System

Abstract

A system is provided.SOLUTION: A system, comprising: means for receiving material related to an invention; means for analyzing the received material and extracting key keywords and concepts; means for generating a patent idea from the extracted information; means for receiving user feedback and refining the patent idea; means for searching for a competitive patent based on the patent idea; means for providing information of the competitive patent to a user; means for generating a patent application; and means for submitting the generated patent application to the patent office.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] The process of applying for intellectual property rights, from discovering an idea to filing a patent application, is complicated and requires a lot of time and effort. In particular, the process of realizing the idea, adjusting the format of the application, adjusting the writing style, and researching competing patents is complicated and inefficient. As a result, the efficiency of patent applications is reduced, and inventors are unable to concentrate on their original creative activities. [Means for solving the problem]

[0005] The present invention provides a system that streamlines intellectual property applications and reduces the burden on inventors. Specifically, the system includes a means for receiving materials related to an invention, a means for analyzing the received materials and extracting important keywords and concepts, and a means for generating patent ideas from the extracted information. The system also includes a means for receiving user feedback and improving the patent ideas, a means for searching for competing patents based on the patent ideas, and a means for providing information on competing patents to the user. The system further includes a means for generating patent application documents and a means for submitting the generated patent application documents to the Patent Office. This allows for the entire patent application process to be consistently automated, enabling efficient and effective intellectual property applications.

[0006] "Invention-related materials" refers to data such as documents and emails that contain information about the technical concepts and technologies that form the basis of the patent application.

[0007] "Means for receiving" refers to the hardware and software functions for incorporating user-provided materials into the system.

[0008] "Means for analysis" refers to the function of analyzing received materials using natural language processing technology and extracting important keywords and concepts.

[0009] "Means for extracting keywords and concepts" refers to the function of identifying important words and phrases that are central to the patent idea from the analyzed materials.

[0010] "Means for generating patent ideas" is a function for constructing new patent ideas based on extracted keywords and concepts.

[0011] "Means for improvement" refers to the function of further developing patent ideas based on feedback from users.

[0012] The "means for searching competing patents" is a function for searching existing patents related to a patent idea and finding potentially competing patents.

[0013] The "means for generating patent application documents" is a function for automatically creating documents for patent applications based on patent ideas.

[0014] "Means for submission to the Patent Office" refers to a function that supports the process of submitting the generated patent application documents to the Patent Office's online system. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

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

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] Understood. I have prepared the following "Mode for carrying out the invention" based on the scope of the claims.

[0037] ---

[0038] This invention relates to a system and method for efficiently filing intellectual property applications. This system generates patent ideas and files patent applications through multiple steps, with a server, a terminal, and a user playing their respective roles.

[0039] Data entry and analysis

[0040] The user uses the terminal to prepare and organize policy documents and emails between related parties related to the invention. The terminal is equipped with a means to upload these documents to the server. The server receives the uploaded data and analyzes it using a natural language processing (NLP) engine.

[0041] During the analysis process, the server tokenizes the received data and performs morphological analysis to extract important keywords and concepts, such as "AI algorithm," "time efficiency," and "improved accuracy."

[0042] Idea generation and refinement

[0043] The server generates hypotheses for patent ideas based on the extracted keywords and concepts. The hypotheses are then presented to the user's device. The user can then provide feedback on the proposed tentative patent ideas, such as adding "methods for further refinement" or "applications to specific industries."

[0044] The server receives user feedback and refines the patent idea using an AI model. The improved idea is then presented to the user again, and this process is repeated until the user is satisfied.

[0045] Competitive research and document generation

[0046] After the idea is confirmed, the server searches the patent database for existing patents that may conflict with the patent idea. The results of the conflict search are reported to the user and necessary adjustments are proposed.

[0047] The server generates a patent application document based on the finalized idea. In this process, the server uses a natural language generation (NLG) engine to create a document in accordance with the patent application format.

[0048] Application Procedure

[0049] The user uses a terminal to check the generated patent application document and instruct the server on any necessary corrections. The server reflects the correction instructions and completes the final patent application document. The server then processes the completed document for submission to the Patent Office's online system.

[0050] Specific examples

[0051] For example, if a user wants to apply for a patent for a new AI algorithm, they first upload their policy documents and related emails to the server. The server analyzes these and extracts keywords such as "new AI algorithm," "time efficiency," and "improved accuracy." Based on these keywords, the server generates a hypothesis for the patent idea: "A new AI algorithm that achieves efficiency through automation." Based on the user's feedback, the server refines and optimizes the idea.

[0052] The server then searches the patent database for competing patents and reports the results to the user. Based on the finalized idea, the server generates a patent application document, which is then submitted to the patent office after the user has confirmed and revised it.

[0053] In this way, the present invention is a system that enables the entire process from the discovery of a patent idea to the application procedure to be carried out efficiently and effectively.

[0054] The processing flow will be explained below.

[0055] Step 1:

[0056] The user prepares invention-related policy documents and emails between related parties on the terminal, which then uploads the data to the server.

[0057] Step 2:

[0058] The server receives the uploaded data and then invokes a natural language processing (NLP) engine to tokenize the data and perform morphological analysis to extract important keywords and concepts.

[0059] Step 3:

[0060] The server generates hypotheses for patent ideas based on the extracted keywords and concepts, a process that provides initial idea suggestions based on similar ideas and an existing knowledge base.

[0061] Step 4:

[0062] The server presents the generated hypotheses for the patent idea to the user's terminal, which the user confirms.

[0063] Step 5:

[0064] Users can input feedback on the presented patent idea via a terminal, for example, suggesting "ways to apply this idea to a specific industry" or "ways to further improve accuracy."

[0065] Step 6:

[0066] The device sends user feedback data to a server, which analyzes the received feedback and uses AI models to refine the idea.

[0067] Step 7:

[0068] The server then presents the refined patent idea to the user again, and this process is repeated until the user is satisfied with the result.

[0069] Step 8:

[0070] The server accesses a patent database to search for existing patents that may be competing with the patent idea, and reports the search results to the user.

[0071] Step 9:

[0072] The server automatically generates patent application documents based on the confirmed patent idea, using a natural language generation (NLG) engine to refine the document's format and writing style.

[0073] Step 10:

[0074] The user checks the patent application document generated on the terminal and instructs the terminal to make any necessary corrections, which are then sent to the server.

[0075] Step 11:

[0076] The server reflects the user's correction instructions and finally completes the patent application document.

[0077] Step 12:

[0078] The server submits the completed patent application to the Patent Office's online system, where users can monitor the application status and provide additional information or materials as needed.

[0079] This streamlines the entire process from discovering a patent idea to filing an application.

[0080] Example 1

[0081] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0082] The current intellectual property application process requires a lot of time and effort, is inefficient in terms of patent idea generation, competitive research, and application document preparation, and places a heavy burden on users. This problem makes it difficult for inventors to protect their new ideas in a timely manner, which can result in a loss of competitiveness. Furthermore, existing systems rely on manual processes for analyzing information and refining ideas, which risks reducing the accuracy and speed of the work. To solve these issues, there is a need for a system that can automate the entire intellectual property application process efficiently and effectively.

[0083] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0084] In this invention, the server includes means for receiving digital documents, means for analyzing the received documents and extracting important information, means for generating intellectual property ideas from the extracted information, means for receiving user opinions and improving the intellectual property ideas, means for searching existing intellectual property based on the intellectual property ideas, means for presenting search results to the user, means for generating intellectual property application documents, and means for submitting the generated intellectual property application documents, thereby automating the entire intellectual property application process and enabling rapid and accurate patent idea generation, competitive research, and application document preparation and submission.

[0085] A "digital document" is a document containing information stored in electronic form that can be viewed, edited, or transmitted using a computer or other electronic device.

[0086] "Important information" refers to keywords and concepts contained within digital documents that are key to patent idea generation and competitive research.

[0087] "Intellectual property idea" refers to a concept or proposal for an invention or technical solution that is the subject of a patent application.

[0088] "User Feedback" means feedback, comments, or suggestions for correction provided by a User regarding an Intellectual Property Idea.

[0089] "Existing intellectual property" refers to technologies and inventions that have already been patented and are publicly available and registered in patent databases, etc.

[0090] "Search results" refers to the list of relevant information and patents that are obtained when searching existing intellectual property.

[0091] "Intellectual Property Application Document" refers to the official patent application document submitted to the Patent Office, which contains details of the invention and its technical features.

[0092] This invention relates to a system and method for efficiently filing intellectual property applications. In this system, a server, a terminal, and a user each play their respective roles, and the system generates patent ideas and files patent applications through multiple steps.

[0093] Entering and Submitting Data

[0094] The user prepares and organizes policy documents and emails between related parties related to the invention. The user uploads these documents to the terminal. The terminal has a means to send these documents to the server.

[0095] Data analysis

[0096] The server receives the uploaded digital document. It then analyzes the received digital document using a natural language processing (NLP) engine to extract important information. During the analysis process, the server tokenizes the received data and performs morphological analysis to extract important keywords and concepts. For example, keywords such as "new AI algorithm," "time efficiency," and "improved accuracy" are extracted.

[0097] Idea generation

[0098] The server generates hypotheses for intellectual property ideas based on the extracted keywords and concepts. The hypotheses are then presented to the user's device. For example, a "patent idea for a technology that uses a new AI algorithm to improve time efficiency and accuracy" might be generated.

[0099] Brushing up ideas

[0100] Users provide feedback on the proposed tentative patent idea, such as adding "further refinement methods" or "applications to specific industries." The server receives the user's feedback and refines the intellectual property idea using a generative AI model. The improved idea is presented to the user again, and this process is repeated until the user is satisfied.

[0101] Competitive Research

[0102] After the intellectual property idea is confirmed, the server will refer to the patent database to search for existing intellectual property that may conflict with the intellectual property idea, and report the results of the conflict search to the user and propose necessary adjustments.

[0103] Generate intellectual property application documents

[0104] The server generates intellectual property application documents based on the finalized idea. In this process, the server uses a natural language generation (NLG) engine to create documents in accordance with the patent application format.

[0105] Application Procedure

[0106] The user checks the generated patent application document on a terminal and instructs the server on any necessary corrections. The server reflects the correction instructions and completes the final intellectual property application document. The server then processes the completed document for submission to the Patent Office's online system.

[0107] Specific examples

[0108] For example, if a user wants to apply for a patent for a new AI algorithm, they first upload their policy documents and related emails to the server. The server analyzes these and extracts keywords such as "new AI algorithm," "time efficiency," and "improved accuracy." Based on these keywords, the server generates a hypothesis for the patent idea: "A new AI algorithm that achieves efficiency through automation." Based on the user's feedback, the server refines and optimizes the idea.

[0109] Specific examples of input prompts for generative AI models

[0110] "I would like to apply for a patent for a new AI algorithm. I would like you to generate patent ideas based on policy documents."

[0111] "Please tell me the steps to refine my patent idea for improving efficiency and accuracy."

[0112] In this way, the present invention is a system that enables the entire process from the discovery of a patent idea to the application procedure to be carried out efficiently and effectively.

[0113] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0114] Step 1:

[0115] Entering and Submitting Data

[0116] The user prepares policy documents and emails between stakeholders related to the invention. Specifically, the user saves data, including research papers and communication records with project members, on the device. Next, the user selects these documents through a dedicated app or web portal and presses the "Upload" button. The device encodes the selected data and sends it to the specified endpoint on the server via an HTTP POST request.

[0117] Input: Policy documents and emails related to inventions

[0118] Output: Data sent to the server

[0119] Step 2:

[0120] Data reception and analysis

[0121] The server receives the data sent from the device. It then analyzes the received data using a natural language processing (NLP) engine. Specifically, the server tokenizes the data and performs morphological analysis. This extracts important keywords and concepts, such as "AI algorithm," "time efficiency," and "accuracy improvement."

[0122] Input: Data sent to the server

[0123] Output: Extracted keywords and concepts

[0124] Step 3:

[0125] Idea generation

[0126] The server generates intellectual property ideas based on the extracted keywords and concepts. In this process, a generative AI model is used to create hypotheses for patent ideas. For example, a "patent idea for a technology that uses a new AI algorithm to improve time efficiency and accuracy" is generated. The generated idea is then sent to the user's device.

[0127] Input: Extracted keywords and concepts

[0128] Output: Generated intellectual property ideas

[0129] Step 4:

[0130] Brushing up ideas

[0131] Users provide feedback on the proposed tentative patent idea. For example, they can enter comments to add "methods for further improvement" or "application to a specific industry." The server receives the user's feedback and refines the idea using a generative AI model. The improved idea is then presented to the user again.

[0132] Input: User feedback

[0133] Output: Improved intellectual property ideas

[0134] Step 5:

[0135] Competitive research

[0136] The server searches patent databases based on the confirmed intellectual property idea, and references existing patent databases to search for existing intellectual property that may conflict with the intellectual property idea. The search results are reported to the user, and necessary adjustments are suggested. Specifically, the server issues queries such as keyword searches and concept matching to patent databases.

[0137] Input: Confirmed intellectual property idea

[0138] Output: List of competing patents

[0139] Step 6:

[0140] Generate application documents

[0141] The server then generates an intellectual property application document based on the finalized idea. During this process, the server uses a natural language generation (NLG) engine to create a document in a patent application format. Specifically, the document is generated in a format such as, "This invention relates to a method for improving the efficiency of specific operations using a new AI algorithm."

[0142] Input: Confirmed intellectual property idea

[0143] Output: Intellectual property application document

[0144] Step 7:

[0145] Application Procedure

[0146] The user checks the generated patent application document using a terminal and instructs the server on any necessary corrections. The server reflects the correction instructions and completes the final intellectual property application document. The server then submits the completed document to the Patent Office's online system. During this process, the user previews the patent application document and directly inputs corrections using a markup tool. The server also receives the user's correction instructions and regenerates the updated document.

[0147] Input: Finalized intellectual property application documents

[0148] Output: Submitted intellectual property application documents

[0149] In this way, the system can efficiently carry out the entire process from patent idea generation to application procedures.

[0150] (Application example 1)

[0151] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0152] The patent application process is extremely complex and time-consuming, resulting in inefficiencies in steps such as extracting important keywords and concepts, generating patent ideas, conducting competitive research, and preparing patent application documents. Furthermore, generating product descriptions quickly and effectively on online shopping sites requires detailed manual writing, placing a significant burden on operators. A system that solves these problems is needed.

[0153] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0154] In this invention, the server includes means for receiving materials related to the invention, means for analyzing the received materials and extracting important keywords and concepts, means for generating patent ideas from the extracted information, means for receiving user feedback and improving the patent ideas, means for searching for competing patents based on the patent ideas, means for providing information on competing patents to the user, means for generating patent application documents, means for submitting the generated patent application documents to the Patent Office, means for receiving product information and generating product descriptions, and means for the user to confirm and modify the generated product descriptions. This improves the efficiency of the patent application process and enables the rapid generation of product descriptions on online shopping sites.

[0155] "Materials related to the invention" refers to data including technical documents required for patent applications, emails between parties, and other related information.

[0156] "Analysis" refers to the process of using natural language processing (NLP) technology to understand the content of received materials and extract important keywords and concepts.

[0157] "Keywords and concepts" are words and ideas that are considered important in generating patent ideas and preparing patent application documents.

[0158] A "patent idea" is a technical idea that is the subject of a patent application and is generated based on the extracted keywords and concepts.

[0159] "Feedback" refers to opinions and suggestions for improvement that users provide to the system.

[0160] A "competing patent" refers to an existing patent registered in a patent database that is similar to the generated patent idea.

[0161] "Patent application document" means a document prepared in the form required to apply for a patent.

[0162] "Patent Office" refers to the public institution that accepts and reviews patent applications.

[0163] "Product information" refers to information such as the name, features, price, and brand of the product sold on the online shopping site.

[0164] A "product description" is a description of a product that is posted on an online shopping site and is text that conveys the appeal of the product to users.

[0165] This invention relates to a system and its implementation method for improving the efficiency of the patent application process and automatically generating product descriptions for online shopping sites. This system is mainly composed of three components: a server, a terminal, and a user.

[0166] Server Roles

[0167] The server has the following features:

[0168] 1. Document receiving means: This has the function of receiving invention-related documents uploaded by users, including technical documents and emails between related parties.

[0169] 2. Analysis method: The received material is analyzed using a natural language processing (NLP) engine to extract important keywords and concepts. This process is carried out through morphological analysis.

[0170] 3. Patent idea generation means: Patent ideas are generated based on the extracted keywords and concepts. The generated ideas are presented to the user.

[0171] 4. Improve method: Receive user feedback and improve the patent idea using an AI model (e.g., GPT-2). This process is repeated until the user is satisfied.

[0172] 5. Competing patent search tool: Consult patent databases to search for existing patents that may compete with the patent idea.

[0173] 6. Information provision means: Provide users with information on competing patents and suggest necessary adjustments.

[0174] 7. Patent application document generation method: A patent application document is generated based on the confirmed idea. An NLG (Natural Language Generation) engine is used in this process.

[0175] 8. Patent Office Submission Method: Submit the final patent application documents to the Patent Office's online system.

[0176] Furthermore, the server also comprises the following means, which are of particular importance in the application of the invention:

[0177] 1. Product information receiving means: Receives product information (e.g., product name, features, price, brand, etc.) from the online shopping site.

[0178] 2. Product description generation method: Generate product descriptions based on the received product information. Generate text using an AI model (e.g., GPT-2).

[0179] 3. User confirmation and correction: Provides a function for users to confirm the generated product description and correct it if necessary.

[0180] Device Role

[0181] The terminal provides an interface with the user. The user uses the terminal to upload invention-related materials and product information to the server. The terminal also presents ideas sent from the server and generated product descriptions to the user and receives feedback.

[0182] User Roles

[0183] The user's role is to provide documents and product information to the server through the terminal, and also to provide feedback on patent ideas and product descriptions provided by the server, and to give instructions for necessary improvements.

[0184] Specific examples

[0185] For example, if a user wants to apply for a patent for a new AI algorithm, they upload technical documents and related emails to the server. The server analyzes these and extracts keywords such as "new AI algorithm," "time efficiency," and "improved accuracy." The patent idea generated will then be "a new AI algorithm that achieves efficiency through automation." The user provides feedback on this idea, and the server makes improvements.

[0186] Also, when an online shopping site operator creates a description for a new product (e.g., a "smart watch"), they provide the product information (product name, features, price, brand) to the server. The server generates a prompt like this:

[0187] New Product: Smartwatch

[0188] Brand: General company name

[0189] Main features: Heart rate monitor, GPS function, waterproof

[0190] Price: 19,800 yen

[0191] Description:

[0192] Based on this prompt, the server generates a product description, which is used as the final description after the user confirms and makes any necessary corrections.

[0193] In this way, this system can streamline the patent application process and the process of generating product descriptions for online shopping sites, significantly reducing the burden on users.

[0194] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0195] Step 1:

[0196] The server receives invention-related materials (such as technical documents and emails between parties) uploaded by users from their terminals, regardless of the file format of the materials.

[0197] Input: Invention-related files

[0198] Output: Received material

[0199] Step 2:

[0200] The server analyzes the received material using a natural language processing (NLP) engine to extract important keywords and concepts. During this process, the text is tokenized through morphological analysis and keywords are extracted.

[0201] Input: Received material

[0202] Output: Extracted keywords and concepts

[0203] Step 3:

[0204] The server generates patent ideas based on the extracted keywords and concepts, and the generated ideas are generated in text format using an AI model (e.g., GPT-2).

[0205] Input: Extracted keywords and concepts

[0206] Output: Generated patent ideas

[0207] Step 4:

[0208] The server sends the generated patent ideas to the terminal and presents them to the user, who then provides feedback on the ideas.

[0209] Input: Generated patent idea

[0210] Output: User feedback

[0211] Step 5:

[0212] The server receives user feedback and uses the AI ​​model to refine the patent idea, a process that is repeated until the user is satisfied.

[0213] Input: User feedback

[0214] Output: Improved patent idea

[0215] Step 6:

[0216] The server searches a patent database to find existing patents that may conflict with the patent idea.

[0217] Input: Improved patent idea

[0218] Output: Competitive patent information

[0219] Step 7:

[0220] The server provides users with information on competing patents and suggests necessary adjustments.

[0221] Input: Competing patent information

[0222] Output: Information and suggestions provided to the user

[0223] Step 8:

[0224] The server generates patent application documents using an NLG engine based on the finalized idea.

[0225] Input: A confirmed idea

[0226] Output: Generated patent application document

[0227] Step 9:

[0228] The user uses the terminal to check the generated patent application document and sends instructions to the server to make any necessary corrections.

[0229] Input: Generated patent application document

[0230] Output: User's correction instructions

[0231] Step 10:

[0232] The server reflects the correction instructions and completes the final patent application document, which is then submitted to the Patent Office's online system.

[0233] Input: User correction instructions

[0234] Output: Final patent application document submitted to the patent office

[0235] Step 11:

[0236] Product information (such as product name, features, price, brand, etc.) is received, and a prompt sentence is created based on this to generate a product description.

[0237] Input: Product information

[0238] Output: prompt statement

[0239] Step 12:

[0240] The server uses a generative AI model (e.g., GPT-2) to generate a product description based on the prompt.

[0241] Input: prompt statement

[0242] Output: Generated product description

[0243] Step 13:

[0244] The server provides the generated product description to the user, who then reviews and makes any necessary corrections.

[0245] Input: Generated product description

[0246] Output: Product description reviewed and corrected by the user

[0247] Step 14:

[0248] The server reflects the user's confirmation and corrections and generates a final product description.

[0249] Input: User correction instructions

[0250] Output: Final product description

[0251] In this way, the system streamlines the patent application process and the product description generation process for online shopping sites.

[0252] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0253] Understood. Below, based on the scope of the claims, we have prepared a "Description of the Invention" for the invention that combines an emotion engine.

[0254] ---

[0255] This invention combines an emotion engine with a system and implementation method for streamlining intellectual property applications. This system recognizes the user's emotions during the patent idea generation and refinement process and makes adjustments based on the feedback, thereby achieving efficient and effective patent applications.

[0256] Data entry and analysis

[0257] Users use their devices to prepare and organize invention-related policy documents and emails with related parties. The devices are equipped with a means to upload these documents to the server. The server receives the uploaded data and uses a natural language processing (NLP) engine to tokenize it, perform morphological analysis, and extract important keywords and concepts.

[0258] Idea generation and refinement

[0259] The server generates hypotheses for patent ideas based on the extracted keywords and concepts. The hypotheses are presented to the user's terminal, and the user provides feedback on the presented patent ideas.

[0260] The server receives user feedback and uses the AI ​​model to refine the patent idea, which is then presented to the user again, and the process is repeated until the user is satisfied.

[0261] Utilizing the Emotion Engine

[0262] When collecting feedback, the server uses an emotion engine to recognize the user's emotions, for example, by capturing emotional data through the style and tone of the user's feedback, as well as facial and voice analysis (if required).

[0263] The emotion engine analyzes the user's emotional state, such as whether their feedback is positive or negative, flexible or strict, and adjusts how the idea is refined and presented based on the results. For example, if the user responds statistically positively, the idea will be explored further, and if the user responds negatively, a different approach will be tried.

[0264] Competitive research and document generation

[0265] Based on the patent idea identified, the server searches the patent database for existing patents that may conflict with it, reporting the results to the user and suggesting adjustments if necessary.

[0266] The server then generates a patent application document based on the finalized idea, using a natural language generation (NLG) engine to adjust the document's format and writing style, even adjusting it based on the user's emotional state.

[0267] Application Procedure

[0268] The user uses the terminal to check the generated patent application document and indicate any necessary corrections. The server reflects these correction instructions and completes the final patent application document. The server then processes this completed document for submission to the Patent Office's online system. The user monitors the application status on the terminal and provides additional information and materials as needed.

[0269] Specific examples

[0270] For example, if a user wants to apply for a patent for a new AI algorithm, they first upload their policy documents and related emails to the server. The server analyzes this information and extracts keywords such as "new AI algorithm," "time efficiency," and "improved accuracy." Based on these keywords, it generates a hypothesis: "a new AI algorithm that achieves efficiency through automation."

[0271] When users provide feedback on a proposed idea, their emotional state (e.g., positive anticipation or negative concern) is also analyzed by the emotion engine. The server uses this data to refine the idea and present it to the user again. The system also adjusts the tone and format of patent application documents, taking the user's emotional state into account.

[0272] In this way, by utilizing the emotion engine, the entire process from patent idea discovery to application processing can be made more personalized, efficient, and effective.

[0273] The processing flow will be explained below.

[0274] Step 1:

[0275] The user prepares invention-related policy documents and emails between related parties on the terminal, which then uploads the data to the server.

[0276] Step 2:

[0277] The server receives the uploaded data and then invokes a natural language processing (NLP) engine to tokenize the data and perform morphological analysis to extract important keywords and concepts.

[0278] Step 3:

[0279] The server generates hypotheses for patent ideas based on the extracted keywords and concepts, a process that provides initial idea suggestions based on similar ideas and an existing knowledge base.

[0280] Step 4:

[0281] The server presents the generated hypotheses for the patent idea to the user's terminal, which the user confirms.

[0282] Step 5:

[0283] Users can input feedback on the presented patent idea via a terminal, for example, suggesting "ways to apply this idea to a specific industry" or "ways to further improve accuracy."

[0284] Step 6:

[0285] The device sends user feedback data to a server, which analyzes the received feedback and uses AI models to refine the idea.

[0286] Step 7:

[0287] The server uses an emotion engine when collecting feedback to recognize the user's emotions, for example by analyzing the style and tone of the feedback, or facial expressions and voice (if applicable).

[0288] Step 8:

[0289] The server adjusts how the patent idea is refined and presented based on the emotional data obtained by the emotion engine. For example, if the user expresses negative emotions, it can suggest different approaches and solutions.

[0290] Step 9:

[0291] The server then presents the refined patent idea to the user again, and this process is repeated until the user is satisfied.

[0292] Step 10:

[0293] The server accesses a patent database to search for existing patents that may be competing with the patent idea, and reports the search results to the user.

[0294] Step 11:

[0295] The server automatically generates patent application documents based on the confirmed patent idea, using a natural language generation (NLG) engine to refine the document's format and writing style.

[0296] Step 12:

[0297] The server sends the generated patent application document to the user's terminal, where the user can review it and make any necessary corrections.

[0298] Step 13:

[0299] The terminal sends the user's correction instructions to the server, which then reflects the correction instructions and completes the final patent application document.

[0300] Step 14:

[0301] The server submits the completed patent application documents to the Patent Office's online system, where users can monitor the application status on their devices and provide additional information or materials as needed.

[0302] This allows systems that utilize emotion engines to make the entire process, from discovering patent ideas to filing applications, more efficient and effective.

[0303] Example 2

[0304] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0305] The traditional patent application process requires many steps, including organizing invention-related materials, generating patent ideas, collecting feedback and refining the ideas, researching competing patents, and preparing patent application documents, and is extremely time-consuming and labor-intensive. Furthermore, because the user's emotional state is not taken into consideration, the quality of feedback is often poor and ideas are often not effectively refined. This leads to a lower success rate for patent applications.

[0306] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0307] In this invention, the server includes means for receiving materials related to the invention, means for analyzing the received materials and extracting important keywords and concepts, means for generating patent ideas from the extracted information, means for receiving user feedback and improving the patent ideas, means for analyzing the user's emotional state and adjusting the method for improving and presenting the ideas based on the feedback, means for searching for competing patents based on the patent ideas, means for providing the user with information on competing patents, means for generating patent application documents, and means for submitting the generated patent application documents to the Patent Office, thereby significantly improving the efficiency of the patent application process and enabling personalized support based on the user's emotional state.

[0308] "Materials related to the invention" refers to documents and data that describe the content, background, and technical features of the invention.

[0309] A "server" is a computer system that receives, analyzes, processes, stores, and transmits data.

[0310] "Natural language processing" refers to the technology that allows computers to analyze, generate, and understand human language.

[0311] "Keywords and concepts" are important words and concepts extracted from the materials that are necessary for generating patent ideas.

[0312] A "patent idea" is a specific concept or proposal for a particular technology or invention.

[0313] "Feedback" refers to the evaluations and opinions that users give about patent ideas.

[0314] An "emotion recognition engine" is a technology for analyzing emotions from user feedback.

[0315] A "competing patent" is an existing patent that is similar to or related to the patent idea being applied for.

[0316] "Patent application documents" means official documents prepared for a patent application.

[0317] "Patent Office" refers to the government agency that accepts, examines, and registers patent applications.

[0318] An "AI model" is a machine learning model that uses artificial intelligence to generate and improve patent ideas.

[0319] A "prompt sentence" is an input sentence given to a generative AI model, based on which the AI ​​generates output.

[0320] This invention is a system aimed at streamlining the patent application process, providing comprehensive support for everything from organizing and analyzing invention-related materials to generating patent ideas, collecting and refining feedback, conducting competitive research, and preparing and submitting patent application documents. The system's hardware configuration includes a user device and a server for processing data. The software configuration includes a natural language processing engine (e.g., SpaCy), a generative AI model (e.g., GPT-3), an emotion recognition engine, a patent database search engine, and a natural language generation engine (NLG engine).

[0321] Data entry and analysis

[0322] Users use their devices to prepare invention-related policy documents and emails with stakeholders, and upload these documents to the server. The device provides a file upload function, allowing users to select PDFs, Word documents, etc. from their local directory and send them to the server. The server stores the received data and uses a natural language processing (NLP) engine to tokenize the data, perform morphological analysis, and extract important keywords and concepts.

[0323] Idea generation and feedback

[0324] The server uses a generative AI model to generate hypotheses for patent ideas based on the extracted keywords and concepts. For example, by entering a prompt to generate a patent idea for a "new AI algorithm," detailed ideas are generated. The generated ideas are displayed on the user's device. The user can provide feedback on the presented patent idea. The feedback is entered in a simple comment field and sent to the server.

[0325] Utilizing the Emotion Engine

[0326] The server analyzes the feedback provided by the user using an emotion recognition engine. It obtains the user's emotional data from the content and tone of the feedback, and, if necessary, through voice and facial expression analysis. The emotion recognition engine determines whether the feedback is positive or negative, and adjusts how the patent idea is improved and presented based on the results.

[0327] Competitive research and document generation

[0328] The server searches patent databases based on the patent idea to find competing patents. The search results are provided to the user, suggesting modifications or adjustments to the idea as needed. The server then uses a natural language generation (NLG) engine to generate the patent application document, which can automatically adjust the format and writing style of the patent document. It also adjusts based on the user's emotional state.

[0329] Application Procedure

[0330] The generated patent application document is reviewed on the user's device, and the user can input correction instructions as needed. The server reflects these instructions and completes the final patent application document. The server then processes the completed document for submission to the Patent Office's online system. The user can monitor the application status on their device and provide additional information and materials.

[0331] In this way, the system aims to consistently support and streamline the patent application process. As a specific example, when applying for a patent for a new AI algorithm, the following prompt is entered: "Generate a patent idea for a new AI algorithm that achieves efficiency through automation." Based on this prompt, the generative AI model will generate detailed ideas.

[0332] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0333] Step 1:

[0334] The user uses a device to prepare policy documents and emails related to the invention and uploads them to the server. The input is a PDF, Word document, etc., and is sent using the device's upload function. The documents are saved on the server as output.

[0335] Step 2:

[0336] The server saves the received data. The input is the file uploaded in the previous step, and the destination is the server's file system. The output is the data saved on the server.

[0337] Step 3:

[0338] The server runs a natural language processing (NLP) engine to tokenize and morphologically analyze the stored material. It uses the text data of the received material as input. Specifically, it uses an NLP engine (e.g., SpaCy) to extract nouns and verbs. The output is a list of important keywords and concepts.

[0339] Step 4:

[0340] The server uses a generative AI model to generate patent idea hypotheses based on the extracted keywords and concepts. It uses a list of keywords or concepts and a prompt (e.g., "Please generate a patent idea for a new AI algorithm") as input. The generated patent idea hypotheses are obtained as output.

[0341] Step 5:

[0342] The server sends the generated patent idea assumptions to the user's terminal and displays them. The generated patent idea assumptions are used as input and are displayed on the user's terminal as output.

[0343] Step 6:

[0344] Users submit feedback on the presented patent ideas from their devices. The system uses the user's evaluations and opinions as input, and sends the feedback entered in the comment field from the device. The feedback is sent to the server as output.

[0345] Step 7:

[0346] The server receives the feedback provided by the user and analyzes it with an emotion recognition engine. Using the feedback content as input, the emotion recognition engine determines the emotional state, whether positive or negative. The output is the emotion analysis result.

[0347] Step 8:

[0348] The server adjusts how to improve and present the patent idea based on the sentiment analysis results. It uses the sentiment analysis results and the original patent idea hypotheses as input. It uses the generative AI model again to generate the improved patent idea. The improved patent idea is obtained as output.

[0349] Step 9:

[0350] The server presents the improved patent idea to the user again and repeats the same feedback process, using the improved patent idea as input and presented to the user's terminal as output.

[0351] Step 10:

[0352] The server searches a patent database for competing patents based on the confirmed patent idea. It uses keywords and concepts from the confirmed patent idea as input and sends a search query to the patent database. The output is a list of competing patents.

[0353] Step 11:

[0354] The server provides the user with information on competing patents. It uses a list of competing patents obtained from a patent database as input and reports it to the user. It displays the competing patent information on a terminal as output.

[0355] Step 12:

[0356] The server uses a natural language generation (NLG) engine to generate a patent application document based on the finalized patent idea. Using the content of the finalized patent idea as input, the NLG engine generates the format and writing style of the document. The patent application document is created as output.

[0357] Step 13:

[0358] The user uses a terminal to check the generated patent application document and instructs on necessary corrections. The patent application document is used as input, and correction instructions are entered in the comment field. The correction instructions are sent to the server as output.

[0359] Step 14:

[0360] The server reflects the correction instructions and completes the final patent application document. The server uses the user's correction instructions as input and updates the patent application document. The final patent application document is completed as output.

[0361] Step 15:

[0362] The server submits the completed patent application to the Patent Office's online system. It uses the final patent application as input and sends the data to the online system. The output is a confirmation of receipt from the Patent Office.

[0363] Step 16:

[0364] The user monitors the application status on the terminal and provides additional information and materials as needed. The user uses notifications from the Patent Office's online system as input and submits the additional information and materials from the terminal. The additional information and materials are sent to the Patent Office as output.

[0365] (Application example 2)

[0366] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0367] The patent application process is complex and requires a lot of time and effort. Furthermore, efficiently incorporating user feedback and generating optimal patent ideas is a difficult problem. Furthermore, existing systems have not been able to utilize feedback that takes into account the user's emotional state. This results in a lack of improvement in the efficiency and quality of patent applications, and makes searching for competing patent information and preparing application documents cumbersome. Therefore, a system that solves these issues, streamlines the patent application process, and improves user satisfaction is needed.

[0368] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving materials related to the invention, means for analyzing the received materials and extracting important keywords and concepts, means for generating a patent idea from the extracted information, means for receiving user feedback and improving the patent idea, means for analyzing the user's emotional state at the time of feedback, means for adjusting the patent idea according to the analyzed emotional state, means for searching for competing patents based on the patent idea, means for providing the user with information on competing patents, means for generating patent application documents, and means for submitting the generated patent application documents to the Patent Office. This enables the patent application process to be carried out efficiently and effectively, and improves user satisfaction.

[0369] "Materials related to the invention" refers to information and documents necessary for filing a patent application, including relevant technical documents, research data, email content, etc.

[0370] "Means for receiving" refers to the function or method by which the server receives materials related to the invention from the user and stores them in storage.

[0371] "Means for analysis" refers to the functions and methods for processing received materials and extracting important keywords and concepts using natural language processing technology.

[0372] "Extracted information" refers to keywords and concepts obtained from the analyzed materials, and is the basis for generating patent ideas.

[0373] A "means for generating patent ideas" is a function or method for automatically generating new patent hypotheses or proposals based on the extracted information.

[0374] "User Feedback" means any opinion, comment, or evaluation provided by a user regarding a patent idea.

[0375] "Means for improving the patent idea" refers to the functions and methods for further improving and optimizing the patent idea based on the feedback received.

[0376] "Means for analyzing emotional state" refers to techniques or methods for analyzing the user's text, voice, or facial expressions during feedback to understand and classify their emotions.

[0377] "Means for adjusting patent ideas" refer to functions and methods for changing and optimizing the content and presentation of patent ideas according to the user's emotional state.

[0378] The "means for searching competing patents" refers to a function or method for searching a patent database for existing patents related to the generated patent idea.

[0379] "Competitive Patent Information" is detailed data about existing patents that have been searched and is a reference provided to the user.

[0380] The "means for generating patent application documents" refers to a function or method for automatically creating documents required for a patent application based on a confirmed patent idea.

[0381] "Means for submission" refers to the functionality or method for submitting the generated patent application documents to the Patent Office online or offline.

[0382] MODE FOR CARRYING OUT THE INVENTION

[0383] The embodiments of the present invention will be described in detail below.

[0384] System Overview

[0385] The system of the present invention is equipped with a series of means for streamlining the patent application process. The system is mainly composed of three elements: a server, a terminal, and a user. The server receives and analyzes invention-related materials and uses that information to generate and refine patent ideas. The terminal functions as an interface for users to provide feedback and upload materials.

[0386] Hardware and software used

[0387] 1. Hardware:

[0388] Server: High-performance data processing server

[0389] Device: Smartphone, smart glasses, or computer

[0390] 2. Software:

[0391] Natural Language Processing Engine (TextBlob)

[0392] Sentiment analysis engine (Hugging Face transformers library)

[0393] Database systems (e.g. PostgreSQL)

[0394] Patent database search function

[0395] Natural Language Generation Engine (Natural Language Model)

[0396] Specific processing flow

[0397] First, the user uploads documents related to the invention using a terminal. The server stores the received documents in storage. A natural language processing engine is used to tokenize and analyze the documents to extract important keywords and concepts. Based on this extracted information, a patent idea is generated.

[0398] The generated patent ideas are presented to the user's device. The user provides feedback on the presented ideas. During the feedback process, the user's emotional state is analyzed using an emotion analysis engine. This allows the idea to be adjusted according to the user's emotional state.

[0399] Once a patent idea is finalized, the server searches the patent database for relevant competing patents, and provides the competing patent information to the user, allowing them to adjust the idea as needed.

[0400] Finally, the server generates a patent application document based on the confirmed patent idea, which can then be submitted to the patent office online or offline. Users can monitor the application status through their devices and provide additional information and materials as needed.

[0401] Examples of concrete examples and prompts

[0402] For example, if a user wants to apply for a patent for a new voice recognition technology, they first upload technical documents and related emails from their device to the server. The server analyzes this information and extracts keywords such as "voice recognition technology," "improved accuracy," and "real-time processing." Based on these keywords, a patent idea for "a new algorithm to improve the accuracy of voice recognition" is generated. The user then provides feedback on this idea, saying, "This idea is interesting, but further details need to be specified."

[0403] Example prompt for a generative AI model:

[0404] User feedback: "This is a great idea, but we should also consider how to improve the accuracy."

[0405] In this way, the system of the present invention can streamline the entire process from the generation of a patent idea to the filing of an application, and can quickly reflect user feedback.

[0406] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0407] Step 1:

[0408] The user uploads documents related to the invention using a terminal. The input includes files such as technical documents and related emails. This document is sent to the server, which then stores the received documents in storage. The output is the saved document file. Specifically, the user selects the documents using the file upload interface and presses the upload button, which sends the documents to the server.

[0409] Step 2:

[0410] The server analyzes the uploaded materials using a natural language processing engine. The material file saved in step 1 is used as input. The analysis process tokenizes the materials and extracts important keywords and concepts. The output is the extracted keywords and concepts. Specifically, the TextBlob library is used to tokenize the documents and perform morphological analysis.

[0411] Step 3:

[0412] The server generates patent ideas based on the extracted keywords and concepts. The input includes the keywords and concepts extracted in step 2. An AI model is used to generate patent ideas based on this information. The output is the generated patent idea. Specifically, the generative AI model is used to create patent ideas on themes such as "new algorithms" and "efficiency."

[0413] Step 4:

[0414] The server presents the generated patent idea to the user's terminal. The patent idea created in step 3 is used as input. The user provides feedback on the presented idea. The output is the user's feedback. Specifically, the server displays the patent idea on the user interface and provides a feedback input field.

[0415] Step 5:

[0416] The server receives the user's feedback and analyzes the feedback content using a sentiment analysis engine. The feedback received in step 4 is used as input. The sentiment analysis determines the user's emotional state (positive, negative, etc.). The output is the analyzed emotional data. Specifically, the server utilizes the Hugging Face transformers library to perform sentiment analysis on the feedback text.

[0417] Step 6:

[0418] The server adjusts the patent idea based on the analyzed emotional state. The input includes the emotional data obtained in step 5 and the patent idea generated in step 3. The idea is refined according to the emotional state and presented to the user again. The output is the adjusted patent idea. Specifically, the server evaluates the emotional data and updates the content and presentation method of the patent idea.

[0419] Step 7:

[0420] The server searches the patent database based on the confirmed patent idea to find related competing patents. The input includes the patent idea confirmed in step 6. The server outputs the competing patent information obtained as a search result. Specifically, it uses the patent database search function to extract related patents from the database.

[0421] Step 8:

[0422] The server provides the searched competing patent information to the user and generates a patent application document. The input includes the competing patent information obtained in step 7 and the patent idea confirmed in step 6. The output is the generated patent application document. Specifically, the server uses a natural language generation engine to automatically create the patent application document.

[0423] Step 9:

[0424] The server submits the generated patent application document to the Patent Office. The patent application document created in step 8 is used as input. The document is submitted to the Patent Office online or offline, and then confirmed. The output is the acceptance status of the patent application. Specifically, the document is uploaded through the Patent Office's online system, and the application number, etc. are confirmed.

[0425] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0426] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0427] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0428] [Second embodiment]

[0429] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0430] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0431] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0432] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0433] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0434] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0435] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0436] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0437] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0438] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0439] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0440] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0441] Understood. I have prepared the following "Mode for carrying out the invention" based on the scope of the claims.

[0442] ---

[0443] This invention relates to a system and method for efficiently filing intellectual property applications. This system generates patent ideas and files patent applications through multiple steps, with a server, a terminal, and a user playing their respective roles.

[0444] Data entry and analysis

[0445] The user uses the terminal to prepare and organize policy documents and emails between related parties related to the invention. The terminal is equipped with a means to upload these documents to the server. The server receives the uploaded data and analyzes it using a natural language processing (NLP) engine.

[0446] During the analysis process, the server tokenizes the received data and performs morphological analysis to extract important keywords and concepts, such as "AI algorithm," "time efficiency," and "improved accuracy."

[0447] Idea generation and refinement

[0448] The server generates hypotheses for patent ideas based on the extracted keywords and concepts. The hypotheses are then presented to the user's device. The user can then provide feedback on the proposed tentative patent ideas, such as adding "methods for further refinement" or "applications to specific industries."

[0449] The server receives user feedback and refines the patent idea using an AI model. The improved idea is then presented to the user again, and this process is repeated until the user is satisfied.

[0450] Competitive research and document generation

[0451] After the idea is confirmed, the server searches the patent database for existing patents that may conflict with the patent idea. The results of the conflict search are reported to the user and necessary adjustments are proposed.

[0452] The server generates a patent application document based on the finalized idea. In this process, the server uses a natural language generation (NLG) engine to create a document in accordance with the patent application format.

[0453] Application Procedure

[0454] The user uses a terminal to check the generated patent application document and instruct the server on any necessary corrections. The server reflects the correction instructions and completes the final patent application document. The server then processes the completed document for submission to the Patent Office's online system.

[0455] Specific examples

[0456] For example, if a user wants to apply for a patent for a new AI algorithm, they first upload their policy documents and related emails to the server. The server analyzes these and extracts keywords such as "new AI algorithm," "time efficiency," and "improved accuracy." Based on these keywords, the server generates a hypothesis for the patent idea: "A new AI algorithm that achieves efficiency through automation." Based on the user's feedback, the server refines and optimizes the idea.

[0457] The server then searches the patent database for competing patents and reports the results to the user. Based on the finalized idea, the server generates a patent application document, which is then submitted to the patent office after the user has confirmed and revised it.

[0458] In this way, the present invention is a system that enables the entire process from the discovery of a patent idea to the application procedure to be carried out efficiently and effectively.

[0459] The processing flow will be explained below.

[0460] Step 1:

[0461] The user prepares invention-related policy documents and emails between related parties on the terminal, which then uploads the data to the server.

[0462] Step 2:

[0463] The server receives the uploaded data and then invokes a natural language processing (NLP) engine to tokenize the data and perform morphological analysis to extract important keywords and concepts.

[0464] Step 3:

[0465] The server generates hypotheses for patent ideas based on the extracted keywords and concepts, a process that provides initial idea suggestions based on similar ideas and an existing knowledge base.

[0466] Step 4:

[0467] The server presents the generated hypotheses for the patent idea to the user's terminal, which the user confirms.

[0468] Step 5:

[0469] Users can input feedback on the presented patent idea via a terminal, for example, suggesting "ways to apply this idea to a specific industry" or "ways to further improve accuracy."

[0470] Step 6:

[0471] The device sends user feedback data to a server, which analyzes the received feedback and uses AI models to refine the idea.

[0472] Step 7:

[0473] The server then presents the refined patent idea to the user again, and this process is repeated until the user is satisfied with the result.

[0474] Step 8:

[0475] The server accesses a patent database to search for existing patents that may be competing with the patent idea, and reports the search results to the user.

[0476] Step 9:

[0477] The server automatically generates patent application documents based on the confirmed patent idea, using a natural language generation (NLG) engine to refine the document's format and writing style.

[0478] Step 10:

[0479] The user checks the patent application document generated on the terminal and instructs the terminal to make any necessary corrections, which are then sent to the server.

[0480] Step 11:

[0481] The server reflects the user's correction instructions and finally completes the patent application document.

[0482] Step 12:

[0483] The server submits the completed patent application to the Patent Office's online system, where users can monitor the application status and provide additional information or materials as needed.

[0484] This streamlines the entire process from discovering a patent idea to filing an application.

[0485] Example 1

[0486] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0487] The current intellectual property application process requires a lot of time and effort, is inefficient in terms of patent idea generation, competitive research, and application document preparation, and places a heavy burden on users. This problem makes it difficult for inventors to protect their new ideas in a timely manner, which can result in a loss of competitiveness. Furthermore, existing systems rely on manual processes for analyzing information and refining ideas, which risks reducing the accuracy and speed of the work. To solve these issues, there is a need for a system that can automate the entire intellectual property application process efficiently and effectively.

[0488] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0489] In this invention, the server includes means for receiving digital documents, means for analyzing the received documents and extracting important information, means for generating intellectual property ideas from the extracted information, means for receiving user opinions and improving the intellectual property ideas, means for searching existing intellectual property based on the intellectual property ideas, means for presenting search results to the user, means for generating intellectual property application documents, and means for submitting the generated intellectual property application documents, thereby automating the entire intellectual property application process and enabling rapid and accurate patent idea generation, competitive research, and application document preparation and submission.

[0490] A "digital document" is a document containing information stored in electronic form that can be viewed, edited, or transmitted using a computer or other electronic device.

[0491] "Important information" refers to keywords and concepts contained within digital documents that are key to patent idea generation and competitive research.

[0492] "Intellectual property idea" refers to a concept or proposal for an invention or technical solution that is the subject of a patent application.

[0493] "User Feedback" means feedback, comments, or suggestions for correction provided by a User regarding an Intellectual Property Idea.

[0494] "Existing intellectual property" refers to technologies and inventions that have already been patented and are publicly available and registered in patent databases, etc.

[0495] "Search results" refers to the list of relevant information and patents that are obtained when searching existing intellectual property.

[0496] "Intellectual Property Application Document" refers to the official patent application document submitted to the Patent Office, which contains details of the invention and its technical features.

[0497] This invention relates to a system and method for efficiently filing intellectual property applications. In this system, a server, a terminal, and a user each play their respective roles, and the system generates patent ideas and files patent applications through multiple steps.

[0498] Entering and Submitting Data

[0499] The user prepares and organizes policy documents and emails between related parties related to the invention. The user uploads these documents to the terminal. The terminal has a means to send these documents to the server.

[0500] Data analysis

[0501] The server receives the uploaded digital document. It then analyzes the received digital document using a natural language processing (NLP) engine to extract important information. During the analysis process, the server tokenizes the received data and performs morphological analysis to extract important keywords and concepts. For example, keywords such as "new AI algorithm," "time efficiency," and "improved accuracy" are extracted.

[0502] Idea generation

[0503] The server generates hypotheses for intellectual property ideas based on the extracted keywords and concepts. The hypotheses are then presented to the user's device. For example, a "patent idea for a technology that uses a new AI algorithm to improve time efficiency and accuracy" might be generated.

[0504] Brushing up ideas

[0505] Users provide feedback on the proposed tentative patent idea, such as adding "further refinement methods" or "applications to specific industries." The server receives the user's feedback and refines the intellectual property idea using a generative AI model. The improved idea is presented to the user again, and this process is repeated until the user is satisfied.

[0506] Competitive Research

[0507] After the intellectual property idea is confirmed, the server will refer to the patent database to search for existing intellectual property that may conflict with the intellectual property idea, and report the results of the conflict search to the user and propose necessary adjustments.

[0508] Generate intellectual property application documents

[0509] The server generates intellectual property application documents based on the finalized idea. In this process, the server uses a natural language generation (NLG) engine to create documents in accordance with the patent application format.

[0510] Application Procedure

[0511] The user checks the generated patent application document on a terminal and instructs the server on any necessary corrections. The server reflects the correction instructions and completes the final intellectual property application document. The server then processes the completed document for submission to the Patent Office's online system.

[0512] Specific examples

[0513] For example, if a user wants to apply for a patent for a new AI algorithm, they first upload their policy documents and related emails to the server. The server analyzes these and extracts keywords such as "new AI algorithm," "time efficiency," and "improved accuracy." Based on these keywords, the server generates a hypothesis for the patent idea: "A new AI algorithm that achieves efficiency through automation." Based on the user's feedback, the server refines and optimizes the idea.

[0514] Specific examples of input prompts for generative AI models

[0515] "I would like to apply for a patent for a new AI algorithm. I would like you to generate patent ideas based on policy documents."

[0516] "Please tell me the steps to refine my patent idea for improving efficiency and accuracy."

[0517] In this way, the present invention is a system that enables the entire process from the discovery of a patent idea to the application procedure to be carried out efficiently and effectively.

[0518] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0519] Step 1:

[0520] Entering and Submitting Data

[0521] The user prepares policy documents and emails between stakeholders related to the invention. Specifically, the user saves data, including research papers and communication records with project members, on the device. Next, the user selects these documents through a dedicated app or web portal and presses the "Upload" button. The device encodes the selected data and sends it to the specified endpoint on the server via an HTTP POST request.

[0522] Input: Policy documents and emails related to inventions

[0523] Output: Data sent to the server

[0524] Step 2:

[0525] Data reception and analysis

[0526] The server receives the data sent from the device. It then analyzes the received data using a natural language processing (NLP) engine. Specifically, the server tokenizes the data and performs morphological analysis. This extracts important keywords and concepts, such as "AI algorithm," "time efficiency," and "accuracy improvement."

[0527] Input: Data sent to the server

[0528] Output: Extracted keywords and concepts

[0529] Step 3:

[0530] Idea generation

[0531] The server generates intellectual property ideas based on the extracted keywords and concepts. In this process, a generative AI model is used to create hypotheses for patent ideas. For example, a "patent idea for a technology that uses a new AI algorithm to improve time efficiency and accuracy" is generated. The generated idea is then sent to the user's device.

[0532] Input: Extracted keywords and concepts

[0533] Output: Generated intellectual property ideas

[0534] Step 4:

[0535] Brushing up ideas

[0536] Users provide feedback on the proposed tentative patent idea. For example, they can enter comments to add "methods for further improvement" or "application to a specific industry." The server receives the user's feedback and refines the idea using a generative AI model. The improved idea is then presented to the user again.

[0537] Input: User feedback

[0538] Output: Improved intellectual property ideas

[0539] Step 5:

[0540] Competitive research

[0541] The server searches patent databases based on the confirmed intellectual property idea, and references existing patent databases to search for existing intellectual property that may conflict with the intellectual property idea. The search results are reported to the user, and necessary adjustments are suggested. Specifically, the server issues queries such as keyword searches and concept matching to patent databases.

[0542] Input: Confirmed intellectual property idea

[0543] Output: List of competing patents

[0544] Step 6:

[0545] Generate application documents

[0546] The server then generates an intellectual property application document based on the finalized idea. During this process, the server uses a natural language generation (NLG) engine to create a document in a patent application format. Specifically, the document is generated in a format such as, "This invention relates to a method for improving the efficiency of specific operations using a new AI algorithm."

[0547] Input: Confirmed intellectual property idea

[0548] Output: Intellectual property application document

[0549] Step 7:

[0550] Application Procedure

[0551] The user checks the generated patent application document using a terminal and instructs the server on any necessary corrections. The server reflects the correction instructions and completes the final intellectual property application document. The server then submits the completed document to the Patent Office's online system. During this process, the user previews the patent application document and directly inputs corrections using a markup tool. The server also receives the user's correction instructions and regenerates the updated document.

[0552] Input: Finalized intellectual property application documents

[0553] Output: Submitted intellectual property application documents

[0554] In this way, the system can efficiently carry out the entire process from patent idea generation to application procedures.

[0555] (Application example 1)

[0556] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0557] The patent application process is extremely complex and time-consuming, resulting in inefficiencies in steps such as extracting important keywords and concepts, generating patent ideas, conducting competitive research, and preparing patent application documents. Furthermore, generating product descriptions quickly and effectively on online shopping sites requires detailed manual writing, placing a significant burden on operators. A system that solves these problems is needed.

[0558] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0559] In this invention, the server includes means for receiving materials related to the invention, means for analyzing the received materials and extracting important keywords and concepts, means for generating patent ideas from the extracted information, means for receiving user feedback and improving the patent ideas, means for searching for competing patents based on the patent ideas, means for providing information on competing patents to the user, means for generating patent application documents, means for submitting the generated patent application documents to the Patent Office, means for receiving product information and generating product descriptions, and means for the user to confirm and modify the generated product descriptions. This improves the efficiency of the patent application process and enables the rapid generation of product descriptions on online shopping sites.

[0560] "Materials related to the invention" refers to data including technical documents required for patent applications, emails between parties, and other related information.

[0561] "Analysis" refers to the process of using natural language processing (NLP) technology to understand the content of received materials and extract important keywords and concepts.

[0562] "Keywords and concepts" are words and ideas that are considered important in generating patent ideas and preparing patent application documents.

[0563] A "patent idea" is a technical idea that is the subject of a patent application and is generated based on the extracted keywords and concepts.

[0564] "Feedback" refers to opinions and suggestions for improvement that users provide to the system.

[0565] A "competing patent" refers to an existing patent registered in a patent database that is similar to the generated patent idea.

[0566] "Patent application document" means a document prepared in the form required to apply for a patent.

[0567] "Patent Office" refers to the public institution that accepts and reviews patent applications.

[0568] "Product information" refers to information such as the name, features, price, and brand of the product sold on the online shopping site.

[0569] A "product description" is a description of a product that is posted on an online shopping site and is text that conveys the appeal of the product to users.

[0570] This invention relates to a system and its implementation method for improving the efficiency of the patent application process and automatically generating product descriptions for online shopping sites. This system is mainly composed of three components: a server, a terminal, and a user.

[0571] Server Roles

[0572] The server has the following features:

[0573] 1. Document receiving means: This has the function of receiving invention-related documents uploaded by users, including technical documents and emails between related parties.

[0574] 2. Analysis method: The received material is analyzed using a natural language processing (NLP) engine to extract important keywords and concepts. This process is carried out through morphological analysis.

[0575] 3. Patent idea generation means: Patent ideas are generated based on the extracted keywords and concepts. The generated ideas are presented to the user.

[0576] 4. Improve method: Receive user feedback and improve the patent idea using an AI model (e.g., GPT-2). This process is repeated until the user is satisfied.

[0577] 5. Competing patent search tool: Consult patent databases to search for existing patents that may compete with the patent idea.

[0578] 6. Information provision means: Provide users with information on competing patents and suggest necessary adjustments.

[0579] 7. Patent application document generation method: A patent application document is generated based on the confirmed idea. An NLG (Natural Language Generation) engine is used in this process.

[0580] 8. Patent Office Submission Method: Submit the final patent application documents to the Patent Office's online system.

[0581] Furthermore, the server also comprises the following means, which are of particular importance in the application of the invention:

[0582] 1. Product information receiving means: Receives product information (e.g., product name, features, price, brand, etc.) from the online shopping site.

[0583] 2. Product description generation method: Generate product descriptions based on the received product information. Generate text using an AI model (e.g., GPT-2).

[0584] 3. User confirmation and correction: Provides a function for users to confirm the generated product description and correct it if necessary.

[0585] Device Role

[0586] The terminal provides an interface with the user. The user uses the terminal to upload invention-related materials and product information to the server. The terminal also presents ideas sent from the server and generated product descriptions to the user and receives feedback.

[0587] User Roles

[0588] The user's role is to provide documents and product information to the server through the terminal, and also to provide feedback on patent ideas and product descriptions provided by the server, and to give instructions for necessary improvements.

[0589] Specific examples

[0590] For example, if a user wants to apply for a patent for a new AI algorithm, they upload technical documents and related emails to the server. The server analyzes these and extracts keywords such as "new AI algorithm," "time efficiency," and "improved accuracy." The patent idea generated will then be "a new AI algorithm that achieves efficiency through automation." The user provides feedback on this idea, and the server makes improvements.

[0591] Also, when an online shopping site operator creates a description for a new product (e.g., a "smart watch"), they provide the product information (product name, features, price, brand) to the server. The server generates a prompt like this:

[0592] New Product: Smartwatch

[0593] Brand: General company name

[0594] Main features: Heart rate monitor, GPS function, waterproof

[0595] Price: 19,800 yen

[0596] Description:

[0597] Based on this prompt, the server generates a product description, which is used as the final description after the user confirms and makes any necessary corrections.

[0598] In this way, this system can streamline the patent application process and the process of generating product descriptions for online shopping sites, significantly reducing the burden on users.

[0599] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0600] Step 1:

[0601] The server receives invention-related materials (such as technical documents and emails between parties) uploaded by users from their terminals, regardless of the file format of the materials.

[0602] Input: Invention-related files

[0603] Output: Received material

[0604] Step 2:

[0605] The server analyzes the received material using a natural language processing (NLP) engine to extract important keywords and concepts. During this process, the text is tokenized through morphological analysis and keywords are extracted.

[0606] Input: Received material

[0607] Output: Extracted keywords and concepts

[0608] Step 3:

[0609] The server generates patent ideas based on the extracted keywords and concepts, and the generated ideas are generated in text format using an AI model (e.g., GPT-2).

[0610] Input: Extracted keywords and concepts

[0611] Output: Generated patent ideas

[0612] Step 4:

[0613] The server sends the generated patent ideas to the terminal and presents them to the user, who then provides feedback on the ideas.

[0614] Input: Generated patent idea

[0615] Output: User feedback

[0616] Step 5:

[0617] The server receives user feedback and uses the AI ​​model to refine the patent idea, a process that is repeated until the user is satisfied.

[0618] Input: User feedback

[0619] Output: Improved patent idea

[0620] Step 6:

[0621] The server searches a patent database to find existing patents that may conflict with the patent idea.

[0622] Input: Improved patent idea

[0623] Output: Competitive patent information

[0624] Step 7:

[0625] The server provides users with information on competing patents and suggests necessary adjustments.

[0626] Input: Competing patent information

[0627] Output: Information and suggestions provided to the user

[0628] Step 8:

[0629] The server generates patent application documents using an NLG engine based on the finalized idea.

[0630] Input: A confirmed idea

[0631] Output: Generated patent application document

[0632] Step 9:

[0633] The user uses the terminal to check the generated patent application document and sends instructions to the server to make any necessary corrections.

[0634] Input: Generated patent application document

[0635] Output: User's correction instructions

[0636] Step 10:

[0637] The server reflects the correction instructions and completes the final patent application document, which is then submitted to the Patent Office's online system.

[0638] Input: User correction instructions

[0639] Output: Final patent application document submitted to the patent office

[0640] Step 11:

[0641] Product information (such as product name, features, price, brand, etc.) is received, and a prompt sentence is created based on this to generate a product description.

[0642] Input: Product information

[0643] Output: prompt statement

[0644] Step 12:

[0645] The server uses a generative AI model (e.g., GPT-2) to generate a product description based on the prompt.

[0646] Input: prompt statement

[0647] Output: Generated product description

[0648] Step 13:

[0649] The server provides the generated product description to the user, who then reviews and makes any necessary corrections.

[0650] Input: Generated product description

[0651] Output: Product description reviewed and corrected by the user

[0652] Step 14:

[0653] The server reflects the user's confirmation and corrections and generates a final product description.

[0654] Input: User correction instructions

[0655] Output: Final product description

[0656] In this way, the system streamlines the patent application process and the product description generation process for online shopping sites.

[0657] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0658] Understood. Below, based on the scope of the claims, we have prepared a "Description of the Invention" for the invention that combines an emotion engine.

[0659] ---

[0660] This invention combines an emotion engine with a system and implementation method for streamlining intellectual property applications. This system recognizes the user's emotions during the patent idea generation and refinement process and makes adjustments based on the feedback, thereby achieving efficient and effective patent applications.

[0661] Data entry and analysis

[0662] Users use their devices to prepare and organize invention-related policy documents and emails with related parties. The devices are equipped with a means to upload these documents to the server. The server receives the uploaded data and uses a natural language processing (NLP) engine to tokenize it, perform morphological analysis, and extract important keywords and concepts.

[0663] Idea generation and refinement

[0664] The server generates hypotheses for patent ideas based on the extracted keywords and concepts. The hypotheses are presented to the user's terminal, and the user provides feedback on the presented patent ideas.

[0665] The server receives user feedback and uses the AI ​​model to refine the patent idea, which is then presented to the user again, and the process is repeated until the user is satisfied.

[0666] Utilizing the Emotion Engine

[0667] When collecting feedback, the server uses an emotion engine to recognize the user's emotions, for example, by capturing emotional data through the style and tone of the user's feedback, as well as facial and voice analysis (if required).

[0668] The emotion engine analyzes the user's emotional state, such as whether their feedback is positive or negative, flexible or strict, and adjusts how the idea is refined and presented based on the results. For example, if the user responds statistically positively, the idea will be explored further, and if the user responds negatively, a different approach will be tried.

[0669] Competitive research and document generation

[0670] Based on the patent idea identified, the server searches the patent database for existing patents that may conflict with it, reporting the results to the user and suggesting adjustments if necessary.

[0671] The server then generates a patent application document based on the finalized idea, using a natural language generation (NLG) engine to adjust the document's format and writing style, even adjusting it based on the user's emotional state.

[0672] Application Procedure

[0673] The user uses the terminal to check the generated patent application document and indicate any necessary corrections. The server reflects these correction instructions and completes the final patent application document. The server then processes this completed document for submission to the Patent Office's online system. The user monitors the application status on the terminal and provides additional information and materials as needed.

[0674] Specific examples

[0675] For example, if a user wants to apply for a patent for a new AI algorithm, they first upload their policy documents and related emails to the server. The server analyzes this information and extracts keywords such as "new AI algorithm," "time efficiency," and "improved accuracy." Based on these keywords, it generates a hypothesis: "a new AI algorithm that achieves efficiency through automation."

[0676] When users provide feedback on a proposed idea, their emotional state (e.g., positive anticipation or negative concern) is also analyzed by the emotion engine. The server uses this data to refine the idea and present it to the user again. The system also adjusts the tone and format of patent application documents, taking the user's emotional state into account.

[0677] In this way, by utilizing the emotion engine, the entire process from patent idea discovery to application processing can be made more personalized, efficient, and effective.

[0678] The processing flow will be explained below.

[0679] Step 1:

[0680] The user prepares invention-related policy documents and emails between related parties on the terminal, which then uploads the data to the server.

[0681] Step 2:

[0682] The server receives the uploaded data and then invokes a natural language processing (NLP) engine to tokenize the data and perform morphological analysis to extract important keywords and concepts.

[0683] Step 3:

[0684] The server generates hypotheses for patent ideas based on the extracted keywords and concepts, a process that provides initial idea suggestions based on similar ideas and an existing knowledge base.

[0685] Step 4:

[0686] The server presents the generated hypotheses for the patent idea to the user's terminal, which the user confirms.

[0687] Step 5:

[0688] Users can input feedback on the presented patent idea via a terminal, for example, suggesting "ways to apply this idea to a specific industry" or "ways to further improve accuracy."

[0689] Step 6:

[0690] The device sends user feedback data to a server, which analyzes the received feedback and uses AI models to refine the idea.

[0691] Step 7:

[0692] The server uses an emotion engine when collecting feedback to recognize the user's emotions, for example by analyzing the style and tone of the feedback, or facial expressions and voice (if applicable).

[0693] Step 8:

[0694] The server adjusts how the patent idea is refined and presented based on the emotional data obtained by the emotion engine. For example, if the user expresses negative emotions, it can suggest different approaches and solutions.

[0695] Step 9:

[0696] The server then presents the refined patent idea to the user again, and this process is repeated until the user is satisfied.

[0697] Step 10:

[0698] The server accesses a patent database to search for existing patents that may be competing with the patent idea, and reports the search results to the user.

[0699] Step 11:

[0700] The server automatically generates patent application documents based on the confirmed patent idea, using a natural language generation (NLG) engine to refine the document's format and writing style.

[0701] Step 12:

[0702] The server sends the generated patent application document to the user's terminal, where the user can review it and make any necessary corrections.

[0703] Step 13:

[0704] The terminal sends the user's correction instructions to the server, which then reflects the correction instructions and completes the final patent application document.

[0705] Step 14:

[0706] The server submits the completed patent application documents to the Patent Office's online system, where users can monitor the application status on their devices and provide additional information or materials as needed.

[0707] This allows systems that utilize emotion engines to make the entire process, from discovering patent ideas to filing applications, more efficient and effective.

[0708] Example 2

[0709] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0710] The traditional patent application process requires many steps, including organizing invention-related materials, generating patent ideas, collecting feedback and refining the ideas, researching competing patents, and preparing patent application documents, and is extremely time-consuming and labor-intensive. Furthermore, because the user's emotional state is not taken into consideration, the quality of feedback is often poor and ideas are often not effectively refined. This leads to a lower success rate for patent applications.

[0711] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0712] In this invention, the server includes means for receiving materials related to the invention, means for analyzing the received materials and extracting important keywords and concepts, means for generating patent ideas from the extracted information, means for receiving user feedback and improving the patent ideas, means for analyzing the user's emotional state and adjusting the method for improving and presenting the ideas based on the feedback, means for searching for competing patents based on the patent ideas, means for providing the user with information on competing patents, means for generating patent application documents, and means for submitting the generated patent application documents to the Patent Office, thereby significantly improving the efficiency of the patent application process and enabling personalized support based on the user's emotional state.

[0713] "Materials related to the invention" refers to documents and data that describe the content, background, and technical features of the invention.

[0714] A "server" is a computer system that receives, analyzes, processes, stores, and transmits data.

[0715] "Natural language processing" refers to the technology that allows computers to analyze, generate, and understand human language.

[0716] "Keywords and concepts" are important words and concepts extracted from the materials that are necessary for generating patent ideas.

[0717] A "patent idea" is a specific concept or proposal for a particular technology or invention.

[0718] "Feedback" refers to the evaluations and opinions that users give about patent ideas.

[0719] An "emotion recognition engine" is a technology for analyzing emotions from user feedback.

[0720] A "competing patent" is an existing patent that is similar to or related to the patent idea being applied for.

[0721] "Patent application documents" means official documents prepared for a patent application.

[0722] "Patent Office" refers to the government agency that accepts, examines, and registers patent applications.

[0723] An "AI model" is a machine learning model that uses artificial intelligence to generate and improve patent ideas.

[0724] A "prompt sentence" is an input sentence given to a generative AI model, based on which the AI ​​generates output.

[0725] This invention is a system aimed at streamlining the patent application process, providing comprehensive support for everything from organizing and analyzing invention-related materials to generating patent ideas, collecting and refining feedback, conducting competitive research, and preparing and submitting patent application documents. The system's hardware configuration includes a user device and a server for processing data. The software configuration includes a natural language processing engine (e.g., SpaCy), a generative AI model (e.g., GPT-3), an emotion recognition engine, a patent database search engine, and a natural language generation engine (NLG engine).

[0726] Data entry and analysis

[0727] Users use their devices to prepare invention-related policy documents and emails with stakeholders, and upload these documents to the server. The device provides a file upload function, allowing users to select PDFs, Word documents, etc. from their local directory and send them to the server. The server stores the received data and uses a natural language processing (NLP) engine to tokenize the data, perform morphological analysis, and extract important keywords and concepts.

[0728] Idea generation and feedback

[0729] The server uses a generative AI model to generate hypotheses for patent ideas based on the extracted keywords and concepts. For example, by entering a prompt to generate a patent idea for a "new AI algorithm," detailed ideas are generated. The generated ideas are displayed on the user's device. The user can provide feedback on the presented patent idea. The feedback is entered in a simple comment field and sent to the server.

[0730] Utilizing the Emotion Engine

[0731] The server analyzes the feedback provided by the user using an emotion recognition engine. It obtains the user's emotional data from the content and tone of the feedback, and, if necessary, through voice and facial expression analysis. The emotion recognition engine determines whether the feedback is positive or negative, and adjusts how the patent idea is improved and presented based on the results.

[0732] Competitive research and document generation

[0733] The server searches patent databases based on the patent idea to find competing patents. The search results are provided to the user, suggesting modifications or adjustments to the idea as needed. The server then uses a natural language generation (NLG) engine to generate the patent application document, which can automatically adjust the format and writing style of the patent document. It also adjusts based on the user's emotional state.

[0734] Application Procedure

[0735] The generated patent application document is reviewed on the user's device, and the user can input correction instructions as needed. The server reflects these instructions and completes the final patent application document. The server then processes the completed document for submission to the Patent Office's online system. The user can monitor the application status on their device and provide additional information and materials.

[0736] In this way, the system aims to consistently support and streamline the patent application process. As a specific example, when applying for a patent for a new AI algorithm, the following prompt is entered: "Generate a patent idea for a new AI algorithm that achieves efficiency through automation." Based on this prompt, the generative AI model will generate detailed ideas.

[0737] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0738] Step 1:

[0739] The user uses a device to prepare policy documents and emails related to the invention and uploads them to the server. The input is a PDF, Word document, etc., and is sent using the device's upload function. The documents are saved on the server as output.

[0740] Step 2:

[0741] The server saves the received data. The input is the file uploaded in the previous step, and the destination is the server's file system. The output is the data saved on the server.

[0742] Step 3:

[0743] The server runs a natural language processing (NLP) engine to tokenize and morphologically analyze the stored material. It uses the text data of the received material as input. Specifically, it uses an NLP engine (e.g., SpaCy) to extract nouns and verbs. The output is a list of important keywords and concepts.

[0744] Step 4:

[0745] The server uses a generative AI model to generate patent idea hypotheses based on the extracted keywords and concepts. It uses a list of keywords or concepts and a prompt (e.g., "Please generate a patent idea for a new AI algorithm") as input. The generated patent idea hypotheses are obtained as output.

[0746] Step 5:

[0747] The server sends the generated patent idea assumptions to the user's terminal and displays them. The generated patent idea assumptions are used as input and are displayed on the user's terminal as output.

[0748] Step 6:

[0749] Users submit feedback on the presented patent ideas from their devices. The system uses the user's evaluations and opinions as input, and sends the feedback entered in the comment field from the device. The feedback is sent to the server as output.

[0750] Step 7:

[0751] The server receives the feedback provided by the user and analyzes it with an emotion recognition engine. Using the feedback content as input, the emotion recognition engine determines the emotional state, whether positive or negative. The output is the emotion analysis result.

[0752] Step 8:

[0753] The server adjusts how to improve and present the patent idea based on the sentiment analysis results. It uses the sentiment analysis results and the original patent idea hypotheses as input. It uses the generative AI model again to generate the improved patent idea. The improved patent idea is obtained as output.

[0754] Step 9:

[0755] The server presents the improved patent idea to the user again and repeats the same feedback process, using the improved patent idea as input and presented to the user's terminal as output.

[0756] Step 10:

[0757] The server searches a patent database for competing patents based on the confirmed patent idea. It uses keywords and concepts from the confirmed patent idea as input and sends a search query to the patent database. The output is a list of competing patents.

[0758] Step 11:

[0759] The server provides the user with information on competing patents. It uses a list of competing patents obtained from a patent database as input and reports it to the user. It displays the competing patent information on a terminal as output.

[0760] Step 12:

[0761] The server uses a natural language generation (NLG) engine to generate a patent application document based on the finalized patent idea. Using the content of the finalized patent idea as input, the NLG engine generates the format and writing style of the document. The patent application document is created as output.

[0762] Step 13:

[0763] The user uses a terminal to check the generated patent application document and instructs on necessary corrections. The patent application document is used as input, and correction instructions are entered in the comment field. The correction instructions are sent to the server as output.

[0764] Step 14:

[0765] The server reflects the correction instructions and completes the final patent application document. The server uses the user's correction instructions as input and updates the patent application document. The final patent application document is completed as output.

[0766] Step 15:

[0767] The server submits the completed patent application to the Patent Office's online system. It uses the final patent application as input and sends the data to the online system. The output is a confirmation of receipt from the Patent Office.

[0768] Step 16:

[0769] The user monitors the application status on the terminal and provides additional information and materials as needed. The user uses notifications from the Patent Office's online system as input and submits the additional information and materials from the terminal. The additional information and materials are sent to the Patent Office as output.

[0770] (Application example 2)

[0771] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0772] The patent application process is complex and requires a lot of time and effort. Furthermore, efficiently incorporating user feedback and generating optimal patent ideas is a difficult problem. Furthermore, existing systems have not been able to utilize feedback that takes into account the user's emotional state. This results in a lack of improvement in the efficiency and quality of patent applications, and makes searching for competing patent information and preparing application documents cumbersome. Therefore, a system that solves these issues, streamlines the patent application process, and improves user satisfaction is needed.

[0773] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving materials related to the invention, means for analyzing the received materials and extracting important keywords and concepts, means for generating a patent idea from the extracted information, means for receiving user feedback and improving the patent idea, means for analyzing the user's emotional state at the time of feedback, means for adjusting the patent idea according to the analyzed emotional state, means for searching for competing patents based on the patent idea, means for providing the user with information on competing patents, means for generating patent application documents, and means for submitting the generated patent application documents to the Patent Office. This enables the patent application process to be carried out efficiently and effectively, and improves user satisfaction.

[0774] "Materials related to the invention" refers to information and documents necessary for filing a patent application, including relevant technical documents, research data, email content, etc.

[0775] "Means for receiving" refers to the function or method by which the server receives materials related to the invention from the user and stores them in storage.

[0776] "Means for analysis" refers to the functions and methods for processing received materials and extracting important keywords and concepts using natural language processing technology.

[0777] "Extracted information" refers to keywords and concepts obtained from the analyzed materials, and is the basis for generating patent ideas.

[0778] A "means for generating patent ideas" is a function or method for automatically generating new patent hypotheses or proposals based on the extracted information.

[0779] "User Feedback" means any opinion, comment, or evaluation provided by a user regarding a patent idea.

[0780] "Means for improving the patent idea" refers to the functions and methods for further improving and optimizing the patent idea based on the feedback received.

[0781] "Means for analyzing emotional state" refers to techniques or methods for analyzing the user's text, voice, or facial expressions during feedback to understand and classify their emotions.

[0782] "Means for adjusting patent ideas" refer to functions and methods for changing and optimizing the content and presentation of patent ideas according to the user's emotional state.

[0783] The "means for searching competing patents" refers to a function or method for searching a patent database for existing patents related to the generated patent idea.

[0784] "Competitive Patent Information" is detailed data about existing patents that have been searched and is a reference provided to the user.

[0785] The "means for generating patent application documents" refers to a function or method for automatically creating documents required for a patent application based on a confirmed patent idea.

[0786] "Means for submission" refers to the functionality or method for submitting the generated patent application documents to the Patent Office online or offline.

[0787] MODE FOR CARRYING OUT THE INVENTION

[0788] The embodiments of the present invention will be described in detail below.

[0789] System Overview

[0790] The system of the present invention is equipped with a series of means for streamlining the patent application process. The system is mainly composed of three elements: a server, a terminal, and a user. The server receives and analyzes invention-related materials and uses that information to generate and refine patent ideas. The terminal functions as an interface for users to provide feedback and upload materials.

[0791] Hardware and software used

[0792] 1. Hardware:

[0793] Server: High-performance data processing server

[0794] Device: Smartphone, smart glasses, or computer

[0795] 2. Software:

[0796] Natural Language Processing Engine (TextBlob)

[0797] Sentiment analysis engine (Hugging Face transformers library)

[0798] Database systems (e.g. PostgreSQL)

[0799] Patent database search function

[0800] Natural Language Generation Engine (Natural Language Model)

[0801] Specific processing flow

[0802] First, the user uploads documents related to the invention using a terminal. The server stores the received documents in storage. A natural language processing engine is used to tokenize and analyze the documents to extract important keywords and concepts. Based on this extracted information, a patent idea is generated.

[0803] The generated patent ideas are presented to the user's device. The user provides feedback on the presented ideas. During the feedback process, the user's emotional state is analyzed using an emotion analysis engine. This allows the idea to be adjusted according to the user's emotional state.

[0804] Once a patent idea is finalized, the server searches the patent database for relevant competing patents, and provides the competing patent information to the user, allowing them to adjust the idea as needed.

[0805] Finally, the server generates a patent application document based on the confirmed patent idea, which can then be submitted to the patent office online or offline. Users can monitor the application status through their devices and provide additional information and materials as needed.

[0806] Examples of concrete examples and prompts

[0807] For example, if a user wants to apply for a patent for a new voice recognition technology, they first upload technical documents and related emails from their device to the server. The server analyzes this information and extracts keywords such as "voice recognition technology," "improved accuracy," and "real-time processing." Based on these keywords, a patent idea for "a new algorithm to improve the accuracy of voice recognition" is generated. The user then provides feedback on this idea, saying, "This idea is interesting, but further details need to be specified."

[0808] Example prompt for a generative AI model:

[0809] User feedback: "This is a great idea, but we should also consider how to improve the accuracy."

[0810] In this way, the system of the present invention can streamline the entire process from the generation of a patent idea to the filing of an application, and can quickly reflect user feedback.

[0811] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0812] Step 1:

[0813] The user uploads documents related to the invention using a terminal. The input includes files such as technical documents and related emails. This document is sent to the server, which then stores the received documents in storage. The output is the saved document file. Specifically, the user selects the documents using the file upload interface and presses the upload button, which sends the documents to the server.

[0814] Step 2:

[0815] The server analyzes the uploaded materials using a natural language processing engine. The material file saved in step 1 is used as input. The analysis process tokenizes the materials and extracts important keywords and concepts. The output is the extracted keywords and concepts. Specifically, the TextBlob library is used to tokenize the documents and perform morphological analysis.

[0816] Step 3:

[0817] The server generates patent ideas based on the extracted keywords and concepts. The input includes the keywords and concepts extracted in step 2. An AI model is used to generate patent ideas based on this information. The output is the generated patent idea. Specifically, the generative AI model is used to create patent ideas on themes such as "new algorithms" and "efficiency."

[0818] Step 4:

[0819] The server presents the generated patent idea to the user's terminal. The patent idea created in step 3 is used as input. The user provides feedback on the presented idea. The output is the user's feedback. Specifically, the server displays the patent idea on the user interface and provides a feedback input field.

[0820] Step 5:

[0821] The server receives the user's feedback and analyzes the feedback content using a sentiment analysis engine. The feedback received in step 4 is used as input. The sentiment analysis determines the user's emotional state (positive, negative, etc.). The output is the analyzed emotional data. Specifically, the server utilizes the Hugging Face transformers library to perform sentiment analysis on the feedback text.

[0822] Step 6:

[0823] The server adjusts the patent idea based on the analyzed emotional state. The input includes the emotional data obtained in step 5 and the patent idea generated in step 3. The idea is refined according to the emotional state and presented to the user again. The output is the adjusted patent idea. Specifically, the server evaluates the emotional data and updates the content and presentation method of the patent idea.

[0824] Step 7:

[0825] The server searches the patent database based on the confirmed patent idea to find related competing patents. The input includes the patent idea confirmed in step 6. The server outputs the competing patent information obtained as a search result. Specifically, it uses the patent database search function to extract related patents from the database.

[0826] Step 8:

[0827] The server provides the searched competing patent information to the user and generates a patent application document. The input includes the competing patent information obtained in step 7 and the patent idea confirmed in step 6. The output is the generated patent application document. Specifically, the server uses a natural language generation engine to automatically create the patent application document.

[0828] Step 9:

[0829] The server submits the generated patent application document to the Patent Office. The patent application document created in step 8 is used as input. The document is submitted to the Patent Office online or offline, and then confirmed. The output is the acceptance status of the patent application. Specifically, the document is uploaded through the Patent Office's online system, and the application number, etc. are confirmed.

[0830] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0831] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0832] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0833] [Third embodiment]

[0834] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0835] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0836] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0837] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0838] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0839] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0840] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0841] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0842] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0843] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0844] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0845] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0846] Understood. I have prepared the following "Mode for carrying out the invention" based on the scope of the claims.

[0847] ---

[0848] This invention relates to a system and method for efficiently filing intellectual property applications. This system generates patent ideas and files patent applications through multiple steps, with a server, a terminal, and a user playing their respective roles.

[0849] Data entry and analysis

[0850] The user uses the terminal to prepare and organize policy documents and emails between related parties related to the invention. The terminal is equipped with a means to upload these documents to the server. The server receives the uploaded data and analyzes it using a natural language processing (NLP) engine.

[0851] During the analysis process, the server tokenizes the received data and performs morphological analysis to extract important keywords and concepts, such as "AI algorithm," "time efficiency," and "improved accuracy."

[0852] Idea generation and refinement

[0853] The server generates hypotheses for patent ideas based on the extracted keywords and concepts. The hypotheses are then presented to the user's device. The user can then provide feedback on the proposed tentative patent ideas, such as adding "methods for further refinement" or "applications to specific industries."

[0854] The server receives user feedback and refines the patent idea using an AI model. The improved idea is then presented to the user again, and this process is repeated until the user is satisfied.

[0855] Competitive research and document generation

[0856] After the idea is confirmed, the server searches the patent database for existing patents that may conflict with the patent idea. The results of the conflict search are reported to the user and necessary adjustments are proposed.

[0857] The server generates a patent application document based on the finalized idea. In this process, the server uses a natural language generation (NLG) engine to create a document in accordance with the patent application format.

[0858] Application Procedure

[0859] The user uses a terminal to check the generated patent application document and instruct the server on any necessary corrections. The server reflects the correction instructions and completes the final patent application document. The server then processes the completed document for submission to the Patent Office's online system.

[0860] Specific examples

[0861] For example, if a user wants to apply for a patent for a new AI algorithm, they first upload their policy documents and related emails to the server. The server analyzes these and extracts keywords such as "new AI algorithm," "time efficiency," and "improved accuracy." Based on these keywords, the server generates a hypothesis for the patent idea: "A new AI algorithm that achieves efficiency through automation." Based on the user's feedback, the server refines and optimizes the idea.

[0862] The server then searches the patent database for competing patents and reports the results to the user. Based on the finalized idea, the server generates a patent application document, which is then submitted to the patent office after the user has confirmed and revised it.

[0863] In this way, the present invention is a system that enables the entire process from the discovery of a patent idea to the application procedure to be carried out efficiently and effectively.

[0864] The processing flow will be explained below.

[0865] Step 1:

[0866] The user prepares invention-related policy documents and emails between related parties on the terminal, which then uploads the data to the server.

[0867] Step 2:

[0868] The server receives the uploaded data and then invokes a natural language processing (NLP) engine to tokenize the data and perform morphological analysis to extract important keywords and concepts.

[0869] Step 3:

[0870] The server generates hypotheses for patent ideas based on the extracted keywords and concepts, a process that provides initial idea suggestions based on similar ideas and an existing knowledge base.

[0871] Step 4:

[0872] The server presents the generated hypotheses for the patent idea to the user's terminal, which the user confirms.

[0873] Step 5:

[0874] Users can input feedback on the presented patent idea via a terminal, for example, suggesting "ways to apply this idea to a specific industry" or "ways to further improve accuracy."

[0875] Step 6:

[0876] The device sends user feedback data to a server, which analyzes the received feedback and uses AI models to refine the idea.

[0877] Step 7:

[0878] The server then presents the refined patent idea to the user again, and this process is repeated until the user is satisfied with the result.

[0879] Step 8:

[0880] The server accesses a patent database to search for existing patents that may be competing with the patent idea, and reports the search results to the user.

[0881] Step 9:

[0882] The server automatically generates patent application documents based on the confirmed patent idea, using a natural language generation (NLG) engine to refine the document's format and writing style.

[0883] Step 10:

[0884] The user checks the patent application document generated on the terminal and instructs the terminal to make any necessary corrections, which are then sent to the server.

[0885] Step 11:

[0886] The server reflects the user's correction instructions and finally completes the patent application document.

[0887] Step 12:

[0888] The server submits the completed patent application to the Patent Office's online system, where users can monitor the application status and provide additional information or materials as needed.

[0889] This streamlines the entire process from discovering a patent idea to filing an application.

[0890] Example 1

[0891] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0892] The current intellectual property application process requires a lot of time and effort, is inefficient in terms of patent idea generation, competitive research, and application document preparation, and places a heavy burden on users. This problem makes it difficult for inventors to protect their new ideas in a timely manner, which can result in a loss of competitiveness. Furthermore, existing systems rely on manual processes for analyzing information and refining ideas, which risks reducing the accuracy and speed of the work. To solve these issues, there is a need for a system that can automate the entire intellectual property application process efficiently and effectively.

[0893] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0894] In this invention, the server includes means for receiving digital documents, means for analyzing the received documents and extracting important information, means for generating intellectual property ideas from the extracted information, means for receiving user opinions and improving the intellectual property ideas, means for searching existing intellectual property based on the intellectual property ideas, means for presenting search results to the user, means for generating intellectual property application documents, and means for submitting the generated intellectual property application documents, thereby automating the entire intellectual property application process and enabling rapid and accurate patent idea generation, competitive research, and application document preparation and submission.

[0895] A "digital document" is a document containing information stored in electronic form that can be viewed, edited, or transmitted using a computer or other electronic device.

[0896] "Important information" refers to keywords and concepts contained within digital documents that are key to patent idea generation and competitive research.

[0897] "Intellectual property idea" refers to a concept or proposal for an invention or technical solution that is the subject of a patent application.

[0898] "User Feedback" means feedback, comments, or suggestions for correction provided by a User regarding an Intellectual Property Idea.

[0899] "Existing intellectual property" refers to technologies and inventions that have already been patented and are publicly available and registered in patent databases, etc.

[0900] "Search results" refers to the list of relevant information and patents that are obtained when searching existing intellectual property.

[0901] "Intellectual Property Application Document" refers to the official patent application document submitted to the Patent Office, which contains details of the invention and its technical features.

[0902] This invention relates to a system and method for efficiently filing intellectual property applications. In this system, a server, a terminal, and a user each play their respective roles, and the system generates patent ideas and files patent applications through multiple steps.

[0903] Entering and Submitting Data

[0904] The user prepares and organizes policy documents and emails between related parties related to the invention. The user uploads these documents to the terminal. The terminal has a means to send these documents to the server.

[0905] Data analysis

[0906] The server receives the uploaded digital document. It then analyzes the received digital document using a natural language processing (NLP) engine to extract important information. During the analysis process, the server tokenizes the received data and performs morphological analysis to extract important keywords and concepts. For example, keywords such as "new AI algorithm," "time efficiency," and "improved accuracy" are extracted.

[0907] Idea generation

[0908] The server generates hypotheses for intellectual property ideas based on the extracted keywords and concepts. The hypotheses are then presented to the user's device. For example, a "patent idea for a technology that uses a new AI algorithm to improve time efficiency and accuracy" might be generated.

[0909] Brushing up ideas

[0910] Users provide feedback on the proposed tentative patent idea, such as adding "further refinement methods" or "applications to specific industries." The server receives the user's feedback and refines the intellectual property idea using a generative AI model. The improved idea is presented to the user again, and this process is repeated until the user is satisfied.

[0911] Competitive Research

[0912] After the intellectual property idea is confirmed, the server will refer to the patent database to search for existing intellectual property that may conflict with the intellectual property idea, and report the results of the conflict search to the user and propose necessary adjustments.

[0913] Generate intellectual property application documents

[0914] The server generates intellectual property application documents based on the finalized idea. In this process, the server uses a natural language generation (NLG) engine to create documents in accordance with the patent application format.

[0915] Application Procedure

[0916] The user checks the generated patent application document on a terminal and instructs the server on any necessary corrections. The server reflects the correction instructions and completes the final intellectual property application document. The server then processes the completed document for submission to the Patent Office's online system.

[0917] Specific examples

[0918] For example, if a user wants to apply for a patent for a new AI algorithm, they first upload their policy documents and related emails to the server. The server analyzes these and extracts keywords such as "new AI algorithm," "time efficiency," and "improved accuracy." Based on these keywords, the server generates a hypothesis for the patent idea: "A new AI algorithm that achieves efficiency through automation." Based on the user's feedback, the server refines and optimizes the idea.

[0919] Specific examples of input prompts for generative AI models

[0920] "I would like to apply for a patent for a new AI algorithm. I would like you to generate patent ideas based on policy documents."

[0921] "Please tell me the steps to refine my patent idea for improving efficiency and accuracy."

[0922] In this way, the present invention is a system that enables the entire process from the discovery of a patent idea to the application procedure to be carried out efficiently and effectively.

[0923] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0924] Step 1:

[0925] Entering and Submitting Data

[0926] The user prepares policy documents and emails between stakeholders related to the invention. Specifically, the user saves data, including research papers and communication records with project members, on the device. Next, the user selects these documents through a dedicated app or web portal and presses the "Upload" button. The device encodes the selected data and sends it to the specified endpoint on the server via an HTTP POST request.

[0927] Input: Policy documents and emails related to inventions

[0928] Output: Data sent to the server

[0929] Step 2:

[0930] Data reception and analysis

[0931] The server receives the data sent from the device. It then analyzes the received data using a natural language processing (NLP) engine. Specifically, the server tokenizes the data and performs morphological analysis. This extracts important keywords and concepts, such as "AI algorithm," "time efficiency," and "accuracy improvement."

[0932] Input: Data sent to the server

[0933] Output: Extracted keywords and concepts

[0934] Step 3:

[0935] Idea generation

[0936] The server generates intellectual property ideas based on the extracted keywords and concepts. In this process, a generative AI model is used to create hypotheses for patent ideas. For example, a "patent idea for a technology that uses a new AI algorithm to improve time efficiency and accuracy" is generated. The generated idea is then sent to the user's device.

[0937] Input: Extracted keywords and concepts

[0938] Output: Generated intellectual property ideas

[0939] Step 4:

[0940] Brushing up ideas

[0941] Users provide feedback on the proposed tentative patent idea. For example, they can enter comments to add "methods for further improvement" or "application to a specific industry." The server receives the user's feedback and refines the idea using a generative AI model. The improved idea is then presented to the user again.

[0942] Input: User feedback

[0943] Output: Improved intellectual property ideas

[0944] Step 5:

[0945] Competitive research

[0946] The server searches patent databases based on the confirmed intellectual property idea, and references existing patent databases to search for existing intellectual property that may conflict with the intellectual property idea. The search results are reported to the user, and necessary adjustments are suggested. Specifically, the server issues queries such as keyword searches and concept matching to patent databases.

[0947] Input: Confirmed intellectual property idea

[0948] Output: List of competing patents

[0949] Step 6:

[0950] Generate application documents

[0951] The server then generates an intellectual property application document based on the finalized idea. During this process, the server uses a natural language generation (NLG) engine to create a document in a patent application format. Specifically, the document is generated in a format such as, "This invention relates to a method for improving the efficiency of specific operations using a new AI algorithm."

[0952] Input: Confirmed intellectual property idea

[0953] Output: Intellectual property application document

[0954] Step 7:

[0955] Application Procedure

[0956] The user checks the generated patent application document using a terminal and instructs the server on any necessary corrections. The server reflects the correction instructions and completes the final intellectual property application document. The server then submits the completed document to the Patent Office's online system. During this process, the user previews the patent application document and directly inputs corrections using a markup tool. The server also receives the user's correction instructions and regenerates the updated document.

[0957] Input: Finalized intellectual property application documents

[0958] Output: Submitted intellectual property application documents

[0959] In this way, the system can efficiently carry out the entire process from patent idea generation to application procedures.

[0960] (Application example 1)

[0961] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0962] The patent application process is extremely complex and time-consuming, resulting in inefficiencies in steps such as extracting important keywords and concepts, generating patent ideas, conducting competitive research, and preparing patent application documents. Furthermore, generating product descriptions quickly and effectively on online shopping sites requires detailed manual writing, placing a significant burden on operators. A system that solves these problems is needed.

[0963] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0964] In this invention, the server includes means for receiving materials related to the invention, means for analyzing the received materials and extracting important keywords and concepts, means for generating patent ideas from the extracted information, means for receiving user feedback and improving the patent ideas, means for searching for competing patents based on the patent ideas, means for providing information on competing patents to the user, means for generating patent application documents, means for submitting the generated patent application documents to the Patent Office, means for receiving product information and generating product descriptions, and means for the user to confirm and modify the generated product descriptions. This improves the efficiency of the patent application process and enables the rapid generation of product descriptions on online shopping sites.

[0965] "Materials related to the invention" refers to data including technical documents required for patent applications, emails between parties, and other related information.

[0966] "Analysis" refers to the process of using natural language processing (NLP) technology to understand the content of received materials and extract important keywords and concepts.

[0967] "Keywords and concepts" are words and ideas that are considered important in generating patent ideas and preparing patent application documents.

[0968] A "patent idea" is a technical idea that is the subject of a patent application and is generated based on the extracted keywords and concepts.

[0969] "Feedback" refers to opinions and suggestions for improvement that users provide to the system.

[0970] A "competing patent" refers to an existing patent registered in a patent database that is similar to the generated patent idea.

[0971] "Patent application document" means a document prepared in the form required to apply for a patent.

[0972] "Patent Office" refers to the public institution that accepts and reviews patent applications.

[0973] "Product information" refers to information such as the name, features, price, and brand of the product sold on the online shopping site.

[0974] A "product description" is a description of a product that is posted on an online shopping site and is text that conveys the appeal of the product to users.

[0975] This invention relates to a system and its implementation method for improving the efficiency of the patent application process and automatically generating product descriptions for online shopping sites. This system is mainly composed of three components: a server, a terminal, and a user.

[0976] Server Roles

[0977] The server has the following features:

[0978] 1. Document receiving means: This has the function of receiving invention-related documents uploaded by users, including technical documents and emails between related parties.

[0979] 2. Analysis method: The received material is analyzed using a natural language processing (NLP) engine to extract important keywords and concepts. This process is carried out through morphological analysis.

[0980] 3. Patent idea generation means: Patent ideas are generated based on the extracted keywords and concepts. The generated ideas are presented to the user.

[0981] 4. Improve method: Receive user feedback and improve the patent idea using an AI model (e.g., GPT-2). This process is repeated until the user is satisfied.

[0982] 5. Competing patent search tool: Consult patent databases to search for existing patents that may compete with the patent idea.

[0983] 6. Information provision means: Provide users with information on competing patents and suggest necessary adjustments.

[0984] 7. Patent application document generation method: A patent application document is generated based on the confirmed idea. An NLG (Natural Language Generation) engine is used in this process.

[0985] 8. Patent Office Submission Method: Submit the final patent application documents to the Patent Office's online system.

[0986] Furthermore, the server also comprises the following means, which are of particular importance in the application of the invention:

[0987] 1. Product information receiving means: Receives product information (e.g., product name, features, price, brand, etc.) from the online shopping site.

[0988] 2. Product description generation method: Generate product descriptions based on the received product information. Generate text using an AI model (e.g., GPT-2).

[0989] 3. User confirmation and correction: Provides a function for users to confirm the generated product description and correct it if necessary.

[0990] Device Role

[0991] The terminal provides an interface with the user. The user uses the terminal to upload invention-related materials and product information to the server. The terminal also presents ideas sent from the server and generated product descriptions to the user and receives feedback.

[0992] User Roles

[0993] The user's role is to provide documents and product information to the server through the terminal, and also to provide feedback on patent ideas and product descriptions provided by the server, and to give instructions for necessary improvements.

[0994] Specific examples

[0995] For example, if a user wants to apply for a patent for a new AI algorithm, they upload technical documents and related emails to the server. The server analyzes these and extracts keywords such as "new AI algorithm," "time efficiency," and "improved accuracy." The patent idea generated will then be "a new AI algorithm that achieves efficiency through automation." The user provides feedback on this idea, and the server makes improvements.

[0996] Also, when an online shopping site operator creates a description for a new product (e.g., a "smart watch"), they provide the product information (product name, features, price, brand) to the server. The server generates a prompt like this:

[0997] New Product: Smartwatch

[0998] Brand: General company name

[0999] Main features: Heart rate monitor, GPS function, waterproof

[1000] Price: 19,800 yen

[1001] Description:

[1002] Based on this prompt, the server generates a product description, which is used as the final description after the user confirms and makes any necessary corrections.

[1003] In this way, this system can streamline the patent application process and the process of generating product descriptions for online shopping sites, significantly reducing the burden on users.

[1004] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1005] Step 1:

[1006] The server receives invention-related materials (such as technical documents and emails between parties) uploaded by users from their terminals, regardless of the file format of the materials.

[1007] Input: Invention-related files

[1008] Output: Received material

[1009] Step 2:

[1010] The server analyzes the received material using a natural language processing (NLP) engine to extract important keywords and concepts. During this process, the text is tokenized through morphological analysis and keywords are extracted.

[1011] Input: Received material

[1012] Output: Extracted keywords and concepts

[1013] Step 3:

[1014] The server generates patent ideas based on the extracted keywords and concepts, and the generated ideas are generated in text format using an AI model (e.g., GPT-2).

[1015] Input: Extracted keywords and concepts

[1016] Output: Generated patent ideas

[1017] Step 4:

[1018] The server sends the generated patent ideas to the terminal and presents them to the user, who then provides feedback on the ideas.

[1019] Input: Generated patent idea

[1020] Output: User feedback

[1021] Step 5:

[1022] The server receives user feedback and uses the AI ​​model to refine the patent idea, a process that is repeated until the user is satisfied.

[1023] Input: User feedback

[1024] Output: Improved patent idea

[1025] Step 6:

[1026] The server searches a patent database to find existing patents that may conflict with the patent idea.

[1027] Input: Improved patent idea

[1028] Output: Competitive patent information

[1029] Step 7:

[1030] The server provides users with information on competing patents and suggests necessary adjustments.

[1031] Input: Competing patent information

[1032] Output: Information and suggestions provided to the user

[1033] Step 8:

[1034] The server generates patent application documents using an NLG engine based on the finalized idea.

[1035] Input: A confirmed idea

[1036] Output: Generated patent application document

[1037] Step 9:

[1038] The user uses the terminal to check the generated patent application document and sends instructions to the server to make any necessary corrections.

[1039] Input: Generated patent application document

[1040] Output: User's correction instructions

[1041] Step 10:

[1042] The server reflects the correction instructions and completes the final patent application document, which is then submitted to the Patent Office's online system.

[1043] Input: User correction instructions

[1044] Output: Final patent application document submitted to the patent office

[1045] Step 11:

[1046] Product information (such as product name, features, price, brand, etc.) is received, and a prompt sentence is created based on this to generate a product description.

[1047] Input: Product information

[1048] Output: prompt statement

[1049] Step 12:

[1050] The server uses a generative AI model (e.g., GPT-2) to generate a product description based on the prompt.

[1051] Input: prompt statement

[1052] Output: Generated product description

[1053] Step 13:

[1054] The server provides the generated product description to the user, who then reviews and makes any necessary corrections.

[1055] Input: Generated product description

[1056] Output: Product description reviewed and corrected by the user

[1057] Step 14:

[1058] The server reflects the user's confirmation and corrections and generates a final product description.

[1059] Input: User correction instructions

[1060] Output: Final product description

[1061] In this way, the system streamlines the patent application process and the product description generation process for online shopping sites.

[1062] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1063] Understood. Below, based on the scope of the claims, we have prepared a "Description of the Invention" for the invention that combines an emotion engine.

[1064] ---

[1065] This invention combines an emotion engine with a system and implementation method for streamlining intellectual property applications. This system recognizes the user's emotions during the patent idea generation and refinement process and makes adjustments based on the feedback, thereby achieving efficient and effective patent applications.

[1066] Data entry and analysis

[1067] Users use their devices to prepare and organize invention-related policy documents and emails with related parties. The devices are equipped with a means to upload these documents to the server. The server receives the uploaded data and uses a natural language processing (NLP) engine to tokenize it, perform morphological analysis, and extract important keywords and concepts.

[1068] Idea generation and refinement

[1069] The server generates hypotheses for patent ideas based on the extracted keywords and concepts. The hypotheses are presented to the user's terminal, and the user provides feedback on the presented patent ideas.

[1070] The server receives user feedback and uses the AI ​​model to refine the patent idea, which is then presented to the user again, and the process is repeated until the user is satisfied.

[1071] Utilizing the Emotion Engine

[1072] When collecting feedback, the server uses an emotion engine to recognize the user's emotions, for example, by capturing emotional data through the style and tone of the user's feedback, as well as facial and voice analysis (if required).

[1073] The emotion engine analyzes the user's emotional state, such as whether their feedback is positive or negative, flexible or strict, and adjusts how the idea is refined and presented based on the results. For example, if the user responds statistically positively, the idea will be explored further, and if the user responds negatively, a different approach will be tried.

[1074] Competitive research and document generation

[1075] Based on the patent idea identified, the server searches the patent database for existing patents that may conflict with it, reporting the results to the user and suggesting adjustments if necessary.

[1076] The server then generates a patent application document based on the finalized idea, using a natural language generation (NLG) engine to adjust the document's format and writing style, even adjusting it based on the user's emotional state.

[1077] Application Procedure

[1078] The user uses the terminal to check the generated patent application document and indicate any necessary corrections. The server reflects these correction instructions and completes the final patent application document. The server then processes this completed document for submission to the Patent Office's online system. The user monitors the application status on the terminal and provides additional information and materials as needed.

[1079] Specific examples

[1080] For example, if a user wants to apply for a patent for a new AI algorithm, they first upload their policy documents and related emails to the server. The server analyzes this information and extracts keywords such as "new AI algorithm," "time efficiency," and "improved accuracy." Based on these keywords, it generates a hypothesis: "a new AI algorithm that achieves efficiency through automation."

[1081] When users provide feedback on a proposed idea, their emotional state (e.g., positive anticipation or negative concern) is also analyzed by the emotion engine. The server uses this data to refine the idea and present it to the user again. The system also adjusts the tone and format of patent application documents, taking the user's emotional state into account.

[1082] In this way, by utilizing the emotion engine, the entire process from patent idea discovery to application processing can be made more personalized, efficient, and effective.

[1083] The processing flow will be explained below.

[1084] Step 1:

[1085] The user prepares invention-related policy documents and emails between related parties on the terminal, which then uploads the data to the server.

[1086] Step 2:

[1087] The server receives the uploaded data and then invokes a natural language processing (NLP) engine to tokenize the data and perform morphological analysis to extract important keywords and concepts.

[1088] Step 3:

[1089] The server generates hypotheses for patent ideas based on the extracted keywords and concepts, a process that provides initial idea suggestions based on similar ideas and an existing knowledge base.

[1090] Step 4:

[1091] The server presents the generated hypotheses for the patent idea to the user's terminal, which the user confirms.

[1092] Step 5:

[1093] Users can input feedback on the presented patent idea via a terminal, for example, suggesting "ways to apply this idea to a specific industry" or "ways to further improve accuracy."

[1094] Step 6:

[1095] The device sends user feedback data to a server, which analyzes the received feedback and uses AI models to refine the idea.

[1096] Step 7:

[1097] The server uses an emotion engine when collecting feedback to recognize the user's emotions, for example by analyzing the style and tone of the feedback, or facial expressions and voice (if applicable).

[1098] Step 8:

[1099] The server adjusts how the patent idea is refined and presented based on the emotional data obtained by the emotion engine. For example, if the user expresses negative emotions, it can suggest different approaches and solutions.

[1100] Step 9:

[1101] The server then presents the refined patent idea to the user again, and this process is repeated until the user is satisfied.

[1102] Step 10:

[1103] The server accesses a patent database to search for existing patents that may be competing with the patent idea, and reports the search results to the user.

[1104] Step 11:

[1105] The server automatically generates patent application documents based on the confirmed patent idea, using a natural language generation (NLG) engine to refine the document's format and writing style.

[1106] Step 12:

[1107] The server sends the generated patent application document to the user's terminal, where the user can review it and make any necessary corrections.

[1108] Step 13:

[1109] The terminal sends the user's correction instructions to the server, which then reflects the correction instructions and completes the final patent application document.

[1110] Step 14:

[1111] The server submits the completed patent application documents to the Patent Office's online system, where users can monitor the application status on their devices and provide additional information or materials as needed.

[1112] This allows systems that utilize emotion engines to make the entire process, from discovering patent ideas to filing applications, more efficient and effective.

[1113] Example 2

[1114] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1115] The traditional patent application process requires many steps, including organizing invention-related materials, generating patent ideas, collecting feedback and refining the ideas, researching competing patents, and preparing patent application documents, and is extremely time-consuming and labor-intensive. Furthermore, because the user's emotional state is not taken into consideration, the quality of feedback is often poor and ideas are often not effectively refined. This leads to a lower success rate for patent applications.

[1116] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1117] In this invention, the server includes means for receiving materials related to the invention, means for analyzing the received materials and extracting important keywords and concepts, means for generating patent ideas from the extracted information, means for receiving user feedback and improving the patent ideas, means for analyzing the user's emotional state and adjusting the method for improving and presenting the ideas based on the feedback, means for searching for competing patents based on the patent ideas, means for providing the user with information on competing patents, means for generating patent application documents, and means for submitting the generated patent application documents to the Patent Office, thereby significantly improving the efficiency of the patent application process and enabling personalized support based on the user's emotional state.

[1118] "Materials related to the invention" refers to documents and data that describe the content, background, and technical features of the invention.

[1119] A "server" is a computer system that receives, analyzes, processes, stores, and transmits data.

[1120] "Natural language processing" refers to the technology that allows computers to analyze, generate, and understand human language.

[1121] "Keywords and concepts" are important words and concepts extracted from the materials that are necessary for generating patent ideas.

[1122] A "patent idea" is a specific concept or proposal for a particular technology or invention.

[1123] "Feedback" refers to the evaluations and opinions that users give about patent ideas.

[1124] An "emotion recognition engine" is a technology for analyzing emotions from user feedback.

[1125] A "competing patent" is an existing patent that is similar to or related to the patent idea being applied for.

[1126] "Patent application documents" means official documents prepared for a patent application.

[1127] "Patent Office" refers to the government agency that accepts, examines, and registers patent applications.

[1128] An "AI model" is a machine learning model that uses artificial intelligence to generate and improve patent ideas.

[1129] A "prompt sentence" is an input sentence given to a generative AI model, based on which the AI ​​generates output.

[1130] This invention is a system aimed at streamlining the patent application process, providing comprehensive support for everything from organizing and analyzing invention-related materials to generating patent ideas, collecting and refining feedback, conducting competitive research, and preparing and submitting patent application documents. The system's hardware configuration includes a user device and a server for processing data. The software configuration includes a natural language processing engine (e.g., SpaCy), a generative AI model (e.g., GPT-3), an emotion recognition engine, a patent database search engine, and a natural language generation engine (NLG engine).

[1131] Data entry and analysis

[1132] Users use their devices to prepare invention-related policy documents and emails with stakeholders, and upload these documents to the server. The device provides a file upload function, allowing users to select PDFs, Word documents, etc. from their local directory and send them to the server. The server stores the received data and uses a natural language processing (NLP) engine to tokenize the data, perform morphological analysis, and extract important keywords and concepts.

[1133] Idea generation and feedback

[1134] The server uses a generative AI model to generate hypotheses for patent ideas based on the extracted keywords and concepts. For example, by entering a prompt to generate a patent idea for a "new AI algorithm," detailed ideas are generated. The generated ideas are displayed on the user's device. The user can provide feedback on the presented patent idea. The feedback is entered in a simple comment field and sent to the server.

[1135] Utilizing the Emotion Engine

[1136] The server analyzes the feedback provided by the user using an emotion recognition engine. It obtains the user's emotional data from the content and tone of the feedback, and, if necessary, through voice and facial expression analysis. The emotion recognition engine determines whether the feedback is positive or negative, and adjusts how the patent idea is improved and presented based on the results.

[1137] Competitive research and document generation

[1138] The server searches patent databases based on the patent idea to find competing patents. The search results are provided to the user, suggesting modifications or adjustments to the idea as needed. The server then uses a natural language generation (NLG) engine to generate the patent application document, which can automatically adjust the format and writing style of the patent document. It also adjusts based on the user's emotional state.

[1139] Application Procedure

[1140] The generated patent application document is reviewed on the user's device, and the user can input correction instructions as needed. The server reflects these instructions and completes the final patent application document. The server then processes the completed document for submission to the Patent Office's online system. The user can monitor the application status on their device and provide additional information and materials.

[1141] In this way, the system aims to consistently support and streamline the patent application process. As a specific example, when applying for a patent for a new AI algorithm, the following prompt is entered: "Generate a patent idea for a new AI algorithm that achieves efficiency through automation." Based on this prompt, the generative AI model will generate detailed ideas.

[1142] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1143] Step 1:

[1144] The user uses a device to prepare policy documents and emails related to the invention and uploads them to the server. The input is a PDF, Word document, etc., and is sent using the device's upload function. The documents are saved on the server as output.

[1145] Step 2:

[1146] The server saves the received data. The input is the file uploaded in the previous step, and the destination is the server's file system. The output is the data saved on the server.

[1147] Step 3:

[1148] The server runs a natural language processing (NLP) engine to tokenize and morphologically analyze the stored material. It uses the text data of the received material as input. Specifically, it uses an NLP engine (e.g., SpaCy) to extract nouns and verbs. The output is a list of important keywords and concepts.

[1149] Step 4:

[1150] The server uses a generative AI model to generate patent idea hypotheses based on the extracted keywords and concepts. It uses a list of keywords or concepts and a prompt (e.g., "Please generate a patent idea for a new AI algorithm") as input. The generated patent idea hypotheses are obtained as output.

[1151] Step 5:

[1152] The server sends the generated patent idea assumptions to the user's terminal and displays them. The generated patent idea assumptions are used as input and are displayed on the user's terminal as output.

[1153] Step 6:

[1154] Users submit feedback on the presented patent ideas from their devices. The system uses the user's evaluations and opinions as input, and sends the feedback entered in the comment field from the device. The feedback is sent to the server as output.

[1155] Step 7:

[1156] The server receives the feedback provided by the user and analyzes it with an emotion recognition engine. Using the feedback content as input, the emotion recognition engine determines the emotional state, whether positive or negative. The output is the emotion analysis result.

[1157] Step 8:

[1158] The server adjusts how to improve and present the patent idea based on the sentiment analysis results. It uses the sentiment analysis results and the original patent idea hypotheses as input. It uses the generative AI model again to generate the improved patent idea. The improved patent idea is obtained as output.

[1159] Step 9:

[1160] The server presents the improved patent idea to the user again and repeats the same feedback process, using the improved patent idea as input and presented to the user's terminal as output.

[1161] Step 10:

[1162] The server searches a patent database for competing patents based on the confirmed patent idea. It uses keywords and concepts from the confirmed patent idea as input and sends a search query to the patent database. The output is a list of competing patents.

[1163] Step 11:

[1164] The server provides the user with information on competing patents. It uses a list of competing patents obtained from a patent database as input and reports it to the user. It displays the competing patent information on a terminal as output.

[1165] Step 12:

[1166] The server uses a natural language generation (NLG) engine to generate a patent application document based on the finalized patent idea. Using the content of the finalized patent idea as input, the NLG engine generates the format and writing style of the document. The patent application document is created as output.

[1167] Step 13:

[1168] The user uses a terminal to check the generated patent application document and instructs on necessary corrections. The patent application document is used as input, and correction instructions are entered in the comment field. The correction instructions are sent to the server as output.

[1169] Step 14:

[1170] The server reflects the correction instructions and completes the final patent application document. The server uses the user's correction instructions as input and updates the patent application document. The final patent application document is completed as output.

[1171] Step 15:

[1172] The server submits the completed patent application to the Patent Office's online system. It uses the final patent application as input and sends the data to the online system. The output is a confirmation of receipt from the Patent Office.

[1173] Step 16:

[1174] The user monitors the application status on the terminal and provides additional information and materials as needed. The user uses notifications from the Patent Office's online system as input and submits the additional information and materials from the terminal. The additional information and materials are sent to the Patent Office as output.

[1175] (Application example 2)

[1176] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1177] The patent application process is complex and requires a lot of time and effort. Furthermore, efficiently incorporating user feedback and generating optimal patent ideas is a difficult problem. Furthermore, existing systems have not been able to utilize feedback that takes into account the user's emotional state. This results in a lack of improvement in the efficiency and quality of patent applications, and makes searching for competing patent information and preparing application documents cumbersome. Therefore, a system that solves these issues, streamlines the patent application process, and improves user satisfaction is needed.

[1178] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving materials related to the invention, means for analyzing the received materials and extracting important keywords and concepts, means for generating a patent idea from the extracted information, means for receiving user feedback and improving the patent idea, means for analyzing the user's emotional state at the time of feedback, means for adjusting the patent idea according to the analyzed emotional state, means for searching for competing patents based on the patent idea, means for providing the user with information on competing patents, means for generating patent application documents, and means for submitting the generated patent application documents to the Patent Office. This enables the patent application process to be carried out efficiently and effectively, and improves user satisfaction.

[1179] "Materials related to the invention" refers to information and documents necessary for filing a patent application, including relevant technical documents, research data, email content, etc.

[1180] "Means for receiving" refers to the function or method by which the server receives materials related to the invention from the user and stores them in storage.

[1181] "Means for analysis" refers to the functions and methods for processing received materials and extracting important keywords and concepts using natural language processing technology.

[1182] "Extracted information" refers to keywords and concepts obtained from the analyzed materials, and is the basis for generating patent ideas.

[1183] A "means for generating patent ideas" is a function or method for automatically generating new patent hypotheses or proposals based on the extracted information.

[1184] "User Feedback" means any opinion, comment, or evaluation provided by a user regarding a patent idea.

[1185] "Means for improving the patent idea" refers to the functions and methods for further improving and optimizing the patent idea based on the feedback received.

[1186] "Means for analyzing emotional state" refers to techniques or methods for analyzing the user's text, voice, or facial expressions during feedback to understand and classify their emotions.

[1187] "Means for adjusting patent ideas" refer to functions and methods for changing and optimizing the content and presentation of patent ideas according to the user's emotional state.

[1188] The "means for searching competing patents" refers to a function or method for searching a patent database for existing patents related to the generated patent idea.

[1189] "Competitive Patent Information" is detailed data about existing patents that have been searched and is a reference provided to the user.

[1190] The "means for generating patent application documents" refers to a function or method for automatically creating documents required for a patent application based on a confirmed patent idea.

[1191] "Means for submission" refers to the functionality or method for submitting the generated patent application documents to the Patent Office online or offline.

[1192] MODE FOR CARRYING OUT THE INVENTION

[1193] The embodiments of the present invention will be described in detail below.

[1194] System Overview

[1195] The system of the present invention is equipped with a series of means for streamlining the patent application process. The system is mainly composed of three elements: a server, a terminal, and a user. The server receives and analyzes invention-related materials and uses that information to generate and refine patent ideas. The terminal functions as an interface for users to provide feedback and upload materials.

[1196] Hardware and software used

[1197] 1. Hardware:

[1198] Server: High-performance data processing server

[1199] Device: Smartphone, smart glasses, or computer

[1200] 2. Software:

[1201] Natural Language Processing Engine (TextBlob)

[1202] Sentiment analysis engine (Hugging Face transformers library)

[1203] Database systems (e.g. PostgreSQL)

[1204] Patent database search function

[1205] Natural Language Generation Engine (Natural Language Model)

[1206] Specific processing flow

[1207] First, the user uploads documents related to the invention using a terminal. The server stores the received documents in storage. A natural language processing engine is used to tokenize and analyze the documents to extract important keywords and concepts. Based on this extracted information, a patent idea is generated.

[1208] The generated patent ideas are presented to the user's device. The user provides feedback on the presented ideas. During the feedback process, the user's emotional state is analyzed using an emotion analysis engine. This allows the idea to be adjusted according to the user's emotional state.

[1209] Once a patent idea is finalized, the server searches the patent database for relevant competing patents, and provides the competing patent information to the user, allowing them to adjust the idea as needed.

[1210] Finally, the server generates a patent application document based on the confirmed patent idea, which can then be submitted to the patent office online or offline. Users can monitor the application status through their devices and provide additional information and materials as needed.

[1211] Examples of concrete examples and prompts

[1212] For example, if a user wants to apply for a patent for a new voice recognition technology, they first upload technical documents and related emails from their device to the server. The server analyzes this information and extracts keywords such as "voice recognition technology," "improved accuracy," and "real-time processing." Based on these keywords, a patent idea for "a new algorithm to improve the accuracy of voice recognition" is generated. The user then provides feedback on this idea, saying, "This idea is interesting, but further details need to be specified."

[1213] Example prompt for a generative AI model:

[1214] User feedback: "This is a great idea, but we should also consider how to improve the accuracy."

[1215] In this way, the system of the present invention can streamline the entire process from the generation of a patent idea to the filing of an application, and can quickly reflect user feedback.

[1216] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1217] Step 1:

[1218] The user uploads documents related to the invention using a terminal. The input includes files such as technical documents and related emails. This document is sent to the server, which then stores the received documents in storage. The output is the saved document file. Specifically, the user selects the documents using the file upload interface and presses the upload button, which sends the documents to the server.

[1219] Step 2:

[1220] The server analyzes the uploaded materials using a natural language processing engine. The material file saved in step 1 is used as input. The analysis process tokenizes the materials and extracts important keywords and concepts. The output is the extracted keywords and concepts. Specifically, the TextBlob library is used to tokenize the documents and perform morphological analysis.

[1221] Step 3:

[1222] The server generates patent ideas based on the extracted keywords and concepts. The input includes the keywords and concepts extracted in step 2. An AI model is used to generate patent ideas based on this information. The output is the generated patent idea. Specifically, the generative AI model is used to create patent ideas on themes such as "new algorithms" and "efficiency."

[1223] Step 4:

[1224] The server presents the generated patent idea to the user's terminal. The patent idea created in step 3 is used as input. The user provides feedback on the presented idea. The output is the user's feedback. Specifically, the server displays the patent idea on the user interface and provides a feedback input field.

[1225] Step 5:

[1226] The server receives the user's feedback and analyzes the feedback content using a sentiment analysis engine. The feedback received in step 4 is used as input. The sentiment analysis determines the user's emotional state (positive, negative, etc.). The output is the analyzed emotional data. Specifically, the server utilizes the Hugging Face transformers library to perform sentiment analysis on the feedback text.

[1227] Step 6:

[1228] The server adjusts the patent idea based on the analyzed emotional state. The input includes the emotional data obtained in step 5 and the patent idea generated in step 3. The idea is refined according to the emotional state and presented to the user again. The output is the adjusted patent idea. Specifically, the server evaluates the emotional data and updates the content and presentation method of the patent idea.

[1229] Step 7:

[1230] The server searches the patent database based on the confirmed patent idea to find related competing patents. The input includes the patent idea confirmed in step 6. The server outputs the competing patent information obtained as a search result. Specifically, it uses the patent database search function to extract related patents from the database.

[1231] Step 8:

[1232] The server provides the searched competing patent information to the user and generates a patent application document. The input includes the competing patent information obtained in step 7 and the patent idea confirmed in step 6. The output is the generated patent application document. Specifically, the server uses a natural language generation engine to automatically create the patent application document.

[1233] Step 9:

[1234] The server submits the generated patent application document to the Patent Office. The patent application document created in step 8 is used as input. The document is submitted to the Patent Office online or offline, and then confirmed. The output is the acceptance status of the patent application. Specifically, the document is uploaded through the Patent Office's online system, and the application number, etc. are confirmed.

[1235] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1236] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1237] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1238] [Fourth embodiment]

[1239] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1240] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1241] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1242] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1243] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1244] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1245] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1246] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1247] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1248] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1249] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1250] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1251] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1252] Understood. I have prepared the following "Mode for carrying out the invention" based on the scope of the claims.

[1253] ---

[1254] This invention relates to a system and method for efficiently filing intellectual property applications. This system generates patent ideas and files patent applications through multiple steps, with a server, a terminal, and a user playing their respective roles.

[1255] Data entry and analysis

[1256] The user uses the terminal to prepare and organize policy documents and emails between related parties related to the invention. The terminal is equipped with a means to upload these documents to the server. The server receives the uploaded data and analyzes it using a natural language processing (NLP) engine.

[1257] During the analysis process, the server tokenizes the received data and performs morphological analysis to extract important keywords and concepts, such as "AI algorithm," "time efficiency," and "improved accuracy."

[1258] Idea generation and refinement

[1259] The server generates hypotheses for patent ideas based on the extracted keywords and concepts. The hypotheses are then presented to the user's device. The user can then provide feedback on the proposed tentative patent ideas, such as adding "methods for further refinement" or "applications to specific industries."

[1260] The server receives user feedback and refines the patent idea using an AI model. The improved idea is then presented to the user again, and this process is repeated until the user is satisfied.

[1261] Competitive research and document generation

[1262] After the idea is confirmed, the server searches the patent database for existing patents that may conflict with the patent idea. The results of the conflict search are reported to the user and necessary adjustments are proposed.

[1263] The server generates a patent application document based on the finalized idea. In this process, the server uses a natural language generation (NLG) engine to create a document in accordance with the patent application format.

[1264] Application Procedure

[1265] The user uses a terminal to check the generated patent application document and instruct the server on any necessary corrections. The server reflects the correction instructions and completes the final patent application document. The server then processes the completed document for submission to the Patent Office's online system.

[1266] Specific examples

[1267] For example, if a user wants to apply for a patent for a new AI algorithm, they first upload their policy documents and related emails to the server. The server analyzes these and extracts keywords such as "new AI algorithm," "time efficiency," and "improved accuracy." Based on these keywords, the server generates a hypothesis for the patent idea: "A new AI algorithm that achieves efficiency through automation." Based on the user's feedback, the server refines and optimizes the idea.

[1268] The server then searches the patent database for competing patents and reports the results to the user. Based on the finalized idea, the server generates a patent application document, which is then submitted to the patent office after the user has confirmed and revised it.

[1269] In this way, the present invention is a system that enables the entire process from the discovery of a patent idea to the application procedure to be carried out efficiently and effectively.

[1270] The processing flow will be explained below.

[1271] Step 1:

[1272] The user prepares invention-related policy documents and emails between related parties on the terminal, which then uploads the data to the server.

[1273] Step 2:

[1274] The server receives the uploaded data and then invokes a natural language processing (NLP) engine to tokenize the data and perform morphological analysis to extract important keywords and concepts.

[1275] Step 3:

[1276] The server generates hypotheses for patent ideas based on the extracted keywords and concepts, a process that provides initial idea suggestions based on similar ideas and an existing knowledge base.

[1277] Step 4:

[1278] The server presents the generated hypotheses for the patent idea to the user's terminal, which the user confirms.

[1279] Step 5:

[1280] Users can input feedback on the presented patent idea via a terminal, for example, suggesting "ways to apply this idea to a specific industry" or "ways to further improve accuracy."

[1281] Step 6:

[1282] The device sends user feedback data to a server, which analyzes the received feedback and uses AI models to refine the idea.

[1283] Step 7:

[1284] The server then presents the refined patent idea to the user again, and this process is repeated until the user is satisfied with the result.

[1285] Step 8:

[1286] The server accesses a patent database to search for existing patents that may be competing with the patent idea, and reports the search results to the user.

[1287] Step 9:

[1288] The server automatically generates patent application documents based on the confirmed patent idea, using a natural language generation (NLG) engine to refine the document's format and writing style.

[1289] Step 10:

[1290] The user checks the patent application document generated on the terminal and instructs the terminal to make any necessary corrections, which are then sent to the server.

[1291] Step 11:

[1292] The server reflects the user's correction instructions and finally completes the patent application document.

[1293] Step 12:

[1294] The server submits the completed patent application to the Patent Office's online system, where users can monitor the application status and provide additional information or materials as needed.

[1295] This streamlines the entire process from discovering a patent idea to filing an application.

[1296] Example 1

[1297] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1298] The current intellectual property application process requires a lot of time and effort, is inefficient in terms of patent idea generation, competitive research, and application document preparation, and places a heavy burden on users. This problem makes it difficult for inventors to protect their new ideas in a timely manner, which can result in a loss of competitiveness. Furthermore, existing systems rely on manual processes for analyzing information and refining ideas, which risks reducing the accuracy and speed of the work. To solve these issues, there is a need for a system that can automate the entire intellectual property application process efficiently and effectively.

[1299] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1300] In this invention, the server includes means for receiving digital documents, means for analyzing the received documents and extracting important information, means for generating intellectual property ideas from the extracted information, means for receiving user opinions and improving the intellectual property ideas, means for searching existing intellectual property based on the intellectual property ideas, means for presenting search results to the user, means for generating intellectual property application documents, and means for submitting the generated intellectual property application documents, thereby automating the entire intellectual property application process and enabling rapid and accurate patent idea generation, competitive research, and application document preparation and submission.

[1301] A "digital document" is a document containing information stored in electronic form that can be viewed, edited, or transmitted using a computer or other electronic device.

[1302] "Important information" refers to keywords and concepts contained within digital documents that are key to patent idea generation and competitive research.

[1303] "Intellectual property idea" refers to a concept or proposal for an invention or technical solution that is the subject of a patent application.

[1304] "User Feedback" means feedback, comments, or suggestions for correction provided by a User regarding an Intellectual Property Idea.

[1305] "Existing intellectual property" refers to technologies and inventions that have already been patented and are publicly available and registered in patent databases, etc.

[1306] "Search results" refers to the list of relevant information and patents that are obtained when searching existing intellectual property.

[1307] "Intellectual Property Application Document" refers to the official patent application document submitted to the Patent Office, which contains details of the invention and its technical features.

[1308] This invention relates to a system and method for efficiently filing intellectual property applications. In this system, a server, a terminal, and a user each play their respective roles, and the system generates patent ideas and files patent applications through multiple steps.

[1309] Entering and Submitting Data

[1310] The user prepares and organizes policy documents and emails between related parties related to the invention. The user uploads these documents to the terminal. The terminal has a means to send these documents to the server.

[1311] Data analysis

[1312] The server receives the uploaded digital document. It then analyzes the received digital document using a natural language processing (NLP) engine to extract important information. During the analysis process, the server tokenizes the received data and performs morphological analysis to extract important keywords and concepts. For example, keywords such as "new AI algorithm," "time efficiency," and "improved accuracy" are extracted.

[1313] Idea generation

[1314] The server generates hypotheses for intellectual property ideas based on the extracted keywords and concepts. The hypotheses are then presented to the user's device. For example, a "patent idea for a technology that uses a new AI algorithm to improve time efficiency and accuracy" might be generated.

[1315] Brushing up ideas

[1316] Users provide feedback on the proposed tentative patent idea, such as adding "further refinement methods" or "applications to specific industries." The server receives the user's feedback and refines the intellectual property idea using a generative AI model. The improved idea is presented to the user again, and this process is repeated until the user is satisfied.

[1317] Competitive Research

[1318] After the intellectual property idea is confirmed, the server will refer to the patent database to search for existing intellectual property that may conflict with the intellectual property idea, and report the results of the conflict search to the user and propose necessary adjustments.

[1319] Generate intellectual property application documents

[1320] The server generates intellectual property application documents based on the finalized idea. In this process, the server uses a natural language generation (NLG) engine to create documents in accordance with the patent application format.

[1321] Application Procedure

[1322] The user checks the generated patent application document on a terminal and instructs the server on any necessary corrections. The server reflects the correction instructions and completes the final intellectual property application document. The server then processes the completed document for submission to the Patent Office's online system.

[1323] Specific examples

[1324] For example, if a user wants to apply for a patent for a new AI algorithm, they first upload their policy documents and related emails to the server. The server analyzes these and extracts keywords such as "new AI algorithm," "time efficiency," and "improved accuracy." Based on these keywords, the server generates a hypothesis for the patent idea: "A new AI algorithm that achieves efficiency through automation." Based on the user's feedback, the server refines and optimizes the idea.

[1325] Specific examples of input prompts for generative AI models

[1326] "I would like to apply for a patent for a new AI algorithm. I would like you to generate patent ideas based on policy documents."

[1327] "Please tell me the steps to refine my patent idea for improving efficiency and accuracy."

[1328] In this way, the present invention is a system that enables the entire process from the discovery of a patent idea to the application procedure to be carried out efficiently and effectively.

[1329] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1330] Step 1:

[1331] Entering and Submitting Data

[1332] The user prepares policy documents and emails between stakeholders related to the invention. Specifically, the user saves data, including research papers and communication records with project members, on the device. Next, the user selects these documents through a dedicated app or web portal and presses the "Upload" button. The device encodes the selected data and sends it to the specified endpoint on the server via an HTTP POST request.

[1333] Input: Policy documents and emails related to inventions

[1334] Output: Data sent to the server

[1335] Step 2:

[1336] Data reception and analysis

[1337] The server receives the data sent from the device. It then analyzes the received data using a natural language processing (NLP) engine. Specifically, the server tokenizes the data and performs morphological analysis. This extracts important keywords and concepts, such as "AI algorithm," "time efficiency," and "accuracy improvement."

[1338] Input: Data sent to the server

[1339] Output: Extracted keywords and concepts

[1340] Step 3:

[1341] Idea generation

[1342] The server generates intellectual property ideas based on the extracted keywords and concepts. In this process, a generative AI model is used to create hypotheses for patent ideas. For example, a "patent idea for a technology that uses a new AI algorithm to improve time efficiency and accuracy" is generated. The generated idea is then sent to the user's device.

[1343] Input: Extracted keywords and concepts

[1344] Output: Generated intellectual property ideas

[1345] Step 4:

[1346] Brushing up ideas

[1347] Users provide feedback on the proposed tentative patent idea. For example, they can enter comments to add "methods for further improvement" or "application to a specific industry." The server receives the user's feedback and refines the idea using a generative AI model. The improved idea is then presented to the user again.

[1348] Input: User feedback

[1349] Output: Improved intellectual property ideas

[1350] Step 5:

[1351] Competitive research

[1352] The server searches patent databases based on the confirmed intellectual property idea, and references existing patent databases to search for existing intellectual property that may conflict with the intellectual property idea. The search results are reported to the user, and necessary adjustments are suggested. Specifically, the server issues queries such as keyword searches and concept matching to patent databases.

[1353] Input: Confirmed intellectual property idea

[1354] Output: List of competing patents

[1355] Step 6:

[1356] Generate application documents

[1357] The server then generates an intellectual property application document based on the finalized idea. During this process, the server uses a natural language generation (NLG) engine to create a document in a patent application format. Specifically, the document is generated in a format such as, "This invention relates to a method for improving the efficiency of specific operations using a new AI algorithm."

[1358] Input: Confirmed intellectual property idea

[1359] Output: Intellectual property application document

[1360] Step 7:

[1361] Application Procedure

[1362] The user checks the generated patent application document using a terminal and instructs the server on any necessary corrections. The server reflects the correction instructions and completes the final intellectual property application document. The server then submits the completed document to the Patent Office's online system. During this process, the user previews the patent application document and directly inputs corrections using a markup tool. The server also receives the user's correction instructions and regenerates the updated document.

[1363] Input: Finalized intellectual property application documents

[1364] Output: Submitted intellectual property application documents

[1365] In this way, the system can efficiently carry out the entire process from patent idea generation to application procedures.

[1366] (Application example 1)

[1367] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1368] The patent application process is extremely complex and time-consuming, resulting in inefficiencies in steps such as extracting important keywords and concepts, generating patent ideas, conducting competitive research, and preparing patent application documents. Furthermore, generating product descriptions quickly and effectively on online shopping sites requires detailed manual writing, placing a significant burden on operators. A system that solves these problems is needed.

[1369] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1370] In this invention, the server includes means for receiving materials related to the invention, means for analyzing the received materials and extracting important keywords and concepts, means for generating patent ideas from the extracted information, means for receiving user feedback and improving the patent ideas, means for searching for competing patents based on the patent ideas, means for providing information on competing patents to the user, means for generating patent application documents, means for submitting the generated patent application documents to the Patent Office, means for receiving product information and generating product descriptions, and means for the user to confirm and modify the generated product descriptions. This improves the efficiency of the patent application process and enables the rapid generation of product descriptions on online shopping sites.

[1371] "Materials related to the invention" refers to data including technical documents required for patent applications, emails between parties, and other related information.

[1372] "Analysis" refers to the process of using natural language processing (NLP) technology to understand the content of received materials and extract important keywords and concepts.

[1373] "Keywords and concepts" are words and ideas that are considered important in generating patent ideas and preparing patent application documents.

[1374] A "patent idea" is a technical idea that is the subject of a patent application and is generated based on the extracted keywords and concepts.

[1375] "Feedback" refers to opinions and suggestions for improvement that users provide to the system.

[1376] A "competing patent" refers to an existing patent registered in a patent database that is similar to the generated patent idea.

[1377] "Patent application document" means a document prepared in the form required to apply for a patent.

[1378] "Patent Office" refers to the public institution that accepts and reviews patent applications.

[1379] "Product information" refers to information such as the name, features, price, and brand of the product sold on the online shopping site.

[1380] A "product description" is a description of a product that is posted on an online shopping site and is text that conveys the appeal of the product to users.

[1381] This invention relates to a system and its implementation method for improving the efficiency of the patent application process and automatically generating product descriptions for online shopping sites. This system is mainly composed of three components: a server, a terminal, and a user.

[1382] Server Roles

[1383] The server has the following features:

[1384] 1. Document receiving means: This has the function of receiving invention-related documents uploaded by users, including technical documents and emails between related parties.

[1385] 2. Analysis method: The received material is analyzed using a natural language processing (NLP) engine to extract important keywords and concepts. This process is carried out through morphological analysis.

[1386] 3. Patent idea generation means: Patent ideas are generated based on the extracted keywords and concepts. The generated ideas are presented to the user.

[1387] 4. Improve method: Receive user feedback and improve the patent idea using an AI model (e.g., GPT-2). This process is repeated until the user is satisfied.

[1388] 5. Competing patent search tool: Consult patent databases to search for existing patents that may compete with the patent idea.

[1389] 6. Information provision means: Provide users with information on competing patents and suggest necessary adjustments.

[1390] 7. Patent application document generation method: A patent application document is generated based on the confirmed idea. An NLG (Natural Language Generation) engine is used in this process.

[1391] 8. Patent Office Submission Method: Submit the final patent application documents to the Patent Office's online system.

[1392] Furthermore, the server also comprises the following means, which are of particular importance in the application of the invention:

[1393] 1. Product information receiving means: Receives product information (e.g., product name, features, price, brand, etc.) from the online shopping site.

[1394] 2. Product description generation method: Generate product descriptions based on the received product information. Generate text using an AI model (e.g., GPT-2).

[1395] 3. User confirmation and correction: Provides a function for users to confirm the generated product description and correct it if necessary.

[1396] Device Role

[1397] The terminal provides an interface with the user. The user uses the terminal to upload invention-related materials and product information to the server. The terminal also presents ideas sent from the server and generated product descriptions to the user and receives feedback.

[1398] User Roles

[1399] The user's role is to provide documents and product information to the server through the terminal, and also to provide feedback on patent ideas and product descriptions provided by the server, and to give instructions for necessary improvements.

[1400] Specific examples

[1401] For example, if a user wants to apply for a patent for a new AI algorithm, they upload technical documents and related emails to the server. The server analyzes these and extracts keywords such as "new AI algorithm," "time efficiency," and "improved accuracy." The patent idea generated will then be "a new AI algorithm that achieves efficiency through automation." The user provides feedback on this idea, and the server makes improvements.

[1402] Also, when an online shopping site operator creates a description for a new product (e.g., a "smart watch"), they provide the product information (product name, features, price, brand) to the server. The server generates a prompt like this:

[1403] New Product: Smartwatch

[1404] Brand: General company name

[1405] Main features: Heart rate monitor, GPS function, waterproof

[1406] Price: 19,800 yen

[1407] Description:

[1408] Based on this prompt, the server generates a product description, which is used as the final description after the user confirms and makes any necessary corrections.

[1409] In this way, this system can streamline the patent application process and the process of generating product descriptions for online shopping sites, significantly reducing the burden on users.

[1410] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1411] Step 1:

[1412] The server receives invention-related materials (such as technical documents and emails between parties) uploaded by users from their terminals, regardless of the file format of the materials.

[1413] Input: Invention-related files

[1414] Output: Received material

[1415] Step 2:

[1416] The server analyzes the received material using a natural language processing (NLP) engine to extract important keywords and concepts. During this process, the text is tokenized through morphological analysis and keywords are extracted.

[1417] Input: Received material

[1418] Output: Extracted keywords and concepts

[1419] Step 3:

[1420] The server generates patent ideas based on the extracted keywords and concepts, and the generated ideas are generated in text format using an AI model (e.g., GPT-2).

[1421] Input: Extracted keywords and concepts

[1422] Output: Generated patent ideas

[1423] Step 4:

[1424] The server sends the generated patent ideas to the terminal and presents them to the user, who then provides feedback on the ideas.

[1425] Input: Generated patent idea

[1426] Output: User feedback

[1427] Step 5:

[1428] The server receives user feedback and uses the AI ​​model to refine the patent idea, a process that is repeated until the user is satisfied.

[1429] Input: User feedback

[1430] Output: Improved patent idea

[1431] Step 6:

[1432] The server searches a patent database to find existing patents that may conflict with the patent idea.

[1433] Input: Improved patent idea

[1434] Output: Competitive patent information

[1435] Step 7:

[1436] The server provides users with information on competing patents and suggests necessary adjustments.

[1437] Input: Competing patent information

[1438] Output: Information and suggestions provided to the user

[1439] Step 8:

[1440] The server generates patent application documents using an NLG engine based on the finalized idea.

[1441] Input: A confirmed idea

[1442] Output: Generated patent application document

[1443] Step 9:

[1444] The user uses the terminal to check the generated patent application document and sends instructions to the server to make any necessary corrections.

[1445] Input: Generated patent application document

[1446] Output: User's correction instructions

[1447] Step 10:

[1448] The server reflects the correction instructions and completes the final patent application document, which is then submitted to the Patent Office's online system.

[1449] Input: User correction instructions

[1450] Output: Final patent application document submitted to the patent office

[1451] Step 11:

[1452] Product information (such as product name, features, price, brand, etc.) is received, and a prompt sentence is created based on this to generate a product description.

[1453] Input: Product information

[1454] Output: prompt statement

[1455] Step 12:

[1456] The server uses a generative AI model (e.g., GPT-2) to generate a product description based on the prompt.

[1457] Input: prompt statement

[1458] Output: Generated product description

[1459] Step 13:

[1460] The server provides the generated product description to the user, who then reviews and makes any necessary corrections.

[1461] Input: Generated product description

[1462] Output: Product description reviewed and corrected by the user

[1463] Step 14:

[1464] The server reflects the user's confirmation and corrections and generates a final product description.

[1465] Input: User correction instructions

[1466] Output: Final product description

[1467] In this way, the system streamlines the patent application process and the product description generation process for online shopping sites.

[1468] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1469] Understood. Below, based on the scope of the claims, we have prepared a "Description of the Invention" for the invention that combines an emotion engine.

[1470] ---

[1471] This invention combines an emotion engine with a system and implementation method for streamlining intellectual property applications. This system recognizes the user's emotions during the patent idea generation and refinement process and makes adjustments based on the feedback, thereby achieving efficient and effective patent applications.

[1472] Data entry and analysis

[1473] Users use their devices to prepare and organize invention-related policy documents and emails with related parties. The devices are equipped with a means to upload these documents to the server. The server receives the uploaded data and uses a natural language processing (NLP) engine to tokenize it, perform morphological analysis, and extract important keywords and concepts.

[1474] Idea generation and refinement

[1475] The server generates hypotheses for patent ideas based on the extracted keywords and concepts. The hypotheses are presented to the user's terminal, and the user provides feedback on the presented patent ideas.

[1476] The server receives user feedback and uses the AI ​​model to refine the patent idea, which is then presented to the user again, and the process is repeated until the user is satisfied.

[1477] Utilizing the Emotion Engine

[1478] When collecting feedback, the server uses an emotion engine to recognize the user's emotions, for example, by capturing emotional data through the style and tone of the user's feedback, as well as facial and voice analysis (if required).

[1479] The emotion engine analyzes the user's emotional state, such as whether their feedback is positive or negative, flexible or strict, and adjusts how the idea is refined and presented based on the results. For example, if the user responds statistically positively, the idea will be explored further, and if the user responds negatively, a different approach will be tried.

[1480] Competitive research and document generation

[1481] Based on the patent idea identified, the server searches the patent database for existing patents that may conflict with it, reporting the results to the user and suggesting adjustments if necessary.

[1482] The server then generates a patent application document based on the finalized idea, using a natural language generation (NLG) engine to adjust the document's format and writing style, even adjusting it based on the user's emotional state.

[1483] Application Procedure

[1484] The user uses the terminal to check the generated patent application document and indicate any necessary corrections. The server reflects these correction instructions and completes the final patent application document. The server then processes this completed document for submission to the Patent Office's online system. The user monitors the application status on the terminal and provides additional information and materials as needed.

[1485] Specific examples

[1486] For example, if a user wants to apply for a patent for a new AI algorithm, they first upload their policy documents and related emails to the server. The server analyzes this information and extracts keywords such as "new AI algorithm," "time efficiency," and "improved accuracy." Based on these keywords, it generates a hypothesis: "a new AI algorithm that achieves efficiency through automation."

[1487] When users provide feedback on a proposed idea, their emotional state (e.g., positive anticipation or negative concern) is also analyzed by the emotion engine. The server uses this data to refine the idea and present it to the user again. The system also adjusts the tone and format of patent application documents, taking the user's emotional state into account.

[1488] In this way, by utilizing the emotion engine, the entire process from patent idea discovery to application processing can be made more personalized, efficient, and effective.

[1489] The processing flow will be explained below.

[1490] Step 1:

[1491] The user prepares invention-related policy documents and emails between related parties on the terminal, which then uploads the data to the server.

[1492] Step 2:

[1493] The server receives the uploaded data and then invokes a natural language processing (NLP) engine to tokenize the data and perform morphological analysis to extract important keywords and concepts.

[1494] Step 3:

[1495] The server generates hypotheses for patent ideas based on the extracted keywords and concepts, a process that provides initial idea suggestions based on similar ideas and an existing knowledge base.

[1496] Step 4:

[1497] The server presents the generated hypotheses for the patent idea to the user's terminal, which the user confirms.

[1498] Step 5:

[1499] Users can input feedback on the presented patent idea via a terminal, for example, suggesting "ways to apply this idea to a specific industry" or "ways to further improve accuracy."

[1500] Step 6:

[1501] The device sends user feedback data to a server, which analyzes the received feedback and uses AI models to refine the idea.

[1502] Step 7:

[1503] The server uses an emotion engine when collecting feedback to recognize the user's emotions, for example by analyzing the style and tone of the feedback, or facial expressions and voice (if applicable).

[1504] Step 8:

[1505] The server adjusts how the patent idea is refined and presented based on the emotional data obtained by the emotion engine. For example, if the user expresses negative emotions, it can suggest different approaches and solutions.

[1506] Step 9:

[1507] The server then presents the refined patent idea to the user again, and this process is repeated until the user is satisfied.

[1508] Step 10:

[1509] The server accesses a patent database to search for existing patents that may be competing with the patent idea, and reports the search results to the user.

[1510] Step 11:

[1511] The server automatically generates patent application documents based on the confirmed patent idea, using a natural language generation (NLG) engine to refine the document's format and writing style.

[1512] Step 12:

[1513] The server sends the generated patent application document to the user's terminal, where the user can review it and make any necessary corrections.

[1514] Step 13:

[1515] The terminal sends the user's correction instructions to the server, which then reflects the correction instructions and completes the final patent application document.

[1516] Step 14:

[1517] The server submits the completed patent application documents to the Patent Office's online system, where users can monitor the application status on their devices and provide additional information or materials as needed.

[1518] This allows systems that utilize emotion engines to make the entire process, from discovering patent ideas to filing applications, more efficient and effective.

[1519] Example 2

[1520] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1521] The traditional patent application process requires many steps, including organizing invention-related materials, generating patent ideas, collecting feedback and refining the ideas, researching competing patents, and preparing patent application documents, and is extremely time-consuming and labor-intensive. Furthermore, because the user's emotional state is not taken into consideration, the quality of feedback is often poor and ideas are often not effectively refined. This leads to a lower success rate for patent applications.

[1522] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1523] In this invention, the server includes means for receiving materials related to the invention, means for analyzing the received materials and extracting important keywords and concepts, means for generating patent ideas from the extracted information, means for receiving user feedback and improving the patent ideas, means for analyzing the user's emotional state and adjusting the method for improving and presenting the ideas based on the feedback, means for searching for competing patents based on the patent ideas, means for providing the user with information on competing patents, means for generating patent application documents, and means for submitting the generated patent application documents to the Patent Office, thereby significantly improving the efficiency of the patent application process and enabling personalized support based on the user's emotional state.

[1524] "Materials related to the invention" refers to documents and data that describe the content, background, and technical features of the invention.

[1525] A "server" is a computer system that receives, analyzes, processes, stores, and transmits data.

[1526] "Natural language processing" refers to the technology that allows computers to analyze, generate, and understand human language.

[1527] "Keywords and concepts" are important words and concepts extracted from the materials that are necessary for generating patent ideas.

[1528] A "patent idea" is a specific concept or proposal for a particular technology or invention.

[1529] "Feedback" refers to the evaluations and opinions that users give about patent ideas.

[1530] An "emotion recognition engine" is a technology for analyzing emotions from user feedback.

[1531] A "competing patent" is an existing patent that is similar to or related to the patent idea being applied for.

[1532] "Patent application documents" means official documents prepared for a patent application.

[1533] "Patent Office" refers to the government agency that accepts, examines, and registers patent applications.

[1534] An "AI model" is a machine learning model that uses artificial intelligence to generate and improve patent ideas.

[1535] A "prompt sentence" is an input sentence given to a generative AI model, based on which the AI ​​generates output.

[1536] This invention is a system aimed at streamlining the patent application process, providing comprehensive support for everything from organizing and analyzing invention-related materials to generating patent ideas, collecting and refining feedback, conducting competitive research, and preparing and submitting patent application documents. The system's hardware configuration includes a user device and a server for processing data. The software configuration includes a natural language processing engine (e.g., SpaCy), a generative AI model (e.g., GPT-3), an emotion recognition engine, a patent database search engine, and a natural language generation engine (NLG engine).

[1537] Data entry and analysis

[1538] Users use their devices to prepare invention-related policy documents and emails with stakeholders, and upload these documents to the server. The device provides a file upload function, allowing users to select PDFs, Word documents, etc. from their local directory and send them to the server. The server stores the received data and uses a natural language processing (NLP) engine to tokenize the data, perform morphological analysis, and extract important keywords and concepts.

[1539] Idea generation and feedback

[1540] The server uses a generative AI model to generate hypotheses for patent ideas based on the extracted keywords and concepts. For example, by entering a prompt to generate a patent idea for a "new AI algorithm," detailed ideas are generated. The generated ideas are displayed on the user's device. The user can provide feedback on the presented patent idea. The feedback is entered in a simple comment field and sent to the server.

[1541] Utilizing the Emotion Engine

[1542] The server analyzes the feedback provided by the user using an emotion recognition engine. It obtains the user's emotional data from the content and tone of the feedback, and, if necessary, through voice and facial expression analysis. The emotion recognition engine determines whether the feedback is positive or negative, and adjusts how the patent idea is improved and presented based on the results.

[1543] Competitive research and document generation

[1544] The server searches patent databases based on the patent idea to find competing patents. The search results are provided to the user, suggesting modifications or adjustments to the idea as needed. The server then uses a natural language generation (NLG) engine to generate the patent application document, which can automatically adjust the format and writing style of the patent document. It also adjusts based on the user's emotional state.

[1545] Application Procedure

[1546] The generated patent application document is reviewed on the user's device, and the user can input correction instructions as needed. The server reflects these instructions and completes the final patent application document. The server then processes the completed document for submission to the Patent Office's online system. The user can monitor the application status on their device and provide additional information and materials.

[1547] In this way, the system aims to consistently support and streamline the patent application process. As a specific example, when applying for a patent for a new AI algorithm, the following prompt is entered: "Generate a patent idea for a new AI algorithm that achieves efficiency through automation." Based on this prompt, the generative AI model will generate detailed ideas.

[1548] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1549] Step 1:

[1550] The user uses a device to prepare policy documents and emails related to the invention and uploads them to the server. The input is a PDF, Word document, etc., and is sent using the device's upload function. The documents are saved on the server as output.

[1551] Step 2:

[1552] The server saves the received data. The input is the file uploaded in the previous step, and the destination is the server's file system. The output is the data saved on the server.

[1553] Step 3:

[1554] The server runs a natural language processing (NLP) engine to tokenize and morphologically analyze the stored material. It uses the text data of the received material as input. Specifically, it uses an NLP engine (e.g., SpaCy) to extract nouns and verbs. The output is a list of important keywords and concepts.

[1555] Step 4:

[1556] The server uses a generative AI model to generate patent idea hypotheses based on the extracted keywords and concepts. It uses a list of keywords or concepts and a prompt (e.g., "Please generate a patent idea for a new AI algorithm") as input. The generated patent idea hypotheses are obtained as output.

[1557] Step 5:

[1558] The server sends the generated patent idea assumptions to the user's terminal and displays them. The generated patent idea assumptions are used as input and are displayed on the user's terminal as output.

[1559] Step 6:

[1560] Users submit feedback on the presented patent ideas from their devices. The system uses the user's evaluations and opinions as input, and sends the feedback entered in the comment field from the device. The feedback is sent to the server as output.

[1561] Step 7:

[1562] The server receives the feedback provided by the user and analyzes it with an emotion recognition engine. Using the feedback content as input, the emotion recognition engine determines the emotional state, whether positive or negative. The output is the emotion analysis result.

[1563] Step 8:

[1564] The server adjusts how to improve and present the patent idea based on the sentiment analysis results. It uses the sentiment analysis results and the original patent idea hypotheses as input. It uses the generative AI model again to generate the improved patent idea. The improved patent idea is obtained as output.

[1565] Step 9:

[1566] The server presents the improved patent idea to the user again and repeats the same feedback process, using the improved patent idea as input and presented to the user's terminal as output.

[1567] Step 10:

[1568] The server searches a patent database for competing patents based on the confirmed patent idea. It uses keywords and concepts from the confirmed patent idea as input and sends a search query to the patent database. The output is a list of competing patents.

[1569] Step 11:

[1570] The server provides the user with information on competing patents. It uses a list of competing patents obtained from a patent database as input and reports it to the user. It displays the competing patent information on a terminal as output.

[1571] Step 12:

[1572] The server uses a natural language generation (NLG) engine to generate a patent application document based on the finalized patent idea. Using the content of the finalized patent idea as input, the NLG engine generates the format and writing style of the document. The patent application document is created as output.

[1573] Step 13:

[1574] The user uses a terminal to check the generated patent application document and instructs on necessary corrections. The patent application document is used as input, and correction instructions are entered in the comment field. The correction instructions are sent to the server as output.

[1575] Step 14:

[1576] The server reflects the correction instructions and completes the final patent application document. The server uses the user's correction instructions as input and updates the patent application document. The final patent application document is completed as output.

[1577] Step 15:

[1578] The server submits the completed patent application to the Patent Office's online system. It uses the final patent application as input and sends the data to the online system. The output is a confirmation of receipt from the Patent Office.

[1579] Step 16:

[1580] The user monitors the application status on the terminal and provides additional information and materials as needed. The user uses notifications from the Patent Office's online system as input and submits the additional information and materials from the terminal. The additional information and materials are sent to the Patent Office as output.

[1581] (Application example 2)

[1582] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1583] The patent application process is complex and requires a lot of time and effort. Furthermore, efficiently incorporating user feedback and generating optimal patent ideas is a difficult problem. Furthermore, existing systems have not been able to utilize feedback that takes into account the user's emotional state. This results in a lack of improvement in the efficiency and quality of patent applications, and makes searching for competing patent information and preparing application documents cumbersome. Therefore, a system that solves these issues, streamlines the patent application process, and improves user satisfaction is needed.

[1584] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving materials related to the invention, means for analyzing the received materials and extracting important keywords and concepts, means for generating a patent idea from the extracted information, means for receiving user feedback and improving the patent idea, means for analyzing the user's emotional state at the time of feedback, means for adjusting the patent idea according to the analyzed emotional state, means for searching for competing patents based on the patent idea, means for providing the user with information on competing patents, means for generating patent application documents, and means for submitting the generated patent application documents to the Patent Office. This enables the patent application process to be carried out efficiently and effectively, and improves user satisfaction.

[1585] "Materials related to the invention" refers to information and documents necessary for filing a patent application, including relevant technical documents, research data, email content, etc.

[1586] "Means for receiving" refers to the function or method by which the server receives materials related to the invention from the user and stores them in storage.

[1587] "Means for analysis" refers to the functions and methods for processing received materials and extracting important keywords and concepts using natural language processing technology.

[1588] "Extracted information" refers to keywords and concepts obtained from the analyzed materials, and is the basis for generating patent ideas.

[1589] A "means for generating patent ideas" is a function or method for automatically generating new patent hypotheses or proposals based on the extracted information.

[1590] "User Feedback" means any opinion, comment, or evaluation provided by a user regarding a patent idea.

[1591] "Means for improving the patent idea" refers to the functions and methods for further improving and optimizing the patent idea based on the feedback received.

[1592] "Means for analyzing emotional state" refers to techniques or methods for analyzing the user's text, voice, or facial expressions during feedback to understand and classify their emotions.

[1593] "Means for adjusting patent ideas" refer to functions and methods for changing and optimizing the content and presentation of patent ideas according to the user's emotional state.

[1594] The "means for searching competing patents" refers to a function or method for searching a patent database for existing patents related to the generated patent idea.

[1595] "Competitive Patent Information" is detailed data about existing patents that have been searched and is a reference provided to the user.

[1596] The "means for generating patent application documents" refers to a function or method for automatically creating documents required for a patent application based on a confirmed patent idea.

[1597] "Means for submission" refers to the functionality or method for submitting the generated patent application documents to the Patent Office online or offline.

[1598] MODE FOR CARRYING OUT THE INVENTION

[1599] The embodiments of the present invention will be described in detail below.

[1600] System Overview

[1601] The system of the present invention is equipped with a series of means for streamlining the patent application process. The system is mainly composed of three elements: a server, a terminal, and a user. The server receives and analyzes invention-related materials and uses that information to generate and refine patent ideas. The terminal functions as an interface for users to provide feedback and upload materials.

[1602] Hardware and software used

[1603] 1. Hardware:

[1604] Server: High-performance data processing server

[1605] Device: Smartphone, smart glasses, or computer

[1606] 2. Software:

[1607] Natural Language Processing Engine (TextBlob)

[1608] Sentiment analysis engine (Hugging Face transformers library)

[1609] Database systems (e.g. PostgreSQL)

[1610] Patent database search function

[1611] Natural Language Generation Engine (Natural Language Model)

[1612] Specific processing flow

[1613] First, the user uploads documents related to the invention using a terminal. The server stores the received documents in storage. A natural language processing engine is used to tokenize and analyze the documents to extract important keywords and concepts. Based on this extracted information, a patent idea is generated.

[1614] The generated patent ideas are presented to the user's device. The user provides feedback on the presented ideas. During the feedback process, the user's emotional state is analyzed using an emotion analysis engine. This allows the idea to be adjusted according to the user's emotional state.

[1615] Once a patent idea is finalized, the server searches the patent database for relevant competing patents, and provides the competing patent information to the user, allowing them to adjust the idea as needed.

[1616] Finally, the server generates a patent application document based on the confirmed patent idea, which can then be submitted to the patent office online or offline. Users can monitor the application status through their devices and provide additional information and materials as needed.

[1617] Examples of concrete examples and prompts

[1618] For example, if a user wants to apply for a patent for a new voice recognition technology, they first upload technical documents and related emails from their device to the server. The server analyzes this information and extracts keywords such as "voice recognition technology," "improved accuracy," and "real-time processing." Based on these keywords, a patent idea for "a new algorithm to improve the accuracy of voice recognition" is generated. The user then provides feedback on this idea, saying, "This idea is interesting, but further details need to be specified."

[1619] Example prompt for a generative AI model:

[1620] User feedback: "This is a great idea, but we should also consider how to improve the accuracy."

[1621] In this way, the system of the present invention can streamline the entire process from the generation of a patent idea to the filing of an application, and can quickly reflect user feedback.

[1622] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1623] Step 1:

[1624] The user uploads documents related to the invention using a terminal. The input includes files such as technical documents and related emails. This document is sent to the server, which then stores the received documents in storage. The output is the saved document file. Specifically, the user selects the documents using the file upload interface and presses the upload button, which sends the documents to the server.

[1625] Step 2:

[1626] The server analyzes the uploaded materials using a natural language processing engine. The material file saved in step 1 is used as input. The analysis process tokenizes the materials and extracts important keywords and concepts. The output is the extracted keywords and concepts. Specifically, the TextBlob library is used to tokenize the documents and perform morphological analysis.

[1627] Step 3:

[1628] The server generates patent ideas based on the extracted keywords and concepts. The input includes the keywords and concepts extracted in step 2. An AI model is used to generate patent ideas based on this information. The output is the generated patent idea. Specifically, the generative AI model is used to create patent ideas on themes such as "new algorithms" and "efficiency."

[1629] Step 4:

[1630] The server presents the generated patent idea to the user's terminal. The patent idea created in step 3 is used as input. The user provides feedback on the presented idea. The output is the user's feedback. Specifically, the server displays the patent idea on the user interface and provides a feedback input field.

[1631] Step 5:

[1632] The server receives the user's feedback and analyzes the feedback content using a sentiment analysis engine. The feedback received in step 4 is used as input. The sentiment analysis determines the user's emotional state (positive, negative, etc.). The output is the analyzed emotional data. Specifically, the server utilizes the Hugging Face transformers library to perform sentiment analysis on the feedback text.

[1633] Step 6:

[1634] The server adjusts the patent idea based on the analyzed emotional state. The input includes the emotional data obtained in step 5 and the patent idea generated in step 3. The idea is refined according to the emotional state and presented to the user again. The output is the adjusted patent idea. Specifically, the server evaluates the emotional data and updates the content and presentation method of the patent idea.

[1635] Step 7:

[1636] The server searches the patent database based on the confirmed patent idea to find related competing patents. The input includes the patent idea confirmed in step 6. The server outputs the competing patent information obtained as a search result. Specifically, it uses the patent database search function to extract related patents from the database.

[1637] Step 8:

[1638] The server provides the searched competing patent information to the user and generates a patent application document. The input includes the competing patent information obtained in step 7 and the patent idea confirmed in step 6. The output is the generated patent application document. Specifically, the server uses a natural language generation engine to automatically create the patent application document.

[1639] Step 9:

[1640] The server submits the generated patent application document to the Patent Office. The patent application document created in step 8 is used as input. The document is submitted to the Patent Office online or offline, and then confirmed. The output is the acceptance status of the patent application. Specifically, the document is uploaded through the Patent Office's online system, and the application number, etc. are confirmed.

[1641] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1642] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1643] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1644] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1645] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1646] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1647] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1648] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1649] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1650] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1651] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1652] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1653] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1654] 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.

[1655] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1656] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1657] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1658] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1659] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1660] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1661] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1662] The following is further disclosed regarding the above embodiment.

[1663] (Claim 1)

[1664] means for receiving materials relating to the invention;

[1665] A means of analyzing received materials and extracting important keywords and concepts;

[1666] a means for generating patent ideas from the extracted information;

[1667] a means for receiving user feedback and refining the patent idea;

[1668] A means for searching for competing patents based on a patent idea;

[1669] a means for providing competitive patent information to a user;

[1670] means for generating a patent application document;

[1671] The system includes means for submitting the generated patent application document to a patent office.

[1672] (Claim 2)

[1673] 2. The system of claim 1, wherein the system analyzes materials using natural language processing and extracts keywords and concepts.

[1674] (Claim 3)

[1675] 10. The system of claim 1, wherein the AI ​​model is used to refine ideas based on user feedback.

[1676] "Example 1"

[1677] (Claim 1)

[1678] means for receiving a digital document;

[1679] means for analyzing received documents and extracting important information;

[1680] means for generating intellectual property ideas from the extracted information;

[1681] a means for receiving user feedback and refining the intellectual property idea;

[1682] A means for searching existing intellectual property based on an intellectual property idea;

[1683] means for presenting search results to a user;

[1684] means for generating an intellectual property application document;

[1685] The system includes a means for submitting the generated intellectual property application document.

[1686] (Claim 2)

[1687] 10. The system of claim 1, wherein natural language processing is used to analyze the document and extract information.

[1688] (Claim 3)

[1689] 10. The system of claim 1, wherein the system refines ideas using a generative AI model based on user feedback.

[1690] "Application Example 1"

[1691] New Claims

[1692] (Claim 1)

[1693] means for receiving materials relating to the invention;

[1694] A means of analyzing received materials and extracting important keywords and concepts;

[1695] a means for generating patent ideas from the extracted information;

[1696] a means for receiving user feedback and refining the patent idea;

[1697] A means for searching for competing patents based on a patent idea;

[1698] a means for providing competitive patent information to a user;

[1699] means for generating a patent application document;

[1700] means for submitting the generated patent application document to a patent office;

[1701] means for receiving product information and generating a product description;

[1702] The system includes a means for a user to review and modify the generated product description.

[1703] (Claim 2)

[1704] 2. The system of claim 1, wherein the system analyzes materials using natural language processing and extracts keywords and concepts.

[1705] (Claim 3)

[1706] 10. The system of claim 1, wherein the system uses an AI model to refine ideas and product descriptions based on user feedback.

[1707] "Example 2: Combining Emotion Engines"

[1708] (Claim 1)

[1709] means for receiving materials relating to the invention;

[1710] A means of analyzing received materials and extracting important keywords and concepts;

[1711] a means for generating patent ideas from the extracted information;

[1712] a means for receiving user feedback and refining the patent idea;

[1713] A means for analyzing the user's emotional state and adjusting how the idea is improved or presented based on the feedback content;

[1714] A means for searching for competing patents based on a patent idea;

[1715] a means for providing competitive patent information to a user;

[1716] means for generating a patent application document;

[1717] The system includes means for submitting the generated patent application document to a patent office.

[1718] (Claim 2)

[1719] 2. The system of claim 1, wherein the system analyzes materials using natural language processing and extracts keywords and concepts.

[1720] (Claim 3)

[1721] 10. The system of claim 1, wherein the AI ​​model is used to refine ideas based on user feedback.

[1722] (Claim 4)

[1723] 10. The system of claim 1, employing an emotion recognition engine to analyze the user's emotional state during feedback collection.

[1724] "Application example 2 when combining emotion engines"

[1725] (Claim 1)

[1726] means for receiving materials relating to the invention;

[1727] A means of analyzing received materials and extracting important keywords and concepts;

[1728] a means for generating patent ideas from the extracted information;

[1729] a means for receiving user feedback and refining the patent idea;

[1730] means for analyzing the user's emotional state at the time of feedback;

[1731] a means for adjusting patent ideas according to the analyzed emotional state;

[1732] A means for searching for competing patents based on a patent idea;

[1733] a means for providing competitive patent information to a user;

[1734] means for generating a patent application document;

[1735] The system includes means for submitting the generated patent application document to a patent office.

[1736] (Claim 2)

[1737] 2. The system of claim 1, wherein the system analyzes materials using natural language processing and extracts keywords and concepts.

[1738] (Claim 3)

[1739] The system of claim 1, which uses an AI model to improve ideas based on user feedback and further analyzes the user's emotional state to adjust patent ideas. [Explanation of symbols]

[1740] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving materials relating to the invention; A means of analyzing received materials and extracting important keywords and concepts; a means for generating patent ideas from the extracted information; a means for receiving user feedback and refining the patent idea; A means for searching for competing patents based on a patent idea; a means for providing competitive patent information to a user; means for generating a patent application document; The system includes means for submitting the generated patent application document to a patent office.

2. 10. The system according to claim 1, wherein the system analyzes the material using natural language processing to extract keywords and concepts.

3. 10. The system of claim 1, wherein the AI ​​model is used to refine ideas based on user feedback.

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