information using a database search means based on received input information, A means including a generation module that analyzes acquired intellectual property rights information and generates new, non-duplicate intellectual property rights proposals, A means of presenting the generated intellectual property rights proposal to the user, A means of applying the generated intellectual property rights draft to a payment management system using dynamic generation technology, 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, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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] The conventional process for obtaining intellectual property rights is complex and time-consuming from the creation of an idea to the investigation of existing intellectual property rights and the preparation of application documents, posing a significant burden on individuals and organizations. In this process, the investigation to avoid duplication with existing intellectual property rights is particularly important, and mistakes or oversights may lead to disputes with competing companies. Therefore, there is a need to provide a means to generate and present a new intellectual property right case without duplication in a short time and efficiently.

Means for Solving the Problems

[0005] To solve the above problems, the present invention receives user ideas and business-related information via a communication device, searches an intellectual property database based on that information to obtain relevant existing intellectual property information, and solves the problem by providing a generation module that generates novel intellectual property proposals without duplication by analyzing this information. Furthermore, it analyzes business materials provided by the user, proposes supplementary intellectual property proposals based on these materials, and supports efficient acquisition of intellectual property rights. As a result, users can obtain high-quality intellectual property proposals without hassle, and as a result, enhance their competitive advantage.

[0006] A "communication device" is a hardware or software interface for receiving user input information and transmitting it to a server.

[0007] "User" refers to an individual or organization that intends to use this system to generate new intellectual property rights proposals.

[0008] "Input information" refers to text data such as ideas and themes provided by users for the purpose of acquiring intellectual property rights.

[0009] A "database search tool" is a program module for searching and retrieving relevant information from a database that stores existing intellectual property rights information, such as patents and trademarks.

[0010] "Intellectual property information" refers to data about existing patents, trademarks, designs, and other legally protected rights.

[0011] A "generation module" is an algorithm or program that generates new, non-repeating ideas based on existing intellectual property rights information.

[0012] "Means of presentation" refers to software components that display the generated intellectual property rights draft in an easily understandable way to the user.

[0013] "Business materials" refer to documents and data that include research and development, technical background, and product information within the organization to which the user belongs.

[0014] "Analyzing" refers to the process of performing computational processing and analysis on received or acquired information to derive its characteristics and relationships. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when 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.

Mode for Carrying Out the Invention

[0016] 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.

[0017] First, the language used in the following description will be explained.

[0018] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0019] 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.

[0020] 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 disks (e.g., hard disks), or magnetic tapes, and the like.

[0021] 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).

[0022] 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."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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".

[0036] This invention provides a system that receives input from users regarding patent ideas and areas of interest via a communication device. The system consists of a terminal and a server, the server which searches an intellectual property database based on the received information to obtain relevant existing intellectual property information.

[0037] Specifically, when a user enters a patent idea on their device, the content is sent to the server. The server analyzes this input, converts it to an appropriate format, and searches the intellectual property database using a patent search API. The retrieved existing patent information is analyzed within the server, and a new, non-duplicate intellectual property proposal is generated using a generation AI. The generated patent proposal is sent to the device and presented to the user.

[0038] This system also includes a function to read user business documents, which the server then analyzes to support the proposal of pre-prepared patent proposals. This allows users to acquire new intellectual property rights proposals with less additional time and effort.

[0039] For example, if a user wants to devise a patent for a "new energy efficiency device," they send the input from their terminal to the server, and the generating AI uses a patent search API to investigate existing related patents. Based on this investigation, the server generates a new patent proposal for the device in a non-duplicate manner and presents it to the user. The user can then smoothly proceed to the next step in patent application based on the presented proposal.

[0040] Thus, the present invention streamlines the patent acquisition process and provides a form that allows users to quickly create high-quality intellectual property drafts.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] Users input their patent ideas and areas of interest through an interface on their device. Specifically, they enter keywords and detailed descriptions into text boxes and press the submit button.

[0044] Step 2:

[0045] The terminal receives the input information and sends it to the server in the appropriate format. During this process, the input data is transferred to the server via the network.

[0046] Step 3:

[0047] The server analyzes the received user input and extracts keywords and phrases. Based on this, it constructs a request to call the patent search API.

[0048] Step 4:

[0049] The server sends a request to the patent search API, which searches the database for relevant existing patents based on the input information. The search results are returned from the API to the server.

[0050] Step 5:

[0051] The server receives information on existing patents returned from the API and analyzes them. Based on the analysis results, it calls a generation AI model to generate new patent proposals.

[0052] Step 6:

[0053] The generative AI model uses the received data to generate new patent proposals that do not overlap with existing patents. The generated proposals are returned to the server.

[0054] Step 7:

[0055] The server formats the generated patent draft into a format that is easy for the user to understand and sends it to the terminal.

[0056] Step 8:

[0057] The terminal presents the user with new patent proposals received from the server. The user can then refer to these and decide on their next course of action.

[0058] Step 9:

[0059] If necessary, users can upload their work documents and additional information to the server via their terminal, and the server will use this information for further analysis and to supplement the patent proposal.

[0060] (Example 1)

[0061] 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."

[0062] In today's highly information-driven society, acquiring new intellectual property rights is a crucial means of enhancing the competitiveness of companies and individuals. However, creating new ideas that do not overlap with existing intellectual property information is an extremely time-consuming and laborious task. Furthermore, there is a lack of effective methods for efficiently linking business-related information with new patent proposals. Therefore, a system is needed to solve these problems and streamline the generation of intellectual property proposals.

[0063] 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.

[0064] In this invention, the server includes means for receiving user input data from a communication device, means for analyzing the received input data and converting it into an appropriate format using natural language processing technology, and means for acquiring existing intellectual property information using a data retrieval module, and a generation module for generating novel intellectual property proposals that do not overlap with existing intellectual property information using a generation AI model based on the acquired intellectual property information. As a result, users can efficiently generate novel ideas that do not overlap with existing intellectual property information and easily create novel intellectual property proposals linked to business-related information.

[0065] "Communication equipment" refers to electronic devices used for sending and receiving data, and is a device that plays a role in acquiring information from users.

[0066] "User" refers to an individual or group that operates the system and inputs ideas or data.

[0067] "Input data" refers to information supplied by the user to the system via communication devices, and is used to generate intellectual property rights.

[0068] "Natural language processing technology" is a technique that allows computers to understand and analyze human language, and is used to convert input data into a specific format.

[0069] A "data retrieval module" is a program or device used to retrieve specified information by referring to a designated database.

[0070] "Intellectual property information" refers to a collection of information about existing patents and intellectual property rights, including data necessary for generating new patent proposals.

[0071] A "generative AI model" is a computer model that uses artificial intelligence technology to create new ideas and intellectual property rights proposals.

[0072] A "generation module" is a program or device for generating new intellectual property rights proposals based on acquired information.

[0073] "Business-related information" refers to all data related to the work of the organization or individual to which the user belongs, and is used as supplementary material for new patent proposals.

[0074] In order to implement the invention, the system must be constructed based on the following configuration and procedure.

[0075] The server receives user input data transmitted from communication devices. This input data contains information about ideas and areas of interest related to intellectual property rights. The server analyzes this data using natural language processing techniques and converts it into a format suitable for patent searches. This process uses general natural language processing libraries to extract relevant keywords and transform phrases.

[0076] The analyzed data is searched for in the intellectual property information database via a data search module. The online database provided by the Japan Patent Office can be used as the database. This allows the server to retrieve existing intellectual property information and, based on this, generate new, non-duplicate intellectual property proposals.

[0077] The generation process utilizes a generative AI model. This model analyzes acquired intellectual property information and generates new ideas. It is implemented on a general machine learning framework and trained to generate new ideas.

[0078] The terminal serves to provide the user with the generated intellectual property draft sent from the server. The user can review the new patent draft on the terminal and send feedback to the server as needed. This allows for a process of further refining the patent draft.

[0079] For example, if a user comes up with an idea for a "new device for clean energy," they input this idea into the terminal. The server then uses a data retrieval module to obtain relevant existing patents, and a generating AI model generates a new patent proposal based on this.

[0080] An example of a prompt message would be: "I want to develop a new patent idea for an energy efficiency device. Please research existing related patents and generate a novel idea that does not overlap."

[0081] This system streamlines the patent application process, enabling users to quickly and effectively create new intellectual property rights proposals.

[0082] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0083] Step 1:

[0084] Subject: User

[0085] Users input their patent-related ideas and areas of interest into the system via a terminal. They freely describe their ideas in natural language. The input information is in text format.

[0086] Step 2:

[0087] Subject: terminal

[0088] The terminal sends the data entered by the user to the server. This communication is conducted using a secure protocol. The output of the terminal is the user's input data directed to the server. This allows the server to process the user's intended content.

[0089] Step 3:

[0090] Subject: Server

[0091] The server analyzes the user's input data using natural language processing techniques. The input data is in text format; the server analyzes it to extract keywords and key phrases and converts it into a data format suitable for patent searches. The server's output is structured data suitable for searching.

[0092] Step 4:

[0093] Subject: Server

[0094] The server searches existing intellectual property information databases using a data retrieval module based on the analyzed data. It uses structured search data as input to retrieve relevant intellectual property information. The server's output is a list of existing patent information.

[0095] Step 5:

[0096] Subject: Server

[0097] The server generates new intellectual property proposals using a generative AI model based on acquired intellectual property information. It receives existing patent information and original user input as input, analyzes them, and devises new, non-repeating ideas. The server's output is a new patent proposal.

[0098] Step 6:

[0099] Subject: Server

[0100] The server sends the generated new patent proposal to the terminal. As output, it generates data containing details of the new patent proposal and provides it to the terminal. This allows the user to consider the new proposal.

[0101] Step 7:

[0102] Subject: User

[0103] The user reviews the proposed new patent on their terminal, receiving it from the server and examining its contents. They provide feedback as needed, expecting further adjustments to be made on the server side. The user's output consists of their feedback and their decision regarding the acceptance or rejection of the proposal.

[0104] (Application Example 1)

[0105] 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."

[0106] There is a need to quickly and efficiently generate new intellectual property rights proposals based on existing intellectual property rights information and apply them to payment management systems. However, current systems are insufficient in efficiently analyzing user input information, generating new proposals that do not overlap with existing intellectual property rights information, and utilizing dynamic generation technology. Therefore, the provision of a new system is desired.

[0107] 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.

[0108] In this invention, the server includes means for receiving user input information from a communication device, means for acquiring existing intellectual property rights information using a database search means based on the received input information, means including a generation module for analyzing the acquired intellectual property rights information and generating new, non-duplicate intellectual property rights proposals, and means for presenting the generated intellectual property rights proposals to the user and applying them to a payment management system using dynamic generation technology. This enables the user to quickly and efficiently generate new intellectual property rights proposals and apply them to a payment management protocol.

[0109] A "communication device" is a device that has the ability to send and receive information, and is particularly used to receive input information from a user.

[0110] "User input information" refers to a collection of data and instructions that users provide to the system, including information such as patent ideas and areas of interest.

[0111] "Database search methods" refer to methods and techniques for searching for information within a database using specific algorithms and obtaining the necessary information.

[0112] "Intellectual property information" refers to a collection of existing information concerning intellectual property such as patents, trademarks, and copyrights.

[0113] A "generation module" is a structure consisting of software or hardware for generating new intellectual property rights proposals based on specific inputs.

[0114] "Dynamic generation technology" is a technology that generates information in real time according to the situation and conditions, and is particularly used in applications such as payment management systems.

[0115] A "payment management system" is a system for managing and processing information related to electronic transactions and settlements.

[0116] This invention aims to efficiently patent new user ideas in an electronic payment system via a communication device. A specific embodiment of the system is shown below.

[0117] First, the user uses a smartphone or other device to input ideas about new payment methods or security protocols they want to patent. This input is then sent to the server via a communication device.

[0118] After receiving the input, the server analyzes it using a natural language processing library (e.g., spaCy or NLTK) and, if necessary, searches for intellectual property information via a patent search API such as the Google Patents API. Based on the existing intellectual property information obtained as a search result, the server generates new intellectual property proposals that do not overlap with the generation modules within the server, using a generation AI (e.g., OpenAI's GPT-3).

[0119] The newly generated intellectual property rights proposals are processed using dynamic generation technology to make them suitable for implementation within the payment management system. These processed proposals are then sent back to the user's terminal and presented to them. This approach allows users to quickly and efficiently generate their own patent proposals and translate them into concrete implementations within the context of electronic payments.

[0120] For example, if a user envisions a "new payment system using QR codes (registered trademark)," the server can search existing QR code-related patents and propose a new security protocol.

[0121] Examples of prompts to input into a generative AI model:

[0122] "Generate a patent idea for a new payment system using QR codes. Consider existing patent information and ensure the idea is novel."

[0123] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0124] Step 1:

[0125] Users input ideas for new payment methods or security protocols using a terminal. The input information is transmitted to a server as digital text via a communication device. The input format is free-form text.

[0126] Step 2:

[0127] The server receives input information sent by the user and parses the text data using a natural language processing library (e.g., spaCy or NLTK). This parsing extracts keywords and important concepts contained in the input information. The output is a list of the parsed keywords.

[0128] Step 3:

[0129] The server uses a patent search API (e.g., Google Patents API) to search intellectual property databases based on an analyzed keyword list. The input is a keyword list, and the output is relevant existing intellectual property information.

[0130] Step 4:

[0131] The server analyzes the acquired intellectual property information and uses a generative AI (e.g., OpenAI's GPT-3) to generate novel, non-overlapping intellectual property proposals. The input is existing patent information, and the generative AI generates new patent proposals that match the ideas of the patents as output.

[0132] Step 5:

[0133] The newly generated intellectual property rights proposals are processed using dynamic generation technology to make them suitable for implementation in an electronic payment system. The input is the generated patent proposal, and the output is the proposal adapted to the target system.

[0134] Step 6:

[0135] The server sends the processed patent draft to the terminal, presents it to the user, and helps them review and decide whether to adopt the generated patent draft. The input is the processed patent draft, and the output is the displayed content as feedback to the user.

[0136] 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.

[0137] This invention is a system that generates new intellectual property rights proposals based on ideas and themes input by the user, and presents these proposals while taking the user's emotional state into consideration. This system mainly consists of a terminal, a server, and an emotion engine.

[0138] The user inputs text about the idea they want to patent or their areas of interest through their device. This input information is sent from the device to the server, and at the same time, the user's emotional state is analyzed by an emotion engine. This emotion is inferred from the language patterns and tone of the input, and the analysis results are sent to the server.

[0139] The server uses a patent search API to search for existing intellectual property rights information based on the user's input and retrieves the results. Based on this retrieved information, the server uses a generative AI to generate new, non-duplicate intellectual property rights proposals.

[0140] The generated intellectual property proposals are formatted by the server, and their presentation is adjusted based on the results of emotional state analysis by the emotion engine. For example, if the analysis indicates that the user is excited, the proposals will be adjusted to emphasize more ambitious ideas.

[0141] This allows users to receive new patent proposals not only in terms of technical novelty, but also in a way that resonates emotionally. The presented intellectual property proposals are fed back to the user through their device, allowing them to proceed with further consideration and patent application procedures based on this feedback.

[0142] For example, if a user excitedly inputs an idea about a "new energy efficiency technology," the emotion engine detects the excitement, and the server, based on this, prioritizes presenting intellectual property proposals that include innovative technological elements. This process allows the user to receive accurate feedback that matches their emotions on the spot, enabling quick decision-making.

[0143] The following describes the processing flow.

[0144] Step 1:

[0145] Users input their patent ideas and areas of interest in technology through the terminal's interface. Specifically, they fill in the content in a text box and click the submit button to send the information to the terminal.

[0146] Step 2:

[0147] The device passes the received input information to the emotion engine, which recognizes the user's emotions. The emotion engine analyzes the language patterns of the input text and determines the user's current emotional state (e.g., excitement, calmness, doubt, etc.).

[0148] Step 3:

[0149] The terminal sends user input information, including analysis results, to the server. This information is transferred to the server via the communication network.

[0150] Step 4:

[0151] The server analyzes the received information and uses a patent search API to retrieve relevant existing intellectual property information from the database. During this process, it generates an appropriate search query based on the user's input and sends a request to the API.

[0152] Step 5:

[0153] The server uses a generative AI model to generate novel, non-duplicate intellectual property rights proposals based on existing patent information obtained from the API. The generative AI executes algorithms to create new ideas while referencing existing data.

[0154] Step 6:

[0155] The server formats the generated intellectual property proposals into a format that is easy for the user to understand. It adjusts the presentation content considering the emotional state determined by the emotion engine. For example, if the user is excited, the proposal will be presented in a way that emphasizes innovative elements.

[0156] Step 7:

[0157] The server sends the formatted patent draft and sentiment analysis results to the terminal.

[0158] Step 8:

[0159] The terminal receives data from the server and displays it on the user interface. Based on this, the user reviews the proposed intellectual property rights and considers the next action.

[0160] (Example 2)

[0161] 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".

[0162] Conventional intellectual property rights proposal generation systems lacked feedback that considered the user's emotional state. As a result, while the generated rights proposals technically met the novelty requirements, they failed to adequately address the user's emotions and creative expectations. Consequently, users found it difficult to empathize with the proposed rights proposals, making effective decision-making and prompt responses challenging.

[0163] 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.

[0164] In this invention, the server includes means for receiving user information from a communication terminal, means for analyzing the received information and the user's emotional state, means for acquiring existing rights information using a data storage device based on the analysis results, and means for presenting the generated rights proposal while taking the user's emotional state into consideration. This makes it possible to present novel and highly empathetic rights proposals that reflect the user's emotional state.

[0165] A "communication terminal" is a device used to input user information and transmit it to a server.

[0166] "User information" refers to text data about ideas and areas of interest entered by the user.

[0167] "Emotional state" refers to the emotional state analyzed based on information entered by the user, and is a numerical representation of emotions such as excitement or calmness.

[0168] A "data storage device" refers to a database used to store existing rights information and to search and retrieve it as needed.

[0169] "Rights information" refers to information about existing intellectual property rights, including data on patents and technical documents.

[0170] A "generative AI model" refers to artificial intelligence technology used to generate new rights proposals based on given data.

[0171] A "proposal for rights" refers to a concept for newly proposed intellectual property rights based on information provided by the user and existing rights information.

[0172] This invention is a system that generates new intellectual property rights proposals based on the user's ideas and presents these proposals while considering the user's emotional state. This system mainly consists of a communication terminal, a server, and an emotion analysis engine.

[0173] The user uses a communication terminal to input text data about the idea they want to patent or their areas of interest. The communication terminal receives this information and sends it to the server. Simultaneously, the data is sent to an emotion analysis engine, which analyzes the user's emotional state from language patterns and tone. This analysis uses natural language processing technology to quantify the user's emotional state.

[0174] The server uses its data storage device based on the received user information and accesses a patent search API to search for existing rights information. Here, existing intellectual property rights information is identified and retrieved. Based on this information, a new rights proposal is created using a generative AI model. The generative AI model operates based on prompt statements, such as "Generate a new patent proposal related to the entered technology field. The emotional state is excited."

[0175] The generated new patent proposals are formatted by the server and presented to the user, taking into account their analyzed emotional state. This adjustment may include modifying the presentation to emphasize more innovative and ambitious elements if the user is excited, for example. Finally, feedback is provided to the user via a communication terminal, allowing them to proceed with further consideration or patent application procedures.

[0176] For example, if a user excitedly inputs an idea about a "new energy efficiency technology," the emotion engine detects that excitement, and the server prioritizes presenting proposals that include innovative technological elements. This process allows users to receive appropriate feedback tailored to their emotions on the spot, enabling quick decision-making.

[0177] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0178] Step 1:

[0179] Users use a communication terminal to input text data about the idea they wish to patent or the area of ​​interest they are interested in. This input includes the specific content and purpose of the idea. This data is temporarily stored by the communication terminal.

[0180] Step 2:

[0181] The terminal sends the entered text data to the server. Simultaneously, it also sends data to an emotion analysis engine, which analyzes the user's language patterns and tone based on the input information. Here, the emotion analysis engine uses natural language processing technology to quantify emotions such as "excitement," "anticipation," and "calmness" from the input text and sends the results to the server.

[0182] Step 3:

[0183] The server uses text data received from the terminal and sentiment analysis results to retrieve existing rights information. It utilizes a patent search API to identify existing intellectual property rights information related to the user's idea. The input is text data from the user, and the output is a list of existing rights information.

[0184] Step 4:

[0185] The server generates new patent proposals using an AI model based on existing patent information. A prompt message is provided, for example, "Generate new patent proposals related to the entered technical field. Emotional state: excited." The AI ​​model operates based on this prompt and outputs new, non-duplicate patent proposals.

[0186] Step 5:

[0187] The generated rights proposal is formatted by the server, and the presented content is adjusted to take into account the user's emotional state. The server utilizes the results of the emotional analysis; for example, if the emotional state is identified as "excited," the rights proposal is refined to emphasize more innovative and ambitious elements.

[0188] Step 6:

[0189] The server returns the formatted and adjusted draft rights to the communication terminal. The terminal displays this draft rights to the user, who then uses it for further consideration. The output is the final draft rights that the user uses to make decisions such as filing a patent application.

[0190] (Application Example 2)

[0191] 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".

[0192] Because conventional technologies lacked methods for effectively reflecting the opinions and feelings of urban residents in urban development and efficiently promoting participatory urban planning, it was difficult to propose urban plans that met the diverse needs of residents.

[0193] 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.

[0194] In this invention, the server includes means for receiving user input information from a communication device, means for acquiring existing intellectual property information using a database search means based on the received input information, means including a generation module for analyzing the acquired intellectual property information and generating new, non-duplicate intellectual property proposals, means for analyzing the user's emotional state and adjusting the generated intellectual property proposals based on the analysis results, and means for presenting the adjusted intellectual property proposals to the user. This makes it possible to propose new urban planning ideas that respond to the ideas and emotions input by urban residents.

[0195] A "communication device" refers to a device used by a user to transmit input information, such as a smartphone or computer.

[0196] "User input information" refers to information about ideas and themes that users provide to the system.

[0197] A "database search means" is a means that has the function of performing a database search to obtain existing intellectual property information.

[0198] "Intellectual property information" includes information related to patents and copyrights that have already been made public.

[0199] A "generation module" is a software module used to create new intellectual asset proposals based on acquired intellectual property information.

[0200] A "means for analyzing emotional states" refers to a means that has the function of inferring the user's emotions from the input information.

[0201] "Means of adjustment" refers to means that have the function of optimizing the generated intellectual property proposal according to the user's feelings.

[0202] "Means of presentation" refers to the means of displaying the adjusted intellectual property proposal to users.

[0203] The embodiment for implementing the invention is configured as follows: The user inputs ideas or themes related to urban development using a communication device such as a smartphone. This input information is sent to a server in the cloud. The server first analyzes the user's emotional state from the input information using Google Cloud's natural language processing API. Based on the result of this emotional state, the server performs a database search and retrieves existing intellectual property information.

[0204] Next, the server analyzes the acquired intellectual property information using machine learning libraries such as TENSORFLOW (registered trademark) to generate novel, non-repeating intellectual property proposals. This generation process utilizes generative AI models such as OpenAI's GPT. The generated intellectual property proposals are then adjusted according to the user's emotional state. Specifically, a script in Python or similar language emphasizes more adventurous urban planning proposals if the user is in an excited state.

[0205] Finally, the refined intellectual property proposal is fed back to the user's communication device. Based on this feedback, the user can evaluate the urban development proposal and decide on the next steps.

[0206] For example, if a user inputs "I want more parks," the server can analyze the user's slightly dissatisfied feelings and generate a proposal for a modern eco-park. The following is an example of a prompt sent to the generating AI model:

[0207] The user entered the following idea regarding urban development: "I want more parks." Their sentiment is somewhat dissatisfied. Based on this information, generate a new urban development plan.

[0208] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0209] Step 1:

[0210] The user inputs ideas and themes related to urban development using a communication device. The input information is sent to the server in text format. The output of this step is the user's input information.

[0211] Step 2:

[0212] The server processes the received user input using Google Cloud's natural language processing API to analyze the user's emotional state. The analysis results are categorized into states such as "excited," "dissatisfied," and "neutral," and output accordingly. Here, the context and keywords of the input information are analyzed to estimate the emotion.

[0213] Step 3:

[0214] The server activates a database search function based on the sentiment analysis results to retrieve existing intellectual property information. Specifically, it searches for patent documents based on specific keywords and outputs the results. The input for this step consists of user input information and the results of the sentiment analysis.

[0215] Step 4:

[0216] The server analyzes the acquired existing intellectual property information using a machine learning algorithm based on TensorFlow and generates new, non-duplicate intellectual property proposals. Generative AI models such as OpenAI's GPT are used for this generation. The input is existing intellectual property information, and the output is new intellectual property proposals.

[0217] Step 5:

[0218] The server adjusts the generated intellectual property proposal based on the results of sentiment analysis. Specifically, it uses a Python script to highlight or remove elements according to the user's emotional state. The input for this step is the generated intellectual property proposal and the emotional state, and the output is the adjusted intellectual property proposal.

[0219] Step 6:

[0220] The server then returns the finalized intellectual property proposal to the user's communication device. The user evaluates this information and uses it for further feedback or urban planning suggestions. The input for this step is the finalized intellectual property proposal, and the output is the urban development proposal presented to the user.

[0221] 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.

[0222] 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.

[0223] 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.

[0224] [Second Embodiment]

[0225] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0226] 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.

[0227] 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).

[0228] 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.

[0229] 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.

[0230] 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).

[0231] 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.

[0232] 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.

[0233] 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.

[0234] 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.

[0235] 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.

[0236] 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".

[0237] This invention provides a system that receives input from users regarding patent ideas and areas of interest via a communication device. The system consists of a terminal and a server, the server which searches an intellectual property database based on the received information to obtain relevant existing intellectual property information.

[0238] Specifically, when a user enters a patent idea on their device, the content is sent to the server. The server analyzes this input, converts it to an appropriate format, and searches the intellectual property database using a patent search API. The retrieved existing patent information is analyzed within the server, and a new, non-duplicate intellectual property proposal is generated using a generation AI. The generated patent proposal is sent to the device and presented to the user.

[0239] This system also includes a function to read user business documents, which the server then analyzes to support the proposal of pre-prepared patent proposals. This allows users to acquire new intellectual property rights proposals with less additional time and effort.

[0240] For example, if a user wants to devise a patent for a "new energy efficiency device," they send the input from their terminal to the server, and the generating AI uses a patent search API to investigate existing related patents. Based on this investigation, the server generates a new patent proposal for the device in a non-duplicate manner and presents it to the user. The user can then smoothly proceed to the next step in patent application based on the presented proposal.

[0241] Thus, the present invention streamlines the patent acquisition process and provides a form that allows users to quickly create high-quality intellectual property drafts.

[0242] The following describes the processing flow.

[0243] Step 1:

[0244] Users input their patent ideas and areas of interest through an interface on their device. Specifically, they enter keywords and detailed descriptions into text boxes and press the submit button.

[0245] Step 2:

[0246] The terminal receives the input information and sends it to the server in the appropriate format. During this process, the input data is transferred to the server via the network.

[0247] Step 3:

[0248] The server analyzes the received user input and extracts keywords and phrases. Based on this, it constructs a request to call the patent search API.

[0249] Step 4:

[0250] The server sends a request to the patent search API, which searches the database for relevant existing patents based on the input information. The search results are returned from the API to the server.

[0251] Step 5:

[0252] The server receives information on existing patents returned from the API and analyzes them. Based on the analysis results, it calls a generation AI model to generate new patent proposals.

[0253] Step 6:

[0254] The generative AI model uses the received data to generate new patent proposals that do not overlap with existing patents. The generated proposals are returned to the server.

[0255] Step 7:

[0256] The server formats the generated patent draft into a format that is easy for the user to understand and sends it to the terminal.

[0257] Step 8:

[0258] The terminal presents the user with new patent proposals received from the server. The user can then refer to these and decide on their next course of action.

[0259] Step 9:

[0260] If necessary, users can upload their work documents and additional information to the server via their terminal, and the server will use this information for further analysis and to supplement the patent proposal.

[0261] (Example 1)

[0262] 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".

[0263] In today's highly information-driven society, acquiring new intellectual property rights is a crucial means of enhancing the competitiveness of companies and individuals. However, creating new ideas that do not overlap with existing intellectual property information is an extremely time-consuming and laborious task. Furthermore, there is a lack of effective methods for efficiently linking business-related information with new patent proposals. Therefore, a system is needed to solve these problems and streamline the generation of intellectual property proposals.

[0264] 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.

[0265] In this invention, the server includes means for receiving user input data from a communication device, means for analyzing the received input data and converting it into an appropriate format using natural language processing technology, and means for acquiring existing intellectual property information using a data retrieval module, and a generation module for generating novel intellectual property proposals that do not overlap with existing intellectual property information using a generation AI model based on the acquired intellectual property information. As a result, users can efficiently generate novel ideas that do not overlap with existing intellectual property information and easily create novel intellectual property proposals linked to business-related information.

[0266] "Communication equipment" refers to electronic devices used for sending and receiving data, and is a device that plays a role in acquiring information from users.

[0267] "User" refers to an individual or group that operates the system and inputs ideas or data.

[0268] "Input data" refers to information supplied by the user to the system via communication devices, and is used to generate intellectual property rights.

[0269] "Natural language processing technology" is a technique that allows computers to understand and analyze human language, and is used to convert input data into a specific format.

[0270] A "data retrieval module" is a program or device used to retrieve specified information by referring to a designated database.

[0271] "Intellectual property information" refers to a collection of information about existing patents and intellectual property rights, including data necessary for generating new patent proposals.

[0272] A "generative AI model" is a computer model that uses artificial intelligence technology to create new ideas and intellectual property rights proposals.

[0273] A "generation module" is a program or device for generating new intellectual property rights proposals based on acquired information.

[0274] "Business-related information" refers to all data related to the work of the organization or individual to which the user belongs, and is used as supplementary material for new patent proposals.

[0275] In order to implement the invention, the system must be constructed based on the following configuration and procedure.

[0276] The server receives user input data transmitted from communication devices. This input data contains information about ideas and areas of interest related to intellectual property rights. The server analyzes this data using natural language processing techniques and converts it into a format suitable for patent searches. This process uses general natural language processing libraries to extract relevant keywords and transform phrases.

[0277] The analyzed data is searched for in the intellectual property information database via a data search module. The online database provided by the Japan Patent Office can be used as the database. This allows the server to retrieve existing intellectual property information and, based on this, generate new, non-duplicate intellectual property proposals.

[0278] The generation process utilizes a generative AI model. This model analyzes acquired intellectual property information and generates new ideas. It is implemented on a general machine learning framework and trained to generate new ideas.

[0279] The terminal serves to provide the user with the generated intellectual property draft sent from the server. The user can review the new patent draft on the terminal and send feedback to the server as needed. This allows for a process of further refining the patent draft.

[0280] For example, if a user comes up with an idea for a "new device for clean energy," they input this idea into the terminal. The server then uses a data retrieval module to obtain relevant existing patents, and a generating AI model generates a new patent proposal based on this.

[0281] An example of a prompt message would be: "I want to develop a new patent idea for an energy efficiency device. Please research existing related patents and generate a novel idea that does not overlap."

[0282] This system streamlines the patent application process, enabling users to quickly and effectively create new intellectual property rights proposals.

[0283] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0284] Step 1:

[0285] Subject: User

[0286] The user inputs ideas related to patents and areas of interest into the system through the terminal. At this time, the user freely describes the ideas in natural language. The information input becomes data in text format.

[0287] Step 2:

[0288] Subject: Terminal

[0289] The terminal sends the data input by the user to the server. This communication is carried out using a secure protocol. The output of the terminal is the input data of the user directed to the server. This enables the server side to process the intended content of the user.

[0290] Step 3:

[0291] Subject: Server

[0292] The server analyzes the received input data of the user using natural language processing technology. The input data is in text format, which is analyzed to extract keywords and main phrases, and converted into a data format suitable for patent search. The output of the server is structured data suitable for search.

[0293] Step 4:

[0294] Subject: Server

[0295] The server searches the existing intellectual property information database using the data search module for the analyzed data. Using the structured search data as input, relevant intellectual property information is obtained. The output of the server is a list of existing patent information.

[0296] Step 5:

[0297] Subject: Server

[0298] The server generates a new intellectual property case using a generated AI model based on the acquired intellectual property information. The inputs are existing patent information and the original user input, which are analyzed to devise new, non-duplicative ideas. The output of the server is a new patent case.

[0299] Step 6:

[0300] Subject: Server

[0301] The server sends the generated new patent case to the terminal. As output, it generates data containing the details of the new patent case and provides it to the terminal. This enables the user to consider the new proposal.

[0302] Step 7:

[0303] Subject: User

[0304] The user checks the new patent case sent from the server on the terminal and examines the content of the proposal. The user provides feedback as needed and expects further adjustments to be made on the server side. The output of the user is feedback and a decision on whether to accept the proposal.

[0305] (Application Example 1)

[0306] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0307] Based on existing intellectual property right information, it is required to quickly and efficiently generate new intellectual property right cases and apply them to the payment management system as the application target. However, in the current system, the input information of the user is not efficiently analyzed to generate new cases that do not overlap with the existing intellectual property right information, and the application using dynamic generation technology is insufficient. Therefore, the provision of a new system is desired.

[0308] 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.

[0309] In this invention, the server includes means for receiving user input information from a communication device, means for acquiring existing intellectual property rights information using a database search means based on the received input information, means including a generation module for analyzing the acquired intellectual property rights information and generating new, non-duplicate intellectual property rights proposals, and means for presenting the generated intellectual property rights proposals to the user and applying them to a payment management system using dynamic generation technology. This enables the user to quickly and efficiently generate new intellectual property rights proposals and apply them to a payment management protocol.

[0310] A "communication device" is a device that has the ability to send and receive information, and is particularly used to receive input information from a user.

[0311] "User input information" refers to a collection of data and instructions that users provide to the system, including information such as patent ideas and areas of interest.

[0312] "Database search methods" refer to methods and techniques for searching for information within a database using specific algorithms and obtaining the necessary information.

[0313] "Intellectual property information" refers to a collection of existing information concerning intellectual property such as patents, trademarks, and copyrights.

[0314] A "generation module" is a structure consisting of software or hardware for generating new intellectual property rights proposals based on specific inputs.

[0315] "Dynamic generation technology" is a technology that generates information in real time according to the situation and conditions, and is particularly used in applications such as payment management systems.

[0316] A "payment management system" is a system for managing and processing information related to electronic transactions and settlements.

[0317] This invention aims to efficiently patent new user ideas in an electronic payment system via a communication device. A specific embodiment of the system is shown below.

[0318] First, the user uses a smartphone or other device to input ideas about new payment methods or security protocols they want to patent. This input is then sent to the server via a communication device.

[0319] After receiving the input, the server analyzes it using a natural language processing library (e.g., spaCy or NLTK) and, if necessary, searches for intellectual property information via a patent search API such as the Google Patents API. Based on the existing intellectual property information obtained as a search result, the server generates new intellectual property proposals that do not overlap with the generation modules within the server, using a generation AI (e.g., OpenAI's GPT-3).

[0320] The newly generated intellectual property rights proposals are processed using dynamic generation technology to make them suitable for implementation within the payment management system. These processed proposals are then sent back to the user's terminal and presented to them. This approach allows users to quickly and efficiently generate their own patent proposals and translate them into concrete implementations within the context of electronic payments.

[0321] For example, if a user conceives of a "new payment system using QR codes," the server can research existing QR code-related patents and propose a new security protocol.

[0322] Examples of prompts to input into a generative AI model:

[0323] "Generate a patent idea for a new payment system using QR codes. Consider existing patent information and ensure the idea is novel."

[0324] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0325] Step 1:

[0326] Users input ideas for new payment methods or security protocols using a terminal. The input information is transmitted to a server as digital text via a communication device. The input format is free-form text.

[0327] Step 2:

[0328] The server receives input information sent by the user and parses the text data using a natural language processing library (e.g., spaCy or NLTK). This parsing extracts keywords and important concepts contained in the input information. The output is a list of the parsed keywords.

[0329] Step 3:

[0330] The server uses a patent search API (e.g., Google Patents API) to search intellectual property databases based on an analyzed keyword list. The input is a keyword list, and the output is relevant existing intellectual property information.

[0331] Step 4:

[0332] The server analyzes the acquired intellectual property information and uses a generative AI (e.g., OpenAI's GPT-3) to generate novel, non-overlapping intellectual property proposals. The input is existing patent information, and the generative AI generates new patent proposals that match the ideas of the patents as output.

[0333] Step 5:

[0334] The newly generated intellectual property rights proposals are processed using dynamic generation technology to make them suitable for implementation in an electronic payment system. The input is the generated patent proposal, and the output is the proposal adapted to the target system.

[0335] Step 6:

[0336] The server sends the processed patent draft to the terminal, presents it to the user, and helps them review and decide whether to adopt the generated patent draft. The input is the processed patent draft, and the output is the displayed content as feedback to the user.

[0337] 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.

[0338] This invention is a system that generates new intellectual property rights proposals based on ideas and themes input by the user, and presents these proposals while taking the user's emotional state into consideration. This system mainly consists of a terminal, a server, and an emotion engine.

[0339] The user inputs text about the idea they want to patent or their areas of interest through their device. This input information is sent from the device to the server, and at the same time, the user's emotional state is analyzed by an emotion engine. This emotion is inferred from the language patterns and tone of the input, and the analysis results are sent to the server.

[0340] The server uses a patent search API to search for existing intellectual property rights information based on the user's input and retrieves the results. Based on this retrieved information, the server uses a generative AI to generate new, non-duplicate intellectual property rights proposals.

[0341] The generated intellectual property proposals are formatted by the server, and their presentation is adjusted based on the results of emotional state analysis by the emotion engine. For example, if the analysis indicates that the user is excited, the proposals will be adjusted to emphasize more ambitious ideas.

[0342] This allows users to receive new patent proposals not only in terms of technical novelty, but also in a way that resonates emotionally. The presented intellectual property proposals are fed back to the user through their device, allowing them to proceed with further consideration and patent application procedures based on this feedback.

[0343] For example, if a user excitedly inputs an idea about a "new energy efficiency technology," the emotion engine detects the excitement, and the server, based on this, prioritizes presenting intellectual property proposals that include innovative technological elements. This process allows the user to receive accurate feedback that matches their emotions on the spot, enabling quick decision-making.

[0344] The following describes the processing flow.

[0345] Step 1:

[0346] Users input their patent ideas and areas of interest in technology through the terminal's interface. Specifically, they fill in the content in a text box and click the submit button to send the information to the terminal.

[0347] Step 2:

[0348] The device passes the received input information to the emotion engine, which recognizes the user's emotions. The emotion engine analyzes the language patterns of the input text and determines the user's current emotional state (e.g., excitement, calmness, doubt, etc.).

[0349] Step 3:

[0350] The terminal sends user input information, including analysis results, to the server. This information is transferred to the server via the communication network.

[0351] Step 4:

[0352] The server analyzes the received information and uses a patent search API to retrieve relevant existing intellectual property information from the database. During this process, it generates an appropriate search query based on the user's input and sends a request to the API.

[0353] Step 5:

[0354] The server uses a generative AI model to generate novel, non-duplicate intellectual property rights proposals based on existing patent information obtained from the API. The generative AI executes algorithms to create new ideas while referencing existing data.

[0355] Step 6:

[0356] The server formats the generated intellectual property proposals into a format that is easy for the user to understand. It adjusts the presentation content considering the emotional state determined by the emotion engine. For example, if the user is excited, the proposal will be presented in a way that emphasizes innovative elements.

[0357] Step 7:

[0358] The server sends the formatted patent draft and sentiment analysis results to the terminal.

[0359] Step 8:

[0360] The terminal receives data from the server and displays it on the user interface. Based on this, the user reviews the proposed intellectual property rights and considers the next action.

[0361] (Example 2)

[0362] 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".

[0363] Conventional intellectual property rights proposal generation systems lacked feedback that considered the user's emotional state. As a result, while the generated rights proposals technically met the novelty requirements, they failed to adequately address the user's emotions and creative expectations. Consequently, users found it difficult to empathize with the proposed rights proposals, making effective decision-making and prompt responses challenging.

[0364] 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.

[0365] In this invention, the server includes means for receiving user information from a communication terminal, means for analyzing the received information and the user's emotional state, means for acquiring existing rights information using a data storage device based on the analysis results, and means for presenting the generated rights proposal while taking the user's emotional state into consideration. This makes it possible to present novel and highly empathetic rights proposals that reflect the user's emotional state.

[0366] A "communication terminal" is a device used to input user information and transmit it to a server.

[0367] "User information" refers to text data about ideas and areas of interest entered by the user.

[0368] "Emotional state" refers to the emotional state analyzed based on information entered by the user, and is a numerical representation of emotions such as excitement or calmness.

[0369] A "data storage device" refers to a database used to store existing rights information and to search and retrieve it as needed.

[0370] "Rights information" refers to information about existing intellectual property rights, including data on patents and technical documents.

[0371] A "generative AI model" refers to artificial intelligence technology used to generate new rights proposals based on given data.

[0372] A "proposal for rights" refers to a concept for newly proposed intellectual property rights based on information provided by the user and existing rights information.

[0373] This invention is a system that generates new intellectual property rights proposals based on the user's ideas and presents these proposals while considering the user's emotional state. This system mainly consists of a communication terminal, a server, and an emotion analysis engine.

[0374] The user uses a communication terminal to input text data about the idea they want to patent or their areas of interest. The communication terminal receives this information and sends it to the server. Simultaneously, the data is sent to an emotion analysis engine, which analyzes the user's emotional state from language patterns and tone. This analysis uses natural language processing technology to quantify the user's emotional state.

[0375] The server uses its data storage device based on the received user information and accesses a patent search API to search for existing rights information. Here, existing intellectual property rights information is identified and retrieved. Based on this information, a new rights proposal is created using a generative AI model. The generative AI model operates based on prompt statements, such as "Generate a new patent proposal related to the entered technology field. The emotional state is excited."

[0376] The generated new patent proposals are formatted by the server and presented to the user, taking into account their analyzed emotional state. This adjustment may include modifying the presentation to emphasize more innovative and ambitious elements if the user is excited, for example. Finally, feedback is provided to the user via a communication terminal, allowing them to proceed with further consideration or patent application procedures.

[0377] For example, if a user excitedly inputs an idea about a "new energy efficiency technology," the emotion engine detects that excitement, and the server prioritizes presenting proposals that include innovative technological elements. This process allows users to receive appropriate feedback tailored to their emotions on the spot, enabling quick decision-making.

[0378] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0379] Step 1:

[0380] Users use a communication terminal to input text data about the idea they wish to patent or the area of ​​interest they are interested in. This input includes the specific content and purpose of the idea. This data is temporarily stored by the communication terminal.

[0381] Step 2:

[0382] The terminal sends the entered text data to the server. Simultaneously, it also sends data to an emotion analysis engine, which analyzes the user's language patterns and tone based on the input information. Here, the emotion analysis engine uses natural language processing technology to quantify emotions such as "excitement," "anticipation," and "calmness" from the input text and sends the results to the server.

[0383] Step 3:

[0384] The server uses text data received from the terminal and sentiment analysis results to retrieve existing rights information. It utilizes a patent search API to identify existing intellectual property rights information related to the user's idea. The input is text data from the user, and the output is a list of existing rights information.

[0385] Step 4:

[0386] The server generates new patent proposals using an AI model based on existing patent information. A prompt message is provided, for example, "Generate new patent proposals related to the entered technical field. Emotional state: excited." The AI ​​model operates based on this prompt and outputs new, non-duplicate patent proposals.

[0387] Step 5:

[0388] The generated rights proposal is formatted by the server, and the presented content is adjusted to take into account the user's emotional state. The server utilizes the results of the emotional analysis; for example, if the emotional state is identified as "excited," the rights proposal is refined to emphasize more innovative and ambitious elements.

[0389] Step 6:

[0390] The server returns the formatted and adjusted draft rights to the communication terminal. The terminal displays this draft rights to the user, who then uses it for further consideration. The output is the final draft rights that the user uses to make decisions such as filing a patent application.

[0391] (Application Example 2)

[0392] 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."

[0393] Because conventional technologies lacked methods for effectively reflecting the opinions and feelings of urban residents in urban development and efficiently promoting participatory urban planning, it was difficult to propose urban plans that met the diverse needs of residents.

[0394] 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.

[0395] In this invention, the server includes means for receiving user input information from a communication device, means for acquiring existing intellectual property information using a database search means based on the received input information, means including a generation module for analyzing the acquired intellectual property information and generating new, non-duplicate intellectual property proposals, means for analyzing the user's emotional state and adjusting the generated intellectual property proposals based on the analysis results, and means for presenting the adjusted intellectual property proposals to the user. This makes it possible to propose new urban planning ideas that respond to the ideas and emotions input by urban residents.

[0396] A "communication device" refers to a device used by a user to transmit input information, such as a smartphone or computer.

[0397] "User input information" refers to information about ideas and themes that users provide to the system.

[0398] A "database search means" is a means that has the function of performing a database search to obtain existing intellectual property information.

[0399] "Intellectual property information" includes information related to patents and copyrights that have already been made public.

[0400] A "generation module" is a software module used to create new intellectual asset proposals based on acquired intellectual property information.

[0401] A "means for analyzing emotional states" refers to a means that has the function of inferring the user's emotions from the input information.

[0402] "Means of adjustment" refers to means that have the function of optimizing the generated intellectual property proposal according to the user's feelings.

[0403] "Means of presentation" refers to the means of displaying the adjusted intellectual property proposal to users.

[0404] The embodiment for implementing the invention is configured as follows: The user inputs ideas or themes related to urban development using a communication device such as a smartphone. This input information is sent to a server in the cloud. The server first analyzes the user's emotional state from the input information using Google Cloud's natural language processing API. Based on the result of this emotional state, the server performs a database search and retrieves existing intellectual property information.

[0405] Next, the server analyzes the acquired intellectual property information using machine learning libraries such as TensorFlow and generates novel, non-repeating intellectual property proposals. Generative AI models such as OpenAI's GPT are used in this generation process. The generated intellectual property proposals are then adjusted according to the user's emotional state. Specifically, a script in Python or similar language emphasizes more adventurous urban planning proposals if the user is in an excited state.

[0406] Finally, the refined intellectual property proposal is fed back to the user's communication device. Based on this feedback, the user can evaluate the urban development proposal and decide on the next steps.

[0407] For example, if a user inputs "I want more parks," the server can analyze the user's slightly dissatisfied feelings and generate a proposal for a modern eco-park. The following is an example of a prompt sent to the generating AI model:

[0408] The user entered the following idea regarding urban development: "I want more parks." Their sentiment is somewhat dissatisfied. Based on this information, generate a new urban development plan.

[0409] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0410] Step 1:

[0411] The user inputs ideas and themes related to urban development using a communication device. The input information is sent to the server in text format. The output of this step is the user's input information.

[0412] Step 2:

[0413] The server processes the received user input using Google Cloud's natural language processing API to analyze the user's emotional state. The analysis results are categorized into states such as "excited," "dissatisfied," and "neutral," and output accordingly. Here, the context and keywords of the input information are analyzed to estimate the emotion.

[0414] Step 3:

[0415] The server activates a database search function based on the sentiment analysis results to retrieve existing intellectual property information. Specifically, it searches for patent documents based on specific keywords and outputs the results. The input for this step consists of user input information and the results of the sentiment analysis.

[0416] Step 4:

[0417] The server analyzes the acquired existing intellectual property information using a machine learning algorithm based on TensorFlow and generates new, non-duplicate intellectual property proposals. Generative AI models such as OpenAI's GPT are used for this generation. The input is existing intellectual property information, and the output is new intellectual property proposals.

[0418] Step 5:

[0419] The server adjusts the generated intellectual property proposal based on the results of sentiment analysis. Specifically, it uses a Python script to highlight or remove elements according to the user's emotional state. The input for this step is the generated intellectual property proposal and the emotional state, and the output is the adjusted intellectual property proposal.

[0420] Step 6:

[0421] The server then returns the finalized intellectual property proposal to the user's communication device. The user evaluates this information and uses it for further feedback or urban planning suggestions. The input for this step is the finalized intellectual property proposal, and the output is the urban development proposal presented to the user.

[0422] 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.

[0423] 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.

[0424] 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.

[0425] [Third Embodiment]

[0426] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0427] 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.

[0428] 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).

[0429] 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.

[0430] 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.

[0431] 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).

[0432] 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.

[0433] 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.

[0434] 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.

[0435] 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.

[0436] 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.

[0437] 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".

[0438] This invention provides a system that receives input from users regarding patent ideas and areas of interest via a communication device. The system consists of a terminal and a server, the server which searches an intellectual property database based on the received information to obtain relevant existing intellectual property information.

[0439] Specifically, when a user enters a patent idea on their device, the content is sent to the server. The server analyzes this input, converts it to an appropriate format, and searches the intellectual property database using a patent search API. The retrieved existing patent information is analyzed within the server, and a new, non-duplicate intellectual property proposal is generated using a generation AI. The generated patent proposal is sent to the device and presented to the user.

[0440] This system also includes a function to read user business documents, which the server then analyzes to support the proposal of pre-prepared patent proposals. This allows users to acquire new intellectual property rights proposals with less additional time and effort.

[0441] For example, if a user wants to devise a patent for a "new energy efficiency device," they send the input from their terminal to the server, and the generating AI uses a patent search API to investigate existing related patents. Based on this investigation, the server generates a new patent proposal for the device in a non-duplicate manner and presents it to the user. The user can then smoothly proceed to the next step in patent application based on the presented proposal.

[0442] Thus, the present invention streamlines the patent acquisition process and provides a form that allows users to quickly create high-quality intellectual property drafts.

[0443] The following describes the processing flow.

[0444] Step 1:

[0445] Users input their patent ideas and areas of interest through an interface on their device. Specifically, they enter keywords and detailed descriptions into text boxes and press the submit button.

[0446] Step 2:

[0447] The terminal receives the input information and sends it to the server in the appropriate format. During this process, the input data is transferred to the server via the network.

[0448] Step 3:

[0449] The server analyzes the received user input and extracts keywords and phrases. Based on this, it constructs a request to call the patent search API.

[0450] Step 4:

[0451] The server sends a request to the patent search API, which searches the database for relevant existing patents based on the input information. The search results are returned from the API to the server.

[0452] Step 5:

[0453] The server receives information on existing patents returned from the API and analyzes them. Based on the analysis results, it calls a generation AI model to generate new patent proposals.

[0454] Step 6:

[0455] The generative AI model uses the received data to generate new patent proposals that do not overlap with existing patents. The generated proposals are returned to the server.

[0456] Step 7:

[0457] The server formats the generated patent draft into a format that is easy for the user to understand and sends it to the terminal.

[0458] Step 8:

[0459] The terminal presents the user with new patent proposals received from the server. The user can then refer to these and decide on their next course of action.

[0460] Step 9:

[0461] If necessary, users can upload their work documents and additional information to the server via their terminal, and the server will use this information for further analysis and to supplement the patent proposal.

[0462] (Example 1)

[0463] 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."

[0464] In today's highly information-driven society, acquiring new intellectual property rights is a crucial means of enhancing the competitiveness of companies and individuals. However, creating new ideas that do not overlap with existing intellectual property information is an extremely time-consuming and laborious task. Furthermore, there is a lack of effective methods for efficiently linking business-related information with new patent proposals. Therefore, a system is needed to solve these problems and streamline the generation of intellectual property proposals.

[0465] 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.

[0466] In this invention, the server includes means for receiving user input data from a communication device, means for analyzing the received input data and converting it into an appropriate format using natural language processing technology, and means for acquiring existing intellectual property information using a data retrieval module, and a generation module for generating novel intellectual property proposals that do not overlap with existing intellectual property information using a generation AI model based on the acquired intellectual property information. As a result, users can efficiently generate novel ideas that do not overlap with existing intellectual property information and easily create novel intellectual property proposals linked to business-related information.

[0467] "Communication equipment" refers to electronic devices used for sending and receiving data, and is a device that plays a role in acquiring information from users.

[0468] "User" refers to an individual or group that operates the system and inputs ideas or data.

[0469] "Input data" refers to information supplied by the user to the system via communication devices, and is used to generate intellectual property rights.

[0470] "Natural language processing technology" is a technique that allows computers to understand and analyze human language, and is used to convert input data into a specific format.

[0471] A "data retrieval module" is a program or device used to retrieve specified information by referring to a designated database.

[0472] "Intellectual property information" refers to a collection of information about existing patents and intellectual property rights, including data necessary for generating new patent proposals.

[0473] A "generative AI model" is a computer model that uses artificial intelligence technology to create new ideas and intellectual property rights proposals.

[0474] A "generation module" is a program or device for generating new intellectual property rights proposals based on acquired information.

[0475] "Business-related information" refers to all data related to the work of the organization or individual to which the user belongs, and is used as supplementary material for new patent proposals.

[0476] In order to implement the invention, the system must be constructed based on the following configuration and procedure.

[0477] The server receives user input data transmitted from communication devices. This input data contains information about ideas and areas of interest related to intellectual property rights. The server analyzes this data using natural language processing techniques and converts it into a format suitable for patent searches. This process uses general natural language processing libraries to extract relevant keywords and transform phrases.

[0478] The analyzed data is searched for in the intellectual property information database via a data search module. The online database provided by the Japan Patent Office can be used as the database. This allows the server to retrieve existing intellectual property information and, based on this, generate new, non-duplicate intellectual property proposals.

[0479] The generation process utilizes a generative AI model. This model analyzes acquired intellectual property information and generates new ideas. It is implemented on a general machine learning framework and trained to generate new ideas.

[0480] The terminal serves to provide the user with the generated intellectual property draft sent from the server. The user can review the new patent draft on the terminal and send feedback to the server as needed. This allows for a process of further refining the patent draft.

[0481] For example, if a user comes up with an idea for a "new device for clean energy," they input this idea into the terminal. The server then uses a data retrieval module to obtain relevant existing patents, and a generating AI model generates a new patent proposal based on this.

[0482] An example of a prompt message would be: "I want to develop a new patent idea for an energy efficiency device. Please research existing related patents and generate a novel idea that does not overlap."

[0483] This system streamlines the patent application process, enabling users to quickly and effectively create new intellectual property rights proposals.

[0484] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0485] Step 1:

[0486] Subject: User

[0487] Users input their patent-related ideas and areas of interest into the system via a terminal. They freely describe their ideas in natural language. The input information is in text format.

[0488] Step 2:

[0489] Subject: terminal

[0490] The terminal sends the data entered by the user to the server. This communication is conducted using a secure protocol. The output of the terminal is the user's input data directed to the server. This allows the server to process the user's intended content.

[0491] Step 3:

[0492] Subject: Server

[0493] The server analyzes the user's input data using natural language processing techniques. The input data is in text format; the server analyzes it to extract keywords and key phrases and converts it into a data format suitable for patent searches. The server's output is structured data suitable for searching.

[0494] Step 4:

[0495] Subject: Server

[0496] The server searches existing intellectual property information databases using a data retrieval module based on the analyzed data. It uses structured search data as input to retrieve relevant intellectual property information. The server's output is a list of existing patent information.

[0497] Step 5:

[0498] Subject: Server

[0499] The server generates new intellectual property proposals using a generative AI model based on acquired intellectual property information. It receives existing patent information and original user input as input, analyzes them, and devises new, non-repeating ideas. The server's output is a new patent proposal.

[0500] Step 6:

[0501] Subject: Server

[0502] The server sends the generated new patent proposal to the terminal. As output, it generates data containing details of the new patent proposal and provides it to the terminal. This allows the user to consider the new proposal.

[0503] Step 7:

[0504] Subject: User

[0505] The user reviews the proposed new patent on their terminal, receiving it from the server and examining its contents. They provide feedback as needed, expecting further adjustments to be made on the server side. The user's output consists of their feedback and their decision regarding the acceptance or rejection of the proposal.

[0506] (Application Example 1)

[0507] 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."

[0508] There is a need to quickly and efficiently generate new intellectual property rights proposals based on existing intellectual property rights information and apply them to payment management systems. However, current systems are insufficient in efficiently analyzing user input information, generating new proposals that do not overlap with existing intellectual property rights information, and utilizing dynamic generation technology. Therefore, the provision of a new system is desired.

[0509] 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.

[0510] In this invention, the server includes means for receiving user input information from a communication device, means for acquiring existing intellectual property rights information using a database search means based on the received input information, means including a generation module for analyzing the acquired intellectual property rights information and generating new, non-duplicate intellectual property rights proposals, and means for presenting the generated intellectual property rights proposals to the user and applying them to a payment management system using dynamic generation technology. This enables the user to quickly and efficiently generate new intellectual property rights proposals and apply them to a payment management protocol.

[0511] A "communication device" is a device that has the ability to send and receive information, and is particularly used to receive input information from a user.

[0512] "User input information" refers to a collection of data and instructions that users provide to the system, including information such as patent ideas and areas of interest.

[0513] "Database search methods" refer to methods and techniques for searching for information within a database using specific algorithms and obtaining the necessary information.

[0514] "Intellectual property information" refers to a collection of existing information concerning intellectual property such as patents, trademarks, and copyrights.

[0515] A "generation module" is a structure consisting of software or hardware for generating new intellectual property rights proposals based on specific inputs.

[0516] "Dynamic generation technology" is a technology that generates information in real time according to the situation and conditions, and is particularly used in applications such as payment management systems.

[0517] A "payment management system" is a system for managing and processing information related to electronic transactions and settlements.

[0518] This invention aims to efficiently patent new user ideas in an electronic payment system via a communication device. A specific embodiment of the system is shown below.

[0519] First, the user uses a smartphone or other device to input ideas about new payment methods or security protocols they want to patent. This input is then sent to the server via a communication device.

[0520] After receiving the input, the server analyzes it using a natural language processing library (e.g., spaCy or NLTK) and, if necessary, searches for intellectual property information via a patent search API such as the Google Patents API. Based on the existing intellectual property information obtained as a search result, the server generates new intellectual property proposals that do not overlap with the generation modules within the server, using a generation AI (e.g., OpenAI's GPT-3).

[0521] The newly generated intellectual property rights proposals are processed using dynamic generation technology to make them suitable for implementation within the payment management system. These processed proposals are then sent back to the user's terminal and presented to them. This approach allows users to quickly and efficiently generate their own patent proposals and translate them into concrete implementations within the context of electronic payments.

[0522] For example, if a user conceives of a "new payment system using QR codes," the server can research existing QR code-related patents and propose a new security protocol.

[0523] Examples of prompts to input into a generative AI model:

[0524] "Generate a patent idea for a new payment system using QR codes. Consider existing patent information and ensure the idea is novel."

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

[0526] Step 1:

[0527] Users input ideas for new payment methods or security protocols using a terminal. The input information is transmitted to a server as digital text via a communication device. The input format is free-form text.

[0528] Step 2:

[0529] The server receives input information sent by the user and parses the text data using a natural language processing library (e.g., spaCy or NLTK). This parsing extracts keywords and important concepts contained in the input information. The output is a list of the parsed keywords.

[0530] Step 3:

[0531] The server uses a patent search API (e.g., Google Patents API) to search intellectual property databases based on an analyzed keyword list. The input is a keyword list, and the output is relevant existing intellectual property information.

[0532] Step 4:

[0533] The server analyzes the acquired intellectual property information and uses a generative AI (e.g., OpenAI's GPT-3) to generate novel, non-overlapping intellectual property proposals. The input is existing patent information, and the generative AI generates new patent proposals that match the ideas of the patents as output.

[0534] Step 5:

[0535] The newly generated intellectual property rights proposals are processed using dynamic generation technology to make them suitable for implementation in an electronic payment system. The input is the generated patent proposal, and the output is the proposal adapted to the target system.

[0536] Step 6:

[0537] The server sends the processed patent draft to the terminal, presents it to the user, and helps them review and decide whether to adopt the generated patent draft. The input is the processed patent draft, and the output is the displayed content as feedback to the user.

[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 is a system that generates new intellectual property rights proposals based on ideas and themes input by the user, and presents these proposals while taking the user's emotional state into consideration. This system mainly consists of a terminal, a server, and an emotion engine.

[0540] The user inputs text about the idea they want to patent or their areas of interest through their device. This input information is sent from the device to the server, and at the same time, the user's emotional state is analyzed by an emotion engine. This emotion is inferred from the language patterns and tone of the input, and the analysis results are sent to the server.

[0541] The server uses a patent search API to search for existing intellectual property rights information based on the user's input and retrieves the results. Based on this retrieved information, the server uses a generative AI to generate new, non-duplicate intellectual property rights proposals.

[0542] The generated intellectual property proposals are formatted by the server, and their presentation is adjusted based on the results of emotional state analysis by the emotion engine. For example, if the analysis indicates that the user is excited, the proposals will be adjusted to emphasize more ambitious ideas.

[0543] This allows users to receive new patent proposals not only in terms of technical novelty, but also in a way that resonates emotionally. The presented intellectual property proposals are fed back to the user through their device, allowing them to proceed with further consideration and patent application procedures based on this feedback.

[0544] For example, if a user excitedly inputs an idea about a "new energy efficiency technology," the emotion engine detects the excitement, and the server, based on this, prioritizes presenting intellectual property proposals that include innovative technological elements. This process allows the user to receive accurate feedback that matches their emotions on the spot, enabling quick decision-making.

[0545] The following describes the processing flow.

[0546] Step 1:

[0547] Users input their patent ideas and areas of interest in technology through the terminal's interface. Specifically, they fill in the content in a text box and click the submit button to send the information to the terminal.

[0548] Step 2:

[0549] The device passes the received input information to the emotion engine, which recognizes the user's emotions. The emotion engine analyzes the language patterns of the input text and determines the user's current emotional state (e.g., excitement, calmness, doubt, etc.).

[0550] Step 3:

[0551] The terminal sends user input information, including analysis results, to the server. This information is transferred to the server via the communication network.

[0552] Step 4:

[0553] The server analyzes the received information and uses a patent search API to retrieve relevant existing intellectual property information from the database. During this process, it generates an appropriate search query based on the user's input and sends a request to the API.

[0554] Step 5:

[0555] The server uses a generative AI model to generate novel, non-duplicate intellectual property rights proposals based on existing patent information obtained from the API. The generative AI executes algorithms to create new ideas while referencing existing data.

[0556] Step 6:

[0557] The server formats the generated intellectual property proposals into a format that is easy for the user to understand. It adjusts the presentation content considering the emotional state determined by the emotion engine. For example, if the user is excited, the proposal will be presented in a way that emphasizes innovative elements.

[0558] Step 7:

[0559] The server sends the formatted patent draft and sentiment analysis results to the terminal.

[0560] Step 8:

[0561] The terminal receives data from the server and displays it on the user interface. Based on this, the user reviews the proposed intellectual property rights and considers the next action.

[0562] (Example 2)

[0563] 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."

[0564] Conventional intellectual property rights proposal generation systems lacked feedback that considered the user's emotional state. As a result, while the generated rights proposals technically met the novelty requirements, they failed to adequately address the user's emotions and creative expectations. Consequently, users found it difficult to empathize with the proposed rights proposals, making effective decision-making and prompt responses challenging.

[0565] 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.

[0566] In this invention, the server includes means for receiving user information from a communication terminal, means for analyzing the received information and the user's emotional state, means for acquiring existing rights information using a data storage device based on the analysis results, and means for presenting the generated rights proposal while taking the user's emotional state into consideration. This makes it possible to present novel and highly empathetic rights proposals that reflect the user's emotional state.

[0567] A "communication terminal" is a device used to input user information and transmit it to a server.

[0568] "User information" refers to text data about ideas and areas of interest entered by the user.

[0569] "Emotional state" refers to the emotional state analyzed based on information entered by the user, and is a numerical representation of emotions such as excitement or calmness.

[0570] A "data storage device" refers to a database used to store existing rights information and to search and retrieve it as needed.

[0571] "Rights information" refers to information about existing intellectual property rights, including data on patents and technical documents.

[0572] A "generative AI model" refers to artificial intelligence technology used to generate new rights proposals based on given data.

[0573] A "proposal for rights" refers to a concept for newly proposed intellectual property rights based on information provided by the user and existing rights information.

[0574] This invention is a system that generates new intellectual property rights proposals based on the user's ideas and presents these proposals while considering the user's emotional state. This system mainly consists of a communication terminal, a server, and an emotion analysis engine.

[0575] The user uses a communication terminal to input text data about the idea they want to patent or their areas of interest. The communication terminal receives this information and sends it to the server. Simultaneously, the data is sent to an emotion analysis engine, which analyzes the user's emotional state from language patterns and tone. This analysis uses natural language processing technology to quantify the user's emotional state.

[0576] The server uses its data storage device based on the received user information and accesses a patent search API to search for existing rights information. Here, existing intellectual property rights information is identified and retrieved. Based on this information, a new rights proposal is created using a generative AI model. The generative AI model operates based on prompt statements, such as "Generate a new patent proposal related to the entered technology field. The emotional state is excited."

[0577] The generated new patent proposals are formatted by the server and presented to the user, taking into account their analyzed emotional state. This adjustment may include modifying the presentation to emphasize more innovative and ambitious elements if the user is excited, for example. Finally, feedback is provided to the user via a communication terminal, allowing them to proceed with further consideration or patent application procedures.

[0578] For example, if a user excitedly inputs an idea about a "new energy efficiency technology," the emotion engine detects that excitement, and the server prioritizes presenting proposals that include innovative technological elements. This process allows users to receive appropriate feedback tailored to their emotions on the spot, enabling quick decision-making.

[0579] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0580] Step 1:

[0581] Users use a communication terminal to input text data about the idea they wish to patent or the area of ​​interest they are interested in. This input includes the specific content and purpose of the idea. This data is temporarily stored by the communication terminal.

[0582] Step 2:

[0583] The terminal sends the entered text data to the server. Simultaneously, it also sends data to an emotion analysis engine, which analyzes the user's language patterns and tone based on the input information. Here, the emotion analysis engine uses natural language processing technology to quantify emotions such as "excitement," "anticipation," and "calmness" from the input text and sends the results to the server.

[0584] Step 3:

[0585] The server uses text data received from the terminal and sentiment analysis results to retrieve existing rights information. It utilizes a patent search API to identify existing intellectual property rights information related to the user's idea. The input is text data from the user, and the output is a list of existing rights information.

[0586] Step 4:

[0587] The server generates new patent proposals using an AI model based on existing patent information. A prompt message is provided, for example, "Generate new patent proposals related to the entered technical field. Emotional state: excited." The AI ​​model operates based on this prompt and outputs new, non-duplicate patent proposals.

[0588] Step 5:

[0589] The generated rights proposal is formatted by the server, and the presented content is adjusted to take into account the user's emotional state. The server utilizes the results of the emotional analysis; for example, if the emotional state is identified as "excited," the rights proposal is refined to emphasize more innovative and ambitious elements.

[0590] Step 6:

[0591] The server returns the formatted and adjusted draft rights to the communication terminal. The terminal displays this draft rights to the user, who then uses it for further consideration. The output is the final draft rights that the user uses to make decisions such as filing a patent application.

[0592] (Application Example 2)

[0593] 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."

[0594] Because conventional technologies lacked methods for effectively reflecting the opinions and feelings of urban residents in urban development and efficiently promoting participatory urban planning, it was difficult to propose urban plans that met the diverse needs of residents.

[0595] 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.

[0596] In this invention, the server includes means for receiving user input information from a communication device, means for acquiring existing intellectual property information using a database search means based on the received input information, means including a generation module for analyzing the acquired intellectual property information and generating new, non-duplicate intellectual property proposals, means for analyzing the user's emotional state and adjusting the generated intellectual property proposals based on the analysis results, and means for presenting the adjusted intellectual property proposals to the user. This makes it possible to propose new urban planning ideas that respond to the ideas and emotions input by urban residents.

[0597] A "communication device" refers to a device used by a user to transmit input information, such as a smartphone or computer.

[0598] "User input information" refers to information about ideas and themes that users provide to the system.

[0599] A "database search means" is a means that has the function of performing a database search to obtain existing intellectual property information.

[0600] "Intellectual property information" includes information related to patents and copyrights that have already been made public.

[0601] A "generation module" is a software module used to create new intellectual asset proposals based on acquired intellectual property information.

[0602] A "means for analyzing emotional states" refers to a means that has the function of inferring the user's emotions from the input information.

[0603] "Means of adjustment" refers to means that have the function of optimizing the generated intellectual property proposal according to the user's feelings.

[0604] "Means of presentation" refers to the means of displaying the adjusted intellectual property proposal to users.

[0605] The embodiment for implementing the invention is configured as follows: The user inputs ideas or themes related to urban development using a communication device such as a smartphone. This input information is sent to a server in the cloud. The server first analyzes the user's emotional state from the input information using Google Cloud's natural language processing API. Based on the result of this emotional state, the server performs a database search and retrieves existing intellectual property information.

[0606] Next, the server analyzes the acquired intellectual property information using machine learning libraries such as TensorFlow and generates novel, non-repeating intellectual property proposals. Generative AI models such as OpenAI's GPT are used in this generation process. The generated intellectual property proposals are then adjusted according to the user's emotional state. Specifically, a script in Python or similar language emphasizes more adventurous urban planning proposals if the user is in an excited state.

[0607] Finally, the refined intellectual property proposal is fed back to the user's communication device. Based on this feedback, the user can evaluate the urban development proposal and decide on the next steps.

[0608] For example, if a user inputs "I want more parks," the server can analyze the user's slightly dissatisfied feelings and generate a proposal for a modern eco-park. The following is an example of a prompt sent to the generating AI model:

[0609] The user entered the following idea regarding urban development: "I want more parks." Their sentiment is somewhat dissatisfied. Based on this information, generate a new urban development plan.

[0610] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0611] Step 1:

[0612] The user inputs ideas and themes related to urban development using a communication device. The input information is sent to the server in text format. The output of this step is the user's input information.

[0613] Step 2:

[0614] The server processes the received user input using Google Cloud's natural language processing API to analyze the user's emotional state. The analysis results are categorized into states such as "excited," "dissatisfied," and "neutral," and output accordingly. Here, the context and keywords of the input information are analyzed to estimate the emotion.

[0615] Step 3:

[0616] The server activates a database search function based on the sentiment analysis results to retrieve existing intellectual property information. Specifically, it searches for patent documents based on specific keywords and outputs the results. The input for this step consists of user input information and the results of the sentiment analysis.

[0617] Step 4:

[0618] The server analyzes the acquired existing intellectual property information using a machine learning algorithm based on TensorFlow and generates new, non-duplicate intellectual property proposals. Generative AI models such as OpenAI's GPT are used for this generation. The input is existing intellectual property information, and the output is new intellectual property proposals.

[0619] Step 5:

[0620] The server adjusts the generated intellectual property proposal based on the results of sentiment analysis. Specifically, it uses a Python script to highlight or remove elements according to the user's emotional state. The input for this step is the generated intellectual property proposal and the emotional state, and the output is the adjusted intellectual property proposal.

[0621] Step 6:

[0622] The server then returns the finalized intellectual property proposal to the user's communication device. The user evaluates this information and uses it for further feedback or urban planning suggestions. The input for this step is the finalized intellectual property proposal, and the output is the urban development proposal presented to the user.

[0623] 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.

[0624] 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.

[0625] 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.

[0626] [Fourth Embodiment]

[0627] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0628] 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.

[0629] 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).

[0630] 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.

[0631] 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.

[0632] 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).

[0633] 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.

[0634] 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.

[0635] 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.

[0636] 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.

[0637] 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.

[0638] 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.

[0639] 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".

[0640] This invention provides a system that receives input from users regarding patent ideas and areas of interest via a communication device. The system consists of a terminal and a server, the server which searches an intellectual property database based on the received information to obtain relevant existing intellectual property information.

[0641] Specifically, when a user enters a patent idea on their device, the content is sent to the server. The server analyzes this input, converts it to an appropriate format, and searches the intellectual property database using a patent search API. The retrieved existing patent information is analyzed within the server, and a new, non-duplicate intellectual property proposal is generated using a generation AI. The generated patent proposal is sent to the device and presented to the user.

[0642] This system also includes a function to read user business documents, which the server then analyzes to support the proposal of pre-prepared patent proposals. This allows users to acquire new intellectual property rights proposals with less additional time and effort.

[0643] For example, if a user wants to devise a patent for a "new energy efficiency device," they send the input from their terminal to the server, and the generating AI uses a patent search API to investigate existing related patents. Based on this investigation, the server generates a new patent proposal for the device in a non-duplicate manner and presents it to the user. The user can then smoothly proceed to the next step in patent application based on the presented proposal.

[0644] Thus, the present invention streamlines the patent acquisition process and provides a form that allows users to quickly create high-quality intellectual property drafts.

[0645] The following describes the processing flow.

[0646] Step 1:

[0647] Users input their patent ideas and areas of interest through an interface on their device. Specifically, they enter keywords and detailed descriptions into text boxes and press the submit button.

[0648] Step 2:

[0649] The terminal receives the input information and sends it to the server in the appropriate format. During this process, the input data is transferred to the server via the network.

[0650] Step 3:

[0651] The server analyzes the received user input and extracts keywords and phrases. Based on this, it constructs a request to call the patent search API.

[0652] Step 4:

[0653] The server sends a request to the patent search API, which searches the database for relevant existing patents based on the input information. The search results are returned from the API to the server.

[0654] Step 5:

[0655] The server receives information on existing patents returned from the API and analyzes them. Based on the analysis results, it calls a generation AI model to generate new patent proposals.

[0656] Step 6:

[0657] The generative AI model uses the received data to generate new patent proposals that do not overlap with existing patents. The generated proposals are returned to the server.

[0658] Step 7:

[0659] The server formats the generated patent draft into a format that is easy for the user to understand and sends it to the terminal.

[0660] Step 8:

[0661] The terminal presents the user with new patent proposals received from the server. The user can then refer to these and decide on their next course of action.

[0662] Step 9:

[0663] If necessary, users can upload their work documents and additional information to the server via their terminal, and the server will use this information for further analysis and to supplement the patent proposal.

[0664] (Example 1)

[0665] 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".

[0666] In today's highly information-driven society, acquiring new intellectual property rights is a crucial means of enhancing the competitiveness of companies and individuals. However, creating new ideas that do not overlap with existing intellectual property information is an extremely time-consuming and laborious task. Furthermore, there is a lack of effective methods for efficiently linking business-related information with new patent proposals. Therefore, a system is needed to solve these problems and streamline the generation of intellectual property proposals.

[0667] 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.

[0668] In this invention, the server includes means for receiving user input data from a communication device, means for analyzing the received input data and converting it into an appropriate format using natural language processing technology, and means for acquiring existing intellectual property information using a data retrieval module, and a generation module for generating novel intellectual property proposals that do not overlap with existing intellectual property information using a generation AI model based on the acquired intellectual property information. As a result, users can efficiently generate novel ideas that do not overlap with existing intellectual property information and easily create novel intellectual property proposals linked to business-related information.

[0669] "Communication equipment" refers to electronic devices used for sending and receiving data, and is a device that plays a role in acquiring information from users.

[0670] "User" refers to an individual or group that operates the system and inputs ideas or data.

[0671] "Input data" refers to information supplied by the user to the system via communication devices, and is used to generate intellectual property rights.

[0672] "Natural language processing technology" is a technique that allows computers to understand and analyze human language, and is used to convert input data into a specific format.

[0673] A "data retrieval module" is a program or device used to retrieve specified information by referring to a designated database.

[0674] "Intellectual property information" refers to a collection of information about existing patents and intellectual property rights, including data necessary for generating new patent proposals.

[0675] A "generative AI model" is a computer model that uses artificial intelligence technology to create new ideas and intellectual property rights proposals.

[0676] A "generation module" is a program or device for generating new intellectual property rights proposals based on acquired information.

[0677] "Business-related information" refers to all data related to the work of the organization or individual to which the user belongs, and is used as supplementary material for new patent proposals.

[0678] In order to implement the invention, the system must be constructed based on the following configuration and procedure.

[0679] The server receives user input data transmitted from communication devices. This input data contains information about ideas and areas of interest related to intellectual property rights. The server analyzes this data using natural language processing techniques and converts it into a format suitable for patent searches. This process uses general natural language processing libraries to extract relevant keywords and transform phrases.

[0680] The analyzed data is searched for in the intellectual property information database via a data search module. The online database provided by the Japan Patent Office can be used as the database. This allows the server to retrieve existing intellectual property information and, based on this, generate new, non-duplicate intellectual property proposals.

[0681] The generation process utilizes a generative AI model. This model analyzes acquired intellectual property information and generates new ideas. It is implemented on a general machine learning framework and trained to generate new ideas.

[0682] The terminal serves to provide the user with the generated intellectual property draft sent from the server. The user can review the new patent draft on the terminal and send feedback to the server as needed. This allows for a process of further refining the patent draft.

[0683] For example, if a user comes up with an idea for a "new device for clean energy," they input this idea into the terminal. The server then uses a data retrieval module to obtain relevant existing patents, and a generating AI model generates a new patent proposal based on this.

[0684] An example of a prompt message would be: "I want to develop a new patent idea for an energy efficiency device. Please research existing related patents and generate a novel idea that does not overlap."

[0685] This system streamlines the patent application process, enabling users to quickly and effectively create new intellectual property rights proposals.

[0686] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0687] Step 1:

[0688] Subject: User

[0689] Users input their patent-related ideas and areas of interest into the system via a terminal. They freely describe their ideas in natural language. The input information is in text format.

[0690] Step 2:

[0691] Subject: terminal

[0692] The terminal sends the data entered by the user to the server. This communication is conducted using a secure protocol. The output of the terminal is the user's input data directed to the server. This allows the server to process the user's intended content.

[0693] Step 3:

[0694] Subject: Server

[0695] The server analyzes the user's input data using natural language processing techniques. The input data is in text format; the server analyzes it to extract keywords and key phrases and converts it into a data format suitable for patent searches. The server's output is structured data suitable for searching.

[0696] Step 4:

[0697] Subject: Server

[0698] The server searches existing intellectual property information databases using a data retrieval module based on the analyzed data. It uses structured search data as input to retrieve relevant intellectual property information. The server's output is a list of existing patent information.

[0699] Step 5:

[0700] Subject: Server

[0701] The server generates new intellectual property proposals using a generative AI model based on acquired intellectual property information. It receives existing patent information and original user input as input, analyzes them, and devises new, non-repeating ideas. The server's output is a new patent proposal.

[0702] Step 6:

[0703] Subject: Server

[0704] The server sends the generated new patent proposal to the terminal. As output, it generates data containing details of the new patent proposal and provides it to the terminal. This allows the user to consider the new proposal.

[0705] Step 7:

[0706] Subject: User

[0707] The user reviews the proposed new patent on their terminal, receiving it from the server and examining its contents. They provide feedback as needed, expecting further adjustments to be made on the server side. The user's output consists of their feedback and their decision regarding the acceptance or rejection of the proposal.

[0708] (Application Example 1)

[0709] 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".

[0710] There is a need to quickly and efficiently generate new intellectual property rights proposals based on existing intellectual property rights information and apply them to payment management systems. However, current systems are insufficient in efficiently analyzing user input information, generating new proposals that do not overlap with existing intellectual property rights information, and utilizing dynamic generation technology. Therefore, the provision of a new system is desired.

[0711] 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.

[0712] In this invention, the server includes means for receiving user input information from a communication device, means for acquiring existing intellectual property rights information using a database search means based on the received input information, means including a generation module for analyzing the acquired intellectual property rights information and generating new, non-duplicate intellectual property rights proposals, and means for presenting the generated intellectual property rights proposals to the user and applying them to a payment management system using dynamic generation technology. This enables the user to quickly and efficiently generate new intellectual property rights proposals and apply them to a payment management protocol.

[0713] A "communication device" is a device that has the ability to send and receive information, and is particularly used to receive input information from a user.

[0714] "User input information" refers to a collection of data and instructions that users provide to the system, including information such as patent ideas and areas of interest.

[0715] "Database search methods" refer to methods and techniques for searching for information within a database using specific algorithms and obtaining the necessary information.

[0716] "Intellectual property information" refers to a collection of existing information concerning intellectual property such as patents, trademarks, and copyrights.

[0717] A "generation module" is a structure consisting of software or hardware for generating new intellectual property rights proposals based on specific inputs.

[0718] "Dynamic generation technology" is a technology that generates information in real time according to the situation and conditions, and is particularly used in applications such as payment management systems.

[0719] A "payment management system" is a system for managing and processing information related to electronic transactions and settlements.

[0720] This invention aims to efficiently patent new user ideas in an electronic payment system via a communication device. A specific embodiment of the system is shown below.

[0721] First, the user uses a smartphone or other device to input ideas about new payment methods or security protocols they want to patent. This input is then sent to the server via a communication device.

[0722] After receiving the input, the server analyzes it using a natural language processing library (e.g., spaCy or NLTK) and, if necessary, searches for intellectual property information via a patent search API such as the Google Patents API. Based on the existing intellectual property information obtained as a search result, the server generates new intellectual property proposals that do not overlap with the generation modules within the server, using a generation AI (e.g., OpenAI's GPT-3).

[0723] The newly generated intellectual property rights proposals are processed using dynamic generation technology to make them suitable for implementation within the payment management system. These processed proposals are then sent back to the user's terminal and presented to them. This approach allows users to quickly and efficiently generate their own patent proposals and translate them into concrete implementations within the context of electronic payments.

[0724] For example, if a user conceives of a "new payment system using QR codes," the server can research existing QR code-related patents and propose a new security protocol.

[0725] Examples of prompts to input into a generative AI model:

[0726] "Generate a patent idea for a new payment system using QR codes. Consider existing patent information and ensure the idea is novel."

[0727] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0728] Step 1:

[0729] Users input ideas for new payment methods or security protocols using a terminal. The input information is transmitted to a server as digital text via a communication device. The input format is free-form text.

[0730] Step 2:

[0731] The server receives input information sent by the user and parses the text data using a natural language processing library (e.g., spaCy or NLTK). This parsing extracts keywords and important concepts contained in the input information. The output is a list of the parsed keywords.

[0732] Step 3:

[0733] The server uses a patent search API (e.g., Google Patents API) to search intellectual property databases based on an analyzed keyword list. The input is a keyword list, and the output is relevant existing intellectual property information.

[0734] Step 4:

[0735] The server analyzes the acquired intellectual property information and uses a generative AI (e.g., OpenAI's GPT-3) to generate novel, non-overlapping intellectual property proposals. The input is existing patent information, and the generative AI generates new patent proposals that match the ideas of the patents as output.

[0736] Step 5:

[0737] The newly generated intellectual property rights proposals are processed using dynamic generation technology to make them suitable for implementation in an electronic payment system. The input is the generated patent proposal, and the output is the proposal adapted to the target system.

[0738] Step 6:

[0739] The server sends the processed patent draft to the terminal, presents it to the user, and helps them review and decide whether to adopt the generated patent draft. The input is the processed patent draft, and the output is the displayed content as feedback to the user.

[0740] 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.

[0741] This invention is a system that generates new intellectual property rights proposals based on ideas and themes input by the user, and presents these proposals while taking the user's emotional state into consideration. This system mainly consists of a terminal, a server, and an emotion engine.

[0742] The user inputs text about the idea they want to patent or their areas of interest through their device. This input information is sent from the device to the server, and at the same time, the user's emotional state is analyzed by an emotion engine. This emotion is inferred from the language patterns and tone of the input, and the analysis results are sent to the server.

[0743] The server uses a patent search API to search for existing intellectual property rights information based on the user's input and retrieves the results. Based on this retrieved information, the server uses a generative AI to generate new, non-duplicate intellectual property rights proposals.

[0744] The generated intellectual property proposals are formatted by the server, and their presentation is adjusted based on the results of emotional state analysis by the emotion engine. For example, if the analysis indicates that the user is excited, the proposals will be adjusted to emphasize more ambitious ideas.

[0745] This allows users to receive new patent proposals not only in terms of technical novelty, but also in a way that resonates emotionally. The presented intellectual property proposals are fed back to the user through their device, allowing them to proceed with further consideration and patent application procedures based on this feedback.

[0746] For example, if a user excitedly inputs an idea about a "new energy efficiency technology," the emotion engine detects the excitement, and the server, based on this, prioritizes presenting intellectual property proposals that include innovative technological elements. This process allows the user to receive accurate feedback that matches their emotions on the spot, enabling quick decision-making.

[0747] The following describes the processing flow.

[0748] Step 1:

[0749] Users input their patent ideas and areas of interest in technology through the terminal's interface. Specifically, they fill in the content in a text box and click the submit button to send the information to the terminal.

[0750] Step 2:

[0751] The device passes the received input information to the emotion engine, which recognizes the user's emotions. The emotion engine analyzes the language patterns of the input text and determines the user's current emotional state (e.g., excitement, calmness, doubt, etc.).

[0752] Step 3:

[0753] The terminal sends user input information, including analysis results, to the server. This information is transferred to the server via the communication network.

[0754] Step 4:

[0755] The server analyzes the received information and uses a patent search API to retrieve relevant existing intellectual property information from the database. During this process, it generates an appropriate search query based on the user's input and sends a request to the API.

[0756] Step 5:

[0757] The server uses a generative AI model to generate novel, non-duplicate intellectual property rights proposals based on existing patent information obtained from the API. The generative AI executes algorithms to create new ideas while referencing existing data.

[0758] Step 6:

[0759] The server formats the generated intellectual property proposals into a format that is easy for the user to understand. It adjusts the presentation content considering the emotional state determined by the emotion engine. For example, if the user is excited, the proposal will be presented in a way that emphasizes innovative elements.

[0760] Step 7:

[0761] The server sends the formatted patent draft and sentiment analysis results to the terminal.

[0762] Step 8:

[0763] The terminal receives data from the server and displays it on the user interface. Based on this, the user reviews the proposed intellectual property rights and considers the next action.

[0764] (Example 2)

[0765] 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".

[0766] Conventional intellectual property rights proposal generation systems lacked feedback that considered the user's emotional state. As a result, while the generated rights proposals technically met the novelty requirements, they failed to adequately address the user's emotions and creative expectations. Consequently, users found it difficult to empathize with the proposed rights proposals, making effective decision-making and prompt responses challenging.

[0767] 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.

[0768] In this invention, the server includes means for receiving user information from a communication terminal, means for analyzing the received information and the user's emotional state, means for acquiring existing rights information using a data storage device based on the analysis results, and means for presenting the generated rights proposal while taking the user's emotional state into consideration. This makes it possible to present novel and highly empathetic rights proposals that reflect the user's emotional state.

[0769] A "communication terminal" is a device used to input user information and transmit it to a server.

[0770] "User information" refers to text data about ideas and areas of interest entered by the user.

[0771] "Emotional state" refers to the emotional state analyzed based on information entered by the user, and is a numerical representation of emotions such as excitement or calmness.

[0772] A "data storage device" refers to a database used to store existing rights information and to search and retrieve it as needed.

[0773] "Rights information" refers to information about existing intellectual property rights, including data on patents and technical documents.

[0774] A "generative AI model" refers to artificial intelligence technology used to generate new rights proposals based on given data.

[0775] A "proposal for rights" refers to a concept for newly proposed intellectual property rights based on information provided by the user and existing rights information.

[0776] This invention is a system that generates new intellectual property rights proposals based on the user's ideas and presents these proposals while considering the user's emotional state. This system mainly consists of a communication terminal, a server, and an emotion analysis engine.

[0777] The user uses a communication terminal to input text data about the idea they want to patent or their areas of interest. The communication terminal receives this information and sends it to the server. Simultaneously, the data is sent to an emotion analysis engine, which analyzes the user's emotional state from language patterns and tone. This analysis uses natural language processing technology to quantify the user's emotional state.

[0778] The server uses its data storage device based on the received user information and accesses a patent search API to search for existing rights information. Here, existing intellectual property rights information is identified and retrieved. Based on this information, a new rights proposal is created using a generative AI model. The generative AI model operates based on prompt statements, such as "Generate a new patent proposal related to the entered technology field. The emotional state is excited."

[0779] The generated new patent proposals are formatted by the server and presented to the user, taking into account their analyzed emotional state. This adjustment may include modifying the presentation to emphasize more innovative and ambitious elements if the user is excited, for example. Finally, feedback is provided to the user via a communication terminal, allowing them to proceed with further consideration or patent application procedures.

[0780] For example, if a user excitedly inputs an idea about a "new energy efficiency technology," the emotion engine detects that excitement, and the server prioritizes presenting proposals that include innovative technological elements. This process allows users to receive appropriate feedback tailored to their emotions on the spot, enabling quick decision-making.

[0781] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0782] Step 1:

[0783] Users use a communication terminal to input text data about the idea they wish to patent or the area of ​​interest they are interested in. This input includes the specific content and purpose of the idea. This data is temporarily stored by the communication terminal.

[0784] Step 2:

[0785] The terminal sends the entered text data to the server. Simultaneously, it also sends data to an emotion analysis engine, which analyzes the user's language patterns and tone based on the input information. Here, the emotion analysis engine uses natural language processing technology to quantify emotions such as "excitement," "anticipation," and "calmness" from the input text and sends the results to the server.

[0786] Step 3:

[0787] The server uses text data received from the terminal and sentiment analysis results to retrieve existing rights information. It utilizes a patent search API to identify existing intellectual property rights information related to the user's idea. The input is text data from the user, and the output is a list of existing rights information.

[0788] Step 4:

[0789] The server generates new patent proposals using an AI model based on existing patent information. A prompt message is provided, for example, "Generate new patent proposals related to the entered technical field. Emotional state: excited." The AI ​​model operates based on this prompt and outputs new, non-duplicate patent proposals.

[0790] Step 5:

[0791] The generated rights proposal is formatted by the server, and the presented content is adjusted to take into account the user's emotional state. The server utilizes the results of the emotional analysis; for example, if the emotional state is identified as "excited," the rights proposal is refined to emphasize more innovative and ambitious elements.

[0792] Step 6:

[0793] The server returns the formatted and adjusted draft rights to the communication terminal. The terminal displays this draft rights to the user, who then uses it for further consideration. The output is the final draft rights that the user uses to make decisions such as filing a patent application.

[0794] (Application Example 2)

[0795] 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".

[0796] Because conventional technologies lacked methods for effectively reflecting the opinions and feelings of urban residents in urban development and efficiently promoting participatory urban planning, it was difficult to propose urban plans that met the diverse needs of residents.

[0797] 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.

[0798] In this invention, the server includes means for receiving user input information from a communication device, means for acquiring existing intellectual property information using a database search means based on the received input information, means including a generation module for analyzing the acquired intellectual property information and generating new, non-duplicate intellectual property proposals, means for analyzing the user's emotional state and adjusting the generated intellectual property proposals based on the analysis results, and means for presenting the adjusted intellectual property proposals to the user. This makes it possible to propose new urban planning ideas that respond to the ideas and emotions input by urban residents.

[0799] A "communication device" refers to a device used by a user to transmit input information, such as a smartphone or computer.

[0800] "User input information" refers to information about ideas and themes that users provide to the system.

[0801] A "database search means" is a means that has the function of performing a database search to obtain existing intellectual property information.

[0802] "Intellectual property information" includes information related to patents and copyrights that have already been made public.

[0803] A "generation module" is a software module used to create new intellectual asset proposals based on acquired intellectual property information.

[0804] A "means for analyzing emotional states" refers to a means that has the function of inferring the user's emotions from the input information.

[0805] "Means of adjustment" refers to means that have the function of optimizing the generated intellectual property proposal according to the user's feelings.

[0806] "Means of presentation" refers to the means of displaying the adjusted intellectual property proposal to users.

[0807] The embodiment for implementing the invention is configured as follows: The user inputs ideas or themes related to urban development using a communication device such as a smartphone. This input information is sent to a server in the cloud. The server first analyzes the user's emotional state from the input information using Google Cloud's natural language processing API. Based on the result of this emotional state, the server performs a database search and retrieves existing intellectual property information.

[0808] Next, the server analyzes the acquired intellectual property information using machine learning libraries such as TensorFlow and generates novel, non-repeating intellectual property proposals. Generative AI models such as OpenAI's GPT are used in this generation process. The generated intellectual property proposals are then adjusted according to the user's emotional state. Specifically, a script in Python or similar language emphasizes more adventurous urban planning proposals if the user is in an excited state.

[0809] Finally, the refined intellectual property proposal is fed back to the user's communication device. Based on this feedback, the user can evaluate the urban development proposal and decide on the next steps.

[0810] For example, if a user inputs "I want more parks," the server can analyze the user's slightly dissatisfied feelings and generate a proposal for a modern eco-park. The following is an example of a prompt sent to the generating AI model:

[0811] The user entered the following idea regarding urban development: "I want more parks." Their sentiment is somewhat dissatisfied. Based on this information, generate a new urban development plan.

[0812] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0813] Step 1:

[0814] The user inputs ideas and themes related to urban development using a communication device. The input information is sent to the server in text format. The output of this step is the user's input information.

[0815] Step 2:

[0816] The server processes the received user input using Google Cloud's natural language processing API to analyze the user's emotional state. The analysis results are categorized into states such as "excited," "dissatisfied," and "neutral," and output accordingly. Here, the context and keywords of the input information are analyzed to estimate the emotion.

[0817] Step 3:

[0818] The server activates a database search function based on the sentiment analysis results to retrieve existing intellectual property information. Specifically, it searches for patent documents based on specific keywords and outputs the results. The input for this step consists of user input information and the results of the sentiment analysis.

[0819] Step 4:

[0820] The server analyzes the acquired existing intellectual property information using a machine learning algorithm based on TensorFlow and generates new, non-duplicate intellectual property proposals. Generative AI models such as OpenAI's GPT are used for this generation. The input is existing intellectual property information, and the output is new intellectual property proposals.

[0821] Step 5:

[0822] The server adjusts the generated intellectual property proposal based on the results of sentiment analysis. Specifically, it uses a Python script to highlight or remove elements according to the user's emotional state. The input for this step is the generated intellectual property proposal and the emotional state, and the output is the adjusted intellectual property proposal.

[0823] Step 6:

[0824] The server then returns the finalized intellectual property proposal to the user's communication device. The user evaluates this information and uses it for further feedback or urban planning suggestions. The input for this step is the finalized intellectual property proposal, and the output is the urban development proposal presented to the user.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] 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.

[0830] 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.

[0831] 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.

[0832] 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.

[0833] 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."

[0834] 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.

[0835] 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.

[0836] 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.

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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.

[0842] 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.

[0843] 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.

[0844] 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.

[0845] 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.

[0846] The following is further disclosed regarding the embodiments described above.

[0847] (Claim 1)

[0848] A means for receiving user input information from a communication device,

[0849] A means for obtaining existing intellectual property rights information using a database search means based on received input information,

[0850] A means including a generation module that analyzes acquired intellectual property rights information and generates new, non-duplicate intellectual property rights proposals,

[0851] A means of presenting the generated intellectual property rights proposal to the user,

[0852] A system that includes this.

[0853] (Claim 2)

[0854] The system according to claim 1, further comprising a generation module that automatically supplements and proposes the generated intellectual property rights draft based on the user's business materials.

[0855] (Claim 3)

[0856] The system according to claim 1, further comprising means for analyzing user business data and generating intellectual property rights proposals using the analysis results.

[0857] "Example 1"

[0858] (Claim 1)

[0859] A means for receiving user input data from a communication device,

[0860] A means of analyzing received input data, converting it into an appropriate format using natural language processing technology, and obtaining existing intellectual property information using a data retrieval module,

[0861] A means including a generation module that generates novel, non-duplicate intellectual property proposals using a generation AI model based on acquired intellectual property information,

[0862] Means for providing the generated intellectual property draft to the user,

[0863] A data processing device that includes a data processing device.

[0864] (Claim 2)

[0865] The data processing device according to claim 1, further comprising a generation module that automatically complements and proposes generated intellectual property proposals based on the user's business-related information.

[0866] (Claim 3)

[0867] The data processing device according to claim 1, further comprising means for analyzing the user's business-related information and generating intellectual property proposals using the analysis results.

[0868] "Application Example 1"

[0869] (Claim 1)

[0870] A means for receiving user input information from a communication device,

[0871] A means for obtaining existing intellectual property rights information using a database search means based on received input information,

[0872] A means including a generation module that analyzes acquired intellectual property rights information and generates new, non-duplicate intellectual property rights proposals,

[0873] A means of presenting the generated intellectual property rights proposal to the user,

[0874] A means of applying the generated intellectual property rights draft to a payment management system using dynamic generation technology,

[0875] A system that includes this.

[0876] (Claim 2)

[0877] The system according to claim 1, further comprising a generation module that automatically supplements and proposes the generated intellectual property rights draft based on the user's business materials.

[0878] (Claim 3)

[0879] The system according to claim 1, further comprising means for analyzing a user's business data, generating a draft intellectual property rights using the analysis results, and applying it to a payment management protocol.

[0880] "Example 2 of combining an emotion engine"

[0881] (Claim 1)

[0882] A means of receiving user information from a communication terminal,

[0883] A means for analyzing the received information and the user's emotional state,

[0884] A means of acquiring existing rights information using a data storage device based on the analysis results,

[0885] A method for generating new rights proposals using an AI model based on acquired rights information,

[0886] A means of presenting the generated rights proposal while taking into account the user's emotional state,

[0887] A system that includes this.

[0888] (Claim 2)

[0889] The system according to claim 1, further comprising means for automatically supplementing and proposing the generated rights proposal based on the user's business information.

[0890] (Claim 3)

[0891] The system according to claim 1, further comprising means for analyzing user business information and generating a proposed rights using the results of the analysis.

[0892] "Application example 2 when combining with an emotional engine"

[0893] (Claim 1)

[0894] A means for receiving user input information from a communication device,

[0895] A means for obtaining existing intellectual property rights information using a database search means based on received input information,

[0896] A means including a generation module that analyzes acquired intellectual property rights information and generates new, non-duplicate intellectual property proposals,

[0897] A means of analyzing the emotional state of users and adjusting the intellectual property proposals generated based on the analysis results,

[0898] A means of presenting the adjusted intellectual property proposal to the user,

[0899] A system that includes this.

[0900] (Claim 2)

[0901] The system according to claim 1, further comprising a generation module that automatically complements and proposes the generated intellectual property draft based on the user's business materials.

[0902] (Claim 3)

[0903] The system according to claim 1, further comprising means for analyzing user business data and generating intellectual property proposals using the analysis results. [Explanation of Symbols]

[0904] 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 for receiving user input information from a communication device, A means for obtaining existing intellectual property rights information using a database search means based on received input information, A means including a generation module that analyzes acquired intellectual property rights information and generates new, non-duplicate intellectual property rights proposals, A means of presenting the generated intellectual property rights proposal to the user, A means of applying the generated intellectual property rights draft to a payment management system using dynamic generation technology, A system that includes this.

2. The system according to claim 1, further comprising a generation module that automatically supplements and proposes the generated intellectual property rights draft based on the user's business materials.

3. The system according to claim 1, further comprising means for analyzing a user's business data, generating a draft intellectual property rights using the analysis results, and applying it to a payment management protocol.

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