system

Abstract

We provide the system. [Solution] A means for content creators to input data, A means for generating unique identification information based on the aforementioned data, means for recording the aforementioned identification information on a distributed recording medium, Means for monitoring the unauthorized use of the aforementioned data on an information and communication network, A means of sending notifications when fraudulent use is detected, A means of evaluating the aforementioned data and analyzing market information to present appropriate trading conditions, A system that includes this.

Description

Technical Field

[0005] ,

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Currently, content generators are facing multiple problems such as copyright infringement, uneven revenue distribution, and difficulty in effective cooperation with enterprises. As a result, the rights of content are not fully protected, and a situation occurs where generators cannot obtain appropriate revenues. Also, strengthening cooperation with enterprises and expanding business opportunities for generators are important issues.

Means for Solving the Problems

[0005] This invention provides a system that allows content creators to safely publish and sell their works. It protects the rights to the works by generating a unique identifier upon content upload and recording it in ledger technology. It also has a function to monitor for unauthorized use on the internet and notify infringements. Furthermore, it maximizes revenue by analyzing sales data and suggesting optimal pricing, and it includes a function to select and propose the most suitable creators to support collaboration with companies. This enables comprehensive support for the business growth of content creators.

[0006] A "content creator" is an individual or group that creates, publishes, or sells works or information in digital format.

[0007] "Content" refers to information and works provided in digital format, including text, images, music, and video.

[0008] A "unique identifier" is a unique piece of identification information assigned to distinguish specific content from others.

[0009] "Ledger technology" refers to technologies for securely and tamper-proof storing and managing data and records, and specifically includes blockchain technology.

[0010] "Unauthorized use on the internet" refers to the act of using, sharing, or selling another person's content without permission.

[0011] "Sales data" refers to data including the listing, sales history, and related transaction information of the content.

[0012] "Collaboration with companies" refers to joint work or partnerships between content creators and companies, aimed at pursuing mutual benefits. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] Shows an emotion map to which multiple emotions are mapped. [Figure 10] Shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

MODE FOR CARRYING OUT THE INVENTION

[0014] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0019] In the following embodiments, a numbered communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), and the like.

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention provides a marketplace system that enables content creators to properly protect their works and facilitate monetization. This system functions around three main components: a server, terminals, and users (content creators).

[0035] First, the system starts processing when the user uploads their content from their device to the server. Upon receiving this content, the server first generates a digital fingerprint. This digital fingerprint is a technology used to uniquely identify the content, thereby protecting the rights to the work.

[0036] Next, the server records the generated digital fingerprint using blockchain technology. Because blockchain is difficult to tamper with, this ensures the authenticity of the content. Furthermore, it also provides a function to automatically and continuously monitor for misuse of content across the entire internet. If a breach is detected, the server immediately sends a notification to the user prompting them to take the necessary action.

[0037] In terms of monetization, the server analyzes the user's past sales data and market trends to suggest appropriate pricing. Prices are dynamically adjusted, enabling more market-adapted monetization. Users can review the displayed price on their device and make a final decision. Furthermore, an optimized algorithm is applied to ensure that creators receive fair profits.

[0038] Furthermore, the server accepts collaboration requests from companies and recommends appropriate creators accordingly. This allows users to gain more collaboration opportunities and secure new revenue streams.

[0039] For example, when a user uploads their own music content to the system, the server generates an identification fingerprint of the music and creates a record to protect copyright. It also analyzes the popularity and trends of the music and suggests the most effective selling price at that time. As a result, users can confidently offer their work and earn revenue.

[0040] As described above, the present invention is a system that aims to solve the numerous challenges faced by content creators and to create an environment in which they can concentrate on their creative activities.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] Users upload their content to the marketplace from their devices. The server receives this request and retrieves the content data.

[0044] Step 2:

[0045] The server generates a digital fingerprint from the retrieved content. This digital fingerprint is created as a unique identifier by analyzing the content's properties.

[0046] Step 3:

[0047] The server records the generated digital fingerprint using blockchain technology. This record protects the rights to the content and allows for action to be taken if objections arise at a later date.

[0048] Step 4:

[0049] For content uploaded by users, the server activates an AI function that monitors the internet to ensure it is not being misused. This monitoring is performed regularly, and if similar content is detected, a notification is sent to the user.

[0050] Step 5:

[0051] The server analyzes the user's past sales data and current market trends. Based on this, it calculates the optimal price for uploaded content and proposes it to the user.

[0052] Step 6:

[0053] The user reviews the price offer provided by the server on their device. If the user agrees, they approve the price, and the content sale begins at the applied price.

[0054] Step 7:

[0055] The server tracks sales data and distributes revenue to users based on sales. An optimized algorithm is used to ensure that revenue is distributed fairly.

[0056] Step 8:

[0057] When a collaboration request is received by the server from a company, the server analyzes the request, selects the most suitable creator, and notifies them. The user checks this notification on their device and proceeds with the necessary collaboration procedures.

[0058] (Example 1)

[0059] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0060] There are challenges in efficiently and securely managing data while addressing issues such as the misuse of data created by information providers on the internet and the infringement of their rights, as well as ensuring appropriate pricing and opportunities for collaboration.

[0061] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0062] In this invention, the server includes means for information providers to transmit data, means for generating a unique certificate based on the data, means for registering the unique certificate on a distributed recording medium, means for detecting unauthorized use of the data on an information communication network, means for outputting a notification when unauthorized use is identified, means for analyzing data transaction information and market information and suggesting an appropriate price, and means for selecting and proposing appropriate information providers in order to promote cooperation with corporations. This creates an environment in which information providers can provide data with peace of mind and enables them to obtain new opportunities through optimal pricing and collaboration.

[0063] An "information provider" is an entity that provides data it creates or owns to a system and has it managed and used by the system.

[0064] "Data" refers to digital content, including media files, documents, or other information transmitted by an information provider.

[0065] "Unique proof" is identification information generated based on data, which uniquely identifies that data and protects rights.

[0066] A "distributed recording medium" is a technology for protecting digital information from tampering and for permanently recording it, and typically includes blockchain technology.

[0067] An "information and communication network" refers to the network infrastructure used for sending and receiving data, including the Internet.

[0068] "Unauthorized use" refers to the act of using data without the permission of the information provider, and constitutes an infringement of rights.

[0069] A "notification" is a message sent to the information provider to warn or inform them when unauthorized use is identified.

[0070] "Transaction information" refers to historical data regarding the past sale and use of data.

[0071] "Market information" refers to information about current economic and consumer trends that influence the value and positioning of data.

[0072] A "legal entity" is an organization or company that engages in business partnerships or collaborations with data and information providers.

[0073] This invention provides a system for information providers to securely manage and appropriately monetize their data. The system consists of three components: a server, a terminal, and the information provider who acts as the user.

[0074] The user first uploads data to the system using a device. This device can be a desktop PC, laptop, or mobile device, and must have a standard internet connection. The user selects and uploads data using a dedicated app or web browser on the device, with an intuitive interface.

[0075] The server applies the SHA-256 algorithm to the received data to generate a unique digital fingerprint. This digital fingerprint uniquely identifies the data and protects ownership rights. Next, the server registers the generated digital fingerprint on the blockchain platform. This registration process ensures that data ownership and access records are securely stored and trusted.

[0076] Furthermore, the server operates dedicated monitoring software to detect unauthorized use of data on the internet. This software crawls a wide range of websites and platforms, searching for any matches with the uploaded data. If unauthorized use is detected, the server immediately sends an alert notification to the user, including specific instructions on how to proceed.

[0077] In terms of monetization, the server uses a generative AI model based on Python to analyze transaction and market information. This allows it to dynamically suggest appropriate prices. For example, the server can provide users with specific suggestions such as, "Based on past sales history, we suggest a price of XX for this data."

[0078] To facilitate collaboration with companies, the server accepts partnership requests via a CRM system and uses a generative AI model to select appropriate information providers. This allows users to increase their opportunities to generate new revenue streams.

[0079] As described above, this system solves various challenges faced by information providers and creates an environment where they can manage and provide data with confidence. An example of a prompt using this system would be, "Analyze and report what a fair market price would be for this data." In response to this prompt, the generating AI model provides the user with a market-value suggestion based on historical data.

[0080] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0081] Step 1:

[0082] Users upload their data to the system using a terminal. This data is in digital format and includes music, videos, images, or document files. The terminal sends this data to the server, completing the upload. The output of this process is the original data file stored on the server.

[0083] Step 2:

[0084] The server receives the uploaded data and generates a digital fingerprint using the SHA-256 algorithm. This algorithm converts the input data into a unique hash value, generating a unique proof corresponding to each piece of data. The output is a digital fingerprint for identifying the data.

[0085] Step 3:

[0086] The server registers the generated digital fingerprint on a distributed recording medium, namely the blockchain. The input is the generated digital fingerprint, and a transaction is created using blockchain technology, which is then recorded on the ledger. The output is the completion of registration on the tamper-proof blockchain.

[0087] Step 4:

[0088] The server crawls each website on the internet and monitors for unauthorized use of uploaded data. Inputs are digital fingerprints and crawled website content data, which are compared to identify inconsistencies. Outputs are warning notifications if infringement is detected.

[0089] Step 5:

[0090] The server analyzes transaction and market data using machine learning models to perform dynamic pricing. Inputs are historical sales data and current market data, and a generative AI model is used to calculate the optimal price. The output is a price suggestion for the user.

[0091] Step 6:

[0092] The server receives partnership requests from companies and, through the CRM system, uses a generative AI model to select appropriate information providers. The inputs are the company's partnership requirements and the information provider's profile data. Based on this, a recommendation algorithm operates and outputs a list of optimal candidates. This process gives the user or company the opportunity to collaborate with the candidates.

[0093] (Application Example 1)

[0094] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0095] In today's digital content market, there is a lack of systems that allow content creators to protect their works from misuse and to monetize them appropriately. Furthermore, the lack of means to offer optimal transaction terms and effectively build cooperative relationships with commercial organizations means that content creators are missing out on opportunities to earn legitimate profits.

[0096] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0097] In this invention, the server includes means for inputting data, means for generating unique identification information, means for recording the identification information on a distributed recording medium, means for monitoring unauthorized use of data on an information and communication network, and means for evaluating the data and analyzing market information to present appropriate transaction terms. This enables content creators to protect their works, effectively monetize them, and facilitate cooperation with commercial organizations.

[0098] A "content creator" is someone who creates and disseminates digital works and data.

[0099] "Data" refers to the information and materials input by content creators, which are then processed by the system.

[0100] "Identifying information" refers to unique information generated to uniquely identify data, and its purpose is protection.

[0101] A "distributed recording medium" is a technological foundation that has the characteristic of making it difficult to change information once it is recorded, and includes ledger technology.

[0102] An "information and communication network" refers to a communication infrastructure that enables the exchange and distribution of data, including the internet.

[0103] "Unauthorized use" refers to the act of using data or its contents without permission by someone without authorization.

[0104] "Terms of trade" refer to the conditions and prices proposed when content creators exchange their data in the market.

[0105] A "commercial organization" refers to a broad range of companies and groups involved in economic activities, and is a target for partnerships with content creators.

[0106] This invention is configured as a system for content creators to securely handle their works in the digital space. Users input data using a terminal, which then transmits it to a server.

[0107] The server generates unique identification information based on the data received from the user. This identification information is obtained by creating a digital fingerprint using a hash algorithm. The obtained identification information is recorded using a decentralized recording medium, specifically the Ethereum blockchain. This makes the identification information difficult to tamper with, guaranteeing the reliability of the data.

[0108] Furthermore, the server monitors for unauthorized use of data via the information and communication network. Using web scraping technology, it continuously searches for similar content elsewhere. If unauthorized use is detected, a notification is immediately sent to the user. This utilizes real-time data processing using AWS® Lambda.

[0109] The server further uses Python's Scikit-Learn to evaluate data and analyze market information, then presents users with appropriate trading conditions. This allows users to obtain accurate information based on market trends.

[0110] To facilitate collaboration with commercial organizations, the server has a function to select and suggest the most suitable data generators. This involves performing real-time data analysis using cloud computing and notifying the generators.

[0111] As a concrete example, when a user uploads video content related to natural scenery, identification information is generated through Creative Guardian and recorded on the Ethereum blockchain. If this content is used without permission on social media, the user receives a prompt notification. Furthermore, a price based on market trends is presented, allowing the user to distribute the content with confidence.

[0112] An example of a prompt for the generating AI model might be: "Propose the best price to protect and sell the content under the following conditions: video content, natural scenery, based on market trends in December 2023." This system would create an environment where content creators can confidently offer their work and earn revenue.

[0113] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0114] Step 1:

[0115] The user inputs and uploads digital content using a terminal. The input is the user's content file. The terminal sends this file to the server. The output is data ready for the server to receive. This creates the foundation for proceeding to the next processing step.

[0116] Step 2:

[0117] The server receives uploaded content files and generates a digital fingerprint. User content data is required as input. The server applies a hash algorithm to generate a unique identifier (digital fingerprint) for the content. The generated identifier is obtained as output. This information is used to ensure the integrity of the data.

[0118] Step 3:

[0119] The server records the generated identification information on the Ethereum blockchain. The input is the identification information obtained in the previous step. The server utilizes an API for saving data to the blockchain and records this information on a distributed storage medium. The output is the location information where the identification information is recorded. This ensures that the identification information is not tampered with.

[0120] Step 4:

[0121] The server monitors for misuse on the internet via the information and communication network. Its inputs include recorded identification information and related data. The server uses web scraping techniques to detect similar content on the internet. The output provides warning information if misuse is detected. This enables early detection of misuse.

[0122] Step 5:

[0123] The server evaluates data and analyzes market information to present appropriate trading conditions to the user. Input includes market trend data and user content data. The server uses Python's Scikit-Learn to analyze this data and predicts optimal trading conditions using a generation AI model. The output provides recommended trading conditions, allowing the user to maximize their profits.

[0124] Step 6:

[0125] The user reviews the transaction terms presented on the terminal and makes a final decision. The transaction terms sent from the server are displayed as input. The user reviews the terms through the terminal interface and chooses to accept or modify them. The user's decision information is provided as output. This decision directly impacts the sale of the content.

[0126] This will enable users to effectively facilitate secure content transactions and monetization.

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

[0128] This invention enhances the user experience by adding the functionality of an emotion engine to conventional content marketplace systems. In this system, the server, terminal, and user work together to achieve optimal content display and price adjustments that reflect the user's emotions.

[0129] First, a new process incorporating an emotion engine is implemented in the traditional user uploading process using their device. The user's device collects emotion data through the user's webcam and microphone and sends it to the server. The server uses the emotion engine to analyze the collected data and identify the emotions the user is currently experiencing.

[0130] The identified emotion data is reflected in the content the server displays to the user and the content it recommends. For example, if a user is relaxed, the server will prioritize displaying calming content that matches that emotion. Conversely, if a user is excited, it can provide more interactive content.

[0131] Furthermore, by leveraging feedback from the emotion engine, the server can also influence pricing. Specifically, if the server determines that a user has an emotion indicating a willingness to purchase, it can dynamically adjust the price to make it more appealing to the user.

[0132] For example, suppose a user is viewing music content, and the device analyzes the user's facial expressions using an emotion engine and determines that the user is relaxed. In this case, the server recommends music related to relaxation and offers some of them at a special price to make the user's choice easier.

[0133] Thus, the present invention aims to improve the user experience and maximize the benefits for creators and the marketplace as a whole by capturing the user's psychological state and reflecting it in content suggestions and pricing.

[0134] The following describes the processing flow.

[0135] Step 1:

[0136] The user logs into the content marketplace using their device and prepares to view content. At this point, the device activates its webcam and microphone, collecting data on the user's facial expressions and voice tone.

[0137] Step 2:

[0138] User emotion data collected on the device is sent to the server in real time. The server receives this data and uses an emotion engine to perform a detailed emotion analysis. This analysis identifies the specific emotional state the user is currently experiencing, such as joy, sadness, or surprise.

[0139] Step 3:

[0140] The server selects the most suitable content for the user based on the emotional state identified through analysis. For example, if the user indicates a relaxed state, it recommends calming music or quiet video content. It also displays a list of selected content on the user's device.

[0141] Step 4:

[0142] When a user selects content they are interested in from the suggested options, the server displays detailed information about that content, along with a price that takes sentiment analysis into account, on the user's device. For example, if the user is very excited, a special offer may be presented to encourage a purchase.

[0143] Step 5:

[0144] When a user decides to make a purchase, the terminal sends order information to the server. The server processes this information and completes the purchase process. The system also records the user's emotional state and purchase behavior data, which is used to improve the accuracy of future recommendations.

[0145] This entire process allows users to enjoy content that matches their emotions, and also enables the marketplace to achieve higher user satisfaction and more efficient monetization.

[0146] (Example 2)

[0147] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0148] Traditional information sharing platforms failed to provide information that took into account user emotions, and were unable to offer an experience optimized for individual users. Furthermore, they struggled to adjust financial value in response to dynamically changing market conditions, failing to provide an optimal financial environment for both information producers and consumers.

[0149] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0150] In this invention, the server includes means for a user to transmit information, means for analyzing the information and extracting sentiment data, and means for displaying information suitable for the user based on the sentiment data. This enables optimized information provision based on the user's emotions and adjustment of financial value in response to dynamic markets.

[0151] "User" refers to an individual or legal entity that transmits or receives information using this system.

[0152] "Information" refers to data and content that users send or receive through the system.

[0153] "Emotional data" refers to data about the emotional state of users extracted through the analysis of information.

[0154] "Financial value" refers to the transaction price or value associated with information, and it can be dynamically adjusted.

[0155] "Combined technologies" refer to distributed ledger technologies and similar technologies used to record financial values ​​and other digital data.

[0156] "Information creator" refers to an entity that creates and provides information within a marketplace.

[0157] A "server" refers to a central computer system that receives, processes, and transmits information.

[0158] This system involves interaction between users, terminals, and servers to provide information that takes into account the user's emotional state. Users can upload information to the marketplace through the interface.

[0159] The device uses specific hardware components such as a webcam and microphone to collect user emotional data. The collected data is sent to a server in real time using dedicated software called an emotion engine. The emotion engine uses a generative AI model based on machine learning to analyze the received facial and audio data and identify the user's emotional state.

[0160] The server uses an emotion engine to analyze emotional data and select and present the most relevant information to the user. For example, if the server determines that the user is relaxed, music and videos suitable for relaxation will be prioritized. The server also features dynamic pricing, automatically adjusting the financial value of information according to market conditions. This allows it to provide optimal trading conditions that are constantly changing.

[0161] As a concrete example, consider a situation where a user is browsing music content. If the device captures the user's facial expression and analyzes it to indicate that the user is experiencing joy, the server recommends enjoyable music or videos that are appropriate for that emotion. Furthermore, purchase options are presented with pricing optimized for that moment.

[0162] As an example of a prompt message for a generative AI model, you could say, "Generate a list of music content to recommend when the user is determined to be relaxed," which would enable the model to provide information based on that.

[0163] Thus, through the concrete implementation of the invention, users can receive personalized information tailored to their emotions and engage in rational transactions in accordance with market trends.

[0164] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0165] Step 1:

[0166] Users upload information of their choice to the marketplace. In this process, users directly select content such as images, videos, and text via their mobile devices or computers and send the information to the system by clicking a submit button. The input here is the user's information, and the output is the completion of information transmission by the device.

[0167] Step 2:

[0168] During the upload process, the device collects the user's biometric information using a webcam and microphone. Specifically, it captures the user's facial expressions in real time and records audio data. This biometric information serves as input, and the output is obtained by sending it to the server as digital data.

[0169] Step 3:

[0170] The server receives biometric data transmitted from the terminal and performs analysis using an emotion engine. This process uses a generative AI model to process the input biometric data and identify the user's emotional state (e.g., joy, sadness, relaxation). The output is the analyzed emotion data.

[0171] Step 4:

[0172] The server selects and provides the most relevant information to the user based on emotional data. For example, if the analysis determines that the user is in a relaxed state, the server will prioritize recommending music and videos suitable for relaxation. Here, the input is the analyzed emotional data, and the output is the information displayed to the user.

[0173] Step 5:

[0174] The server dynamically adjusts financial value based on market and transactional data. Specifically, if user sentiment indicates a willingness to buy, the server uses prompt messages to generate optimal pricing and presents the user with discount options. The input is market and sentiment data, and the output is dynamically adjusted financial value.

[0175] Step 6:

[0176] Users can review personalized information and adjusted financial values ​​provided by the server and make their own decisions regarding the purchase and use of that information. The user's final decision is based on the information presented as output from the server.

[0177] (Application Example 2)

[0178] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0179] Traditional content distribution platforms lack personalized content recommendations that take into account users' emotional states, and emotion-based pricing, making it difficult to improve the user experience. Furthermore, insufficient measures against content misuse hinder the profitability of content creators.

[0180] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0181] In this invention, the server includes means for sensing the user's psychological state through emotion analysis means, means for presenting optimal information based on the psychological state, and means for dynamic price adjustment based on the psychological state. This enables personalized content recommendations and emotion-based price adjustments that respond to the user's emotions, and in addition, it enables appropriate monitoring of misuse of content.

[0182] "Emotional analysis methods" are technologies that determine a user's psychological state based on their facial expressions and voice, and acquire that data.

[0183] "Psychological state" refers to the user's emotions, mood, and level of excitement, and is evaluated through emotion analysis methods.

[0184] "Means of presenting information" refers to the process of displaying content and pricing information optimized according to the user's psychological state.

[0185] A "dynamic price adjustment mechanism" is a system that changes prices in real time based on the user's psychological state and market data.

[0186] A "content creator" refers to an individual or legal entity that produces digital content and uploads it to a platform.

[0187] A "unique identifier" is a unique number or code assigned to uploaded content, which is managed using database technology.

[0188] "Database technology" refers to systems and platforms that structurally store and manage digital information and efficiently retrieve that information as needed.

[0189] "Unauthorized use" refers to acts in which content is used without permission or infringes upon intellectual property rights.

[0190] "Means of sending notifications" refers to a communication process used to warn or inform relevant parties when fraudulent activity is detected.

[0191] This system senses the user's psychological state and performs a series of processes to recommend content and dynamically adjust prices based on that state. The server uses cameras and microphones built into devices such as smartphones and tablets as means of sentiment analysis. The devices collect data on the user's psychological state from their facial expressions and voice through these devices and transmit it to the server.

[0192] The server uses Google Cloud's "Cloud Vision API" and "Speech-to-Text API" to analyze the received sentiment data. Based on the analysis results, machine learning models using TENSORFLOW® or PyTorch select and recommend content that best matches the user's emotions.

[0193] Furthermore, the server uses database technology to manage unique identifiers and features an abuse monitoring system that monitors content misuse in real time. This ensures that notifications are sent immediately if content is misused.

[0194] For example, when a user is enjoying a movie through this system, if the camera and microphone detect that the user is relaxed, the system will recommend a comedy movie and offer it at a special price. In this way, the system provides the optimal entertainment experience according to the user's mood.

[0195] Examples of prompt statements for a generative AI model are as follows:

[0196] "As a way to improve the user's video viewing experience, please provide ideas for a system that analyzes user emotions and suggests the best movies and discounted prices based on those emotions. The emotion analysis would use facial expression data and include real-time updated price adjustments."

[0197] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0198] Step 1:

[0199] The device captures the user's facial expressions and voice through its camera and microphone. It acquires real-time video and audio data of the user as input. This data is temporarily stored on the device before being sent to the server.

[0200] Step 2:

[0201] The server performs sentiment analysis using the received video and audio data. It receives video and audio data transmitted from the terminal as input and analyzes it using Google Cloud's "Cloud Vision API" and "Speech-to-Text API." As a result, it generates sentiment data to identify the user's emotional state (e.g., relaxed, excited).

[0202] Step 3:

[0203] The server uses the analyzed sentiment data to run a recommendation model using TensorFlow or PyTorch. The sentiment data obtained in step 2 is input to the model, and it outputs a list of optimal content based on the user's psychological state.

[0204] Step 4:

[0205] The server adjusts the price of specified content based on dynamic pricing. Using the generated content list as input, it applies a pre-configured pricing algorithm to determine the optimal price. The output is a final content list containing the adjusted prices.

[0206] Step 5:

[0207] The server sends a content list and pricing information optimized for the user's device. This allows the user to browse and purchase content that suits their mood at an appropriate price. The content list and prices obtained in step 4 are used as input, and the information to be presented to the user is sent as output.

[0208] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0209] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0210] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0211] [Second Embodiment]

[0212] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0213] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0214] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0215] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0216] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0217] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0218] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0219] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0220] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0221] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0222] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0223] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0224] This invention provides a marketplace system that enables content creators to properly protect their works and facilitate monetization. This system functions around three main components: a server, terminals, and users (content creators).

[0225] First, the system starts processing when the user uploads their content from their device to the server. Upon receiving this content, the server first generates a digital fingerprint. This digital fingerprint is a technology used to uniquely identify the content, thereby protecting the rights to the work.

[0226] Next, the server records the generated digital fingerprint using blockchain technology. Because blockchain is difficult to tamper with, this ensures the authenticity of the content. Furthermore, it also provides a function to automatically and continuously monitor for misuse of content across the entire internet. If a breach is detected, the server immediately sends a notification to the user prompting them to take the necessary action.

[0227] In terms of monetization, the server analyzes the user's past sales data and market trends to suggest appropriate pricing. Prices are dynamically adjusted, enabling more market-adapted monetization. Users can review the displayed price on their device and make a final decision. Furthermore, an optimized algorithm is applied to ensure that creators receive fair profits.

[0228] Furthermore, the server accepts collaboration requests from companies and recommends appropriate creators accordingly. This allows users to gain more collaboration opportunities and secure new revenue streams.

[0229] For example, when a user uploads their own music content to the system, the server generates an identification fingerprint of the music and creates a record to protect copyright. It also analyzes the popularity and trends of the music and suggests the most effective selling price at that time. As a result, users can confidently offer their work and earn revenue.

[0230] As described above, the present invention is a system that aims to solve the numerous challenges faced by content creators and to create an environment in which they can concentrate on their creative activities.

[0231] The following describes the processing flow.

[0232] Step 1:

[0233] Users upload their content to the marketplace from their devices. The server receives this request and retrieves the content data.

[0234] Step 2:

[0235] The server generates a digital fingerprint from the retrieved content. This digital fingerprint is created as a unique identifier by analyzing the content's properties.

[0236] Step 3:

[0237] The server records the generated digital fingerprint using blockchain technology. This record protects the rights to the content and allows for action to be taken if objections arise at a later date.

[0238] Step 4:

[0239] For content uploaded by users, the server activates an AI function that monitors the internet to ensure it is not being misused. This monitoring is performed regularly, and if similar content is detected, a notification is sent to the user.

[0240] Step 5:

[0241] The server analyzes the user's past sales data and current market trends. Based on this, it calculates the optimal price for uploaded content and proposes it to the user.

[0242] Step 6:

[0243] The user reviews the price offer provided by the server on their device. If the user agrees, they approve the price, and the content sale begins at the applied price.

[0244] Step 7:

[0245] The server tracks sales data and distributes revenue to users based on sales. An optimized algorithm is used to ensure that revenue is distributed fairly.

[0246] Step 8:

[0247] When a collaboration request is received by the server from a company, the server analyzes the request, selects the most suitable creator, and notifies them. The user checks this notification on their device and proceeds with the necessary collaboration procedures.

[0248] (Example 1)

[0249] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0250] There are challenges in efficiently and securely managing data while addressing issues such as the misuse of data created by information providers on the internet and the infringement of their rights, as well as ensuring appropriate pricing and opportunities for collaboration.

[0251] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0252] In this invention, the server includes means for information providers to transmit data, means for generating a unique certificate based on the data, means for registering the unique certificate on a distributed recording medium, means for detecting unauthorized use of the data on an information communication network, means for outputting a notification when unauthorized use is identified, means for analyzing data transaction information and market information and suggesting an appropriate price, and means for selecting and proposing appropriate information providers in order to promote cooperation with corporations. This creates an environment in which information providers can provide data with peace of mind and enables them to obtain new opportunities through optimal pricing and collaboration.

[0253] An "information provider" is an entity that provides data it creates or owns to a system and has it managed and used by the system.

[0254] "Data" refers to digital content, including media files, documents, or other information transmitted by an information provider.

[0255] "Unique proof" is identification information generated based on data, which uniquely identifies that data and protects rights.

[0256] A "distributed recording medium" is a technology for protecting digital information from tampering and for permanently recording it, and typically includes blockchain technology.

[0257] An "information and communication network" refers to the network infrastructure used for sending and receiving data, including the Internet.

[0258] "Unauthorized use" refers to the act of using data without the permission of the information provider, and constitutes an infringement of rights.

[0259] A "notification" is a message sent to the information provider to warn or inform them when unauthorized use is identified.

[0260] "Transaction information" refers to historical data regarding the past sale and use of data.

[0261] "Market information" refers to information about current economic and consumer trends that influence the value and positioning of data.

[0262] A "legal entity" is an organization or company that engages in business partnerships or collaborations with data and information providers.

[0263] This invention provides a system for information providers to securely manage and appropriately monetize their data. The system consists of three components: a server, a terminal, and the information provider who acts as the user.

[0264] The user first uploads data to the system using a device. This device can be a desktop PC, laptop, or mobile device, and must have a standard internet connection. The user selects and uploads data using a dedicated app or web browser on the device, with an intuitive interface.

[0265] The server applies the SHA-256 algorithm to the received data to generate a unique digital fingerprint. This digital fingerprint uniquely identifies the data and protects ownership rights. Next, the server registers the generated digital fingerprint on the blockchain platform. This registration process ensures that data ownership and access records are securely stored and trusted.

[0266] Furthermore, the server operates dedicated monitoring software to detect unauthorized use of data on the internet. This software crawls a wide range of websites and platforms, searching for any matches with the uploaded data. If unauthorized use is detected, the server immediately sends an alert notification to the user, including specific instructions on how to proceed.

[0267] In terms of monetization, the server uses a generative AI model based on Python to analyze transaction and market information. This allows it to dynamically suggest appropriate prices. For example, the server can provide users with specific suggestions such as, "Based on past sales history, we suggest a price of XX for this data."

[0268] To facilitate collaboration with companies, the server accepts partnership requests via a CRM system and uses a generative AI model to select appropriate information providers. This allows users to increase their opportunities to generate new revenue streams.

[0269] As described above, this system solves various challenges faced by information providers and creates an environment where they can manage and provide data with confidence. An example of a prompt using this system would be, "Analyze and report what a fair market price would be for this data." In response to this prompt, the generating AI model provides the user with a market-value suggestion based on historical data.

[0270] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0271] Step 1:

[0272] Users upload their data to the system using a terminal. This data is in digital format and includes music, videos, images, or document files. The terminal sends this data to the server, completing the upload. The output of this process is the original data file stored on the server.

[0273] Step 2:

[0274] The server receives the uploaded data and generates a digital fingerprint using the SHA-256 algorithm. This algorithm converts the input data into a unique hash value, generating a unique proof corresponding to each piece of data. The output is a digital fingerprint for identifying the data.

[0275] Step 3:

[0276] The server registers the generated digital fingerprint on a distributed recording medium, namely the blockchain. The input is the generated digital fingerprint, and a transaction is created using blockchain technology, which is then recorded on the ledger. The output is the completion of registration on the tamper-proof blockchain.

[0277] Step 4:

[0278] The server crawls each website on the Internet and monitors whether there is any unauthorized use of the uploaded data. The input is the digital fingerprint and the content data of the crawled website, and these are compared to identify discrepancies. The output is a warning notice when fraud is detected.

[0279] Step 5:

[0280] The server analyzes the transaction information and market information of the data using a machine learning model to perform dynamic pricing. The input is past sales data and current market data, and an AI generation model is used to calculate the optimal price. The output is a price proposal to the user.

[0281] Step 6:

[0282] The server receives a cooperation request from an enterprise and selects an appropriate information provider using an AI generation model through a CRM system. The input is the enterprise's cooperation conditions and the profile data of the information provider. Based on these, the recommendation algorithm operates to output a list of optimal candidates. Through this process, the user or corporation obtains an opportunity to cooperate with the candidates.

[0283] (Application Example 1)

[0284] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0285] In the modern digital content market, there is a lack of a system for content creators to protect their works from unauthorized use and to appropriately monetize their works. In addition, there is an issue that content creators are missing opportunities to obtain legitimate profits because there are no means to effectively present optimal trading conditions or to build cooperative relationships with commercial organizations.

[0286] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0287] In this invention, the server includes means for inputting data, means for generating unique identification information, means for recording the identification information on a distributed recording medium, means for monitoring unauthorized use of data on an information communication network, and means for analyzing data evaluation and market information and presenting appropriate transaction conditions. As a result, content creators can protect their works and effectively monetize them, and can also smoothly promote cooperation with commercial organizations.

[0288] A "content creator" is a person who creates and transmits digital works and data.

[0289] "Data" refers to the information and materials input by content creators, which are the objects to be processed by the system.

[0290] "Identification information" is unique information generated to uniquely identify data and is for the purpose of protection.

[0291] A "distributed recording medium" is a technical infrastructure with the characteristic that once information is recorded, it is difficult to change, and includes ledger technology.

[0292] An "information communication network" refers to a communication infrastructure that enables data exchange and distribution including the Internet.

[0293] "Unauthorized use" refers to the act of an unauthorized person using data or its content without permission.

[0294] "Transaction conditions" refer to the conditions and prices proposed when a content creator exchanges their data in the market.

[0295] A "commercial organization" is a company or organization widely involved in economic activities and is the target of cooperation with content creators.

[0296] This invention is configured as a system for content creators to securely handle their works in the digital space. Users input data using a terminal, which then transmits it to a server.

[0297] The server generates unique identification information based on the data received from the user. This identification information is obtained by creating a digital fingerprint using a hash algorithm. The obtained identification information is recorded using a decentralized recording medium, specifically the Ethereum blockchain. This makes the identification information difficult to tamper with, guaranteeing the reliability of the data.

[0298] Furthermore, the server monitors for unauthorized use of data via the information and communication network. Using web scraping techniques, it continuously searches for similar content elsewhere. If unauthorized use is detected, a notification is immediately sent to the user. This utilizes real-time data processing using AWS Lambda.

[0299] The server further uses Python's Scikit-Learn to evaluate data and analyze market information, then presents users with appropriate trading conditions. This allows users to obtain accurate information based on market trends.

[0300] To facilitate collaboration with commercial organizations, the server has a function to select and suggest the most suitable data generators. This involves performing real-time data analysis using cloud computing and notifying the generators.

[0301] As a concrete example, when a user uploads video content related to natural scenery, identification information is generated through Creative Guardian and recorded on the Ethereum blockchain. If this content is used without permission on social media, the user receives a prompt notification. Furthermore, a price based on market trends is presented, allowing the user to distribute the content with confidence.

[0302] As an example of a prompt sentence for the generative AI model, a format such as "Please propose the optimal price for protecting and selling content under the following conditions: video content, natural landscapes, based on the market trends in December 2023." can be considered. With this system, an environment is realized where content creators can safely provide their works and obtain profits.

[0303] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0304] Step 1:

[0305] The user uses the terminal to input and upload digital content. As the input, the user's content file is provided. The terminal sends this file to the server. As the output, data prepared for the server to receive is generated. This creates a basis for proceeding to the next process.

[0306] Step 2:

[0307] The server receives the uploaded content file and generates a digital fingerprint. As the input, the user's content data is required. The server applies a hash algorithm to generate unique identification information (digital fingerprint) of the content. As the output, the generated identification information is obtained. This information is used to ensure the reliability of the data.

[0308] Step 3:

[0309] The server records the generated identification information on the Ethereum blockchain. As the input, there is the identification information obtained in the previous step. The server utilizes an API for storing data on the blockchain to record this information on a distributed recording medium. As the output, the location information where the identification information is recorded can be obtained. This realizes the prevention of tampering with the identification information.

[0310] Step 4:

[0311] The server monitors for misuse on the internet via the information and communication network. Its inputs include recorded identification information and related data. The server uses web scraping techniques to detect similar content on the internet. The output provides warning information if misuse is detected. This enables early detection of misuse.

[0312] Step 5:

[0313] The server evaluates data and analyzes market information to present appropriate trading conditions to the user. Input includes market trend data and user content data. The server uses Python's Scikit-Learn to analyze this data and predicts optimal trading conditions using a generation AI model. The output provides recommended trading conditions, allowing the user to maximize their profits.

[0314] Step 6:

[0315] The user reviews the transaction terms presented on the terminal and makes a final decision. The transaction terms sent from the server are displayed as input. The user reviews the terms through the terminal interface and chooses to accept or modify them. The user's decision information is provided as output. This decision directly impacts the sale of the content.

[0316] This will enable users to effectively facilitate secure content transactions and monetization.

[0317] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0318] This invention enhances the user experience by adding the functionality of an emotion engine to conventional content marketplace systems. In this system, the server, terminal, and user work together to achieve optimal content display and price adjustments that reflect the user's emotions.

[0319] First, a new process incorporating an emotion engine is implemented in the traditional user uploading process using their device. The user's device collects emotion data through the user's webcam and microphone and sends it to the server. The server uses the emotion engine to analyze the collected data and identify the emotions the user is currently experiencing.

[0320] The identified emotion data is reflected in the content the server displays to the user and the content it recommends. For example, if a user is relaxed, the server will prioritize displaying calming content that matches that emotion. Conversely, if a user is excited, it can provide more interactive content.

[0321] Furthermore, by leveraging feedback from the emotion engine, the server can also influence pricing. Specifically, if the server determines that a user has an emotion indicating a willingness to purchase, it can dynamically adjust the price to make it more appealing to the user.

[0322] For example, suppose a user is viewing music content, and the device analyzes the user's facial expressions using an emotion engine and determines that the user is relaxed. In this case, the server recommends music related to relaxation and offers some of them at a special price to make the user's choice easier.

[0323] Thus, the present invention aims to improve the user experience and maximize the benefits for creators and the marketplace as a whole by capturing the user's psychological state and reflecting it in content suggestions and pricing.

[0324] The following describes the processing flow.

[0325] Step 1:

[0326] The user logs into the content marketplace using their device and prepares to view content. At this point, the device activates its webcam and microphone, collecting data on the user's facial expressions and voice tone.

[0327] Step 2:

[0328] User emotion data collected on the device is sent to the server in real time. The server receives this data and uses an emotion engine to perform a detailed emotion analysis. This analysis identifies the specific emotional state the user is currently experiencing, such as joy, sadness, or surprise.

[0329] Step 3:

[0330] The server selects the most suitable content for the user based on the emotional state identified through analysis. For example, if the user indicates a relaxed state, it recommends calming music or quiet video content. It also displays a list of selected content on the user's device.

[0331] Step 4:

[0332] When a user selects content they are interested in from the suggested options, the server displays detailed information about that content, along with a price that takes sentiment analysis into account, on the user's device. For example, if the user is very excited, a special offer may be presented to encourage a purchase.

[0333] Step 5:

[0334] When a user decides to make a purchase, the terminal sends order information to the server. The server processes this information and completes the purchase process. The system also records the user's emotional state and purchase behavior data, which is used to improve the accuracy of future recommendations.

[0335] This entire process allows users to enjoy content that matches their emotions, and also enables the marketplace to achieve higher user satisfaction and more efficient monetization.

[0336] (Example 2)

[0337] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0338] Traditional information sharing platforms failed to provide information that took into account user emotions, and were unable to offer an experience optimized for individual users. Furthermore, they struggled to adjust financial value in response to dynamically changing market conditions, failing to provide an optimal financial environment for both information producers and consumers.

[0339] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0340] In this invention, the server includes means for a user to transmit information, means for analyzing the information and extracting sentiment data, and means for displaying information suitable for the user based on the sentiment data. This enables optimized information provision based on the user's emotions and adjustment of financial value in response to dynamic markets.

[0341] "User" refers to an individual or legal entity that transmits or receives information using this system.

[0342] "Information" refers to data and content that users send or receive through the system.

[0343] "Emotional data" refers to data about the emotional state of users extracted through the analysis of information.

[0344] "Financial value" refers to the transaction price or value associated with information, and it can be dynamically adjusted.

[0345] "Combined technologies" refer to distributed ledger technologies and similar technologies used to record financial values ​​and other digital data.

[0346] "Information creator" refers to an entity that creates and provides information within a marketplace.

[0347] A "server" refers to a central computer system that receives, processes, and transmits information.

[0348] This system involves interaction between users, terminals, and servers to provide information that takes into account the user's emotional state. Users can upload information to the marketplace through the interface.

[0349] The device uses specific hardware components such as a webcam and microphone to collect user emotional data. The collected data is sent to a server in real time using dedicated software called an emotion engine. The emotion engine uses a generative AI model based on machine learning to analyze the received facial and audio data and identify the user's emotional state.

[0350] The server uses an emotion engine to analyze emotional data and select and present the most relevant information to the user. For example, if the server determines that the user is relaxed, music and videos suitable for relaxation will be prioritized. The server also features dynamic pricing, automatically adjusting the financial value of information according to market conditions. This allows it to provide optimal trading conditions that are constantly changing.

[0351] As a concrete example, consider a situation where a user is browsing music content. If the device captures the user's facial expression and analyzes it to indicate that the user is experiencing joy, the server recommends enjoyable music or videos that are appropriate for that emotion. Furthermore, purchase options are presented with pricing optimized for that moment.

[0352] As an example of a prompt message for a generative AI model, you could say, "Generate a list of music content to recommend when the user is determined to be relaxed," which would enable the model to provide information based on that.

[0353] Thus, through the concrete implementation of the invention, users can receive personalized information tailored to their emotions and engage in rational transactions in accordance with market trends.

[0354] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0355] Step 1:

[0356] Users upload information of their choice to the marketplace. In this process, users directly select content such as images, videos, and text via their mobile devices or computers and send the information to the system by clicking a submit button. The input here is the user's information, and the output is the completion of information transmission by the device.

[0357] Step 2:

[0358] During the upload process, the device collects the user's biometric information using a webcam and microphone. Specifically, it captures the user's facial expressions in real time and records audio data. This biometric information serves as input, and the output is obtained by sending it to the server as digital data.

[0359] Step 3:

[0360] The server receives biometric data transmitted from the terminal and performs analysis using an emotion engine. This process uses a generative AI model to process the input biometric data and identify the user's emotional state (e.g., joy, sadness, relaxation). The output is the analyzed emotion data.

[0361] Step 4:

[0362] The server selects and provides the most relevant information to the user based on emotional data. For example, if the analysis determines that the user is in a relaxed state, the server will prioritize recommending music and videos suitable for relaxation. Here, the input is the analyzed emotional data, and the output is the information displayed to the user.

[0363] Step 5:

[0364] The server dynamically adjusts financial value based on market and transactional data. Specifically, if user sentiment indicates a willingness to buy, the server uses prompt messages to generate optimal pricing and presents the user with discount options. The input is market and sentiment data, and the output is dynamically adjusted financial value.

[0365] Step 6:

[0366] Users can review personalized information and adjusted financial values ​​provided by the server and make their own decisions regarding the purchase and use of that information. The user's final decision is based on the information presented as output from the server.

[0367] (Application Example 2)

[0368] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0369] Traditional content distribution platforms lack personalized content recommendations that take into account users' emotional states, and emotion-based pricing, making it difficult to improve the user experience. Furthermore, insufficient measures against content misuse hinder the profitability of content creators.

[0370] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0371] In this invention, the server includes means for sensing the user's psychological state through emotion analysis means, means for presenting optimal information based on the psychological state, and means for dynamic price adjustment based on the psychological state. This enables personalized content recommendations and emotion-based price adjustments that respond to the user's emotions, and in addition, it enables appropriate monitoring of misuse of content.

[0372] "Emotional analysis methods" are technologies that determine a user's psychological state based on their facial expressions and voice, and acquire that data.

[0373] "Psychological state" refers to the user's emotions, mood, and level of excitement, and is evaluated through emotion analysis methods.

[0374] "Means of presenting information" refers to the process of displaying content and pricing information optimized according to the user's psychological state.

[0375] A "dynamic price adjustment mechanism" is a system that changes prices in real time based on the user's psychological state and market data.

[0376] A "content creator" refers to an individual or legal entity that produces digital content and uploads it to a platform.

[0377] A "unique identifier" is a unique number or code assigned to uploaded content, which is managed using database technology.

[0378] "Database technology" refers to systems and platforms that structurally store and manage digital information and efficiently retrieve that information as needed.

[0379] "Unauthorized use" refers to acts in which content is used without permission or infringes upon intellectual property rights.

[0380] "Means of sending notifications" refers to a communication process used to warn or inform relevant parties when fraudulent activity is detected.

[0381] This system senses the user's psychological state and performs a series of processes to recommend content and dynamically adjust prices based on that state. The server uses cameras and microphones built into devices such as smartphones and tablets as means of sentiment analysis. The devices collect data on the user's psychological state from their facial expressions and voice through these devices and transmit it to the server.

[0382] The server uses Google Cloud's "Cloud Vision API" and "Speech-to-Text API" to analyze the received sentiment data. Based on the analysis results, a machine learning model using TensorFlow or PyTorch selects and recommends content that best matches the user's emotions.

[0383] Furthermore, the server uses database technology to manage unique identifiers and features an abuse monitoring system that monitors content misuse in real time. This ensures that notifications are sent immediately if content is misused.

[0384] For example, when a user is enjoying a movie through this system, if the camera and microphone detect that the user is relaxed, the system will recommend a comedy movie and offer it at a special price. In this way, the system provides the optimal entertainment experience according to the user's mood.

[0385] Examples of prompt statements for a generative AI model are as follows:

[0386] "As a way to improve the user's video viewing experience, please provide ideas for a system that analyzes user emotions and suggests the best movies and discounted prices based on those emotions. The emotion analysis would use facial expression data and include real-time updated price adjustments."

[0387] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0388] Step 1:

[0389] The device captures the user's facial expressions and voice through its camera and microphone. It acquires real-time video and audio data of the user as input. This data is temporarily stored on the device before being sent to the server.

[0390] Step 2:

[0391] The server performs sentiment analysis using the received video and audio data. It receives video and audio data transmitted from the terminal as input and analyzes it using Google Cloud's "Cloud Vision API" and "Speech-to-Text API." As a result, it generates sentiment data to identify the user's emotional state (e.g., relaxed, excited).

[0392] Step 3:

[0393] The server uses the analyzed sentiment data to run a recommendation model using TensorFlow or PyTorch. The sentiment data obtained in step 2 is input to the model, and it outputs a list of optimal content based on the user's psychological state.

[0394] Step 4:

[0395] The server adjusts the price of specified content based on dynamic pricing. Using the generated content list as input, it applies a pre-configured pricing algorithm to determine the optimal price. The output is a final content list containing the adjusted prices.

[0396] Step 5:

[0397] The server sends a content list and pricing information optimized for the user's device. This allows the user to browse and purchase content that suits their mood at an appropriate price. The content list and prices obtained in step 4 are used as input, and the information to be presented to the user is sent as output.

[0398] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0399] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0400] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0401] [Third Embodiment]

[0402] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0403] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0404] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0405] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0406] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0407] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0408] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0409] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0410] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0411] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0412] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0413] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0414] This invention provides a marketplace system that enables content creators to properly protect their works and facilitate monetization. This system functions around three main components: a server, terminals, and users (content creators).

[0415] First, the system starts processing when the user uploads their content from their device to the server. Upon receiving this content, the server first generates a digital fingerprint. This digital fingerprint is a technology used to uniquely identify the content, thereby protecting the rights to the work.

[0416] Next, the server records the generated digital fingerprint using blockchain technology. Because blockchain is difficult to tamper with, this ensures the authenticity of the content. Furthermore, it also provides a function to automatically and continuously monitor for misuse of content across the entire internet. If a breach is detected, the server immediately sends a notification to the user prompting them to take the necessary action.

[0417] In terms of monetization, the server analyzes the user's past sales data and market trends to suggest appropriate pricing. Prices are dynamically adjusted, enabling more market-adapted monetization. Users can review the displayed price on their device and make a final decision. Furthermore, an optimized algorithm is applied to ensure that creators receive fair profits.

[0418] Furthermore, the server accepts collaboration requests from companies and recommends appropriate creators accordingly. This allows users to gain more collaboration opportunities and secure new revenue streams.

[0419] For example, when a user uploads their own music content to the system, the server generates an identification fingerprint of the music and creates a record to protect copyright. It also analyzes the popularity and trends of the music and suggests the most effective selling price at that time. As a result, users can confidently offer their work and earn revenue.

[0420] As described above, the present invention is a system that aims to solve the numerous challenges faced by content creators and to create an environment in which they can concentrate on their creative activities.

[0421] The following describes the processing flow.

[0422] Step 1:

[0423] Users upload their content to the marketplace from their devices. The server receives this request and retrieves the content data.

[0424] Step 2:

[0425] The server generates a digital fingerprint from the retrieved content. This digital fingerprint is created as a unique identifier by analyzing the content's properties.

[0426] Step 3:

[0427] The server records the generated digital fingerprint using blockchain technology. This record protects the rights to the content and allows for action to be taken if objections arise at a later date.

[0428] Step 4:

[0429] For content uploaded by users, the server activates an AI function that monitors the internet to ensure it is not being misused. This monitoring is performed regularly, and if similar content is detected, a notification is sent to the user.

[0430] Step 5:

[0431] The server analyzes the user's past sales data and current market trends. Based on this, it calculates the optimal price for uploaded content and proposes it to the user.

[0432] Step 6:

[0433] The user reviews the price offer provided by the server on their device. If the user agrees, they approve the price, and the content sale begins at the applied price.

[0434] Step 7:

[0435] The server tracks sales data and distributes revenue to users based on sales. An optimized algorithm is used to ensure that revenue is distributed fairly.

[0436] Step 8:

[0437] When a collaboration request is received by the server from a company, the server analyzes the request, selects the most suitable creator, and notifies them. The user checks this notification on their device and proceeds with the necessary collaboration procedures.

[0438] (Example 1)

[0439] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0440] There are challenges in efficiently and securely managing data while addressing issues such as the misuse of data created by information providers on the internet and the infringement of their rights, as well as ensuring appropriate pricing and opportunities for collaboration.

[0441] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0442] In this invention, the server includes means for information providers to transmit data, means for generating a unique certificate based on the data, means for registering the unique certificate on a distributed recording medium, means for detecting unauthorized use of the data on an information communication network, means for outputting a notification when unauthorized use is identified, means for analyzing data transaction information and market information and suggesting an appropriate price, and means for selecting and proposing appropriate information providers in order to promote cooperation with corporations. This creates an environment in which information providers can provide data with peace of mind and enables them to obtain new opportunities through optimal pricing and collaboration.

[0443] An "information provider" is an entity that provides data it creates or owns to a system and has it managed and used by the system.

[0444] "Data" refers to digital content, including media files, documents, or other information transmitted by an information provider.

[0445] "Unique proof" is identification information generated based on data, which uniquely identifies that data and protects rights.

[0446] A "distributed recording medium" is a technology for protecting digital information from tampering and for permanently recording it, and typically includes blockchain technology.

[0447] An "information and communication network" refers to the network infrastructure used for sending and receiving data, including the Internet.

[0448] "Unauthorized use" refers to the act of using data without the permission of the information provider, and constitutes an infringement of rights.

[0449] A "notification" is a message sent to the information provider to warn or inform them when unauthorized use is identified.

[0450] "Transaction information" refers to historical data regarding the past sale and use of data.

[0451] "Market information" refers to information about current economic and consumer trends that influence the value and positioning of data.

[0452] A "legal entity" is an organization or company that engages in business partnerships or collaborations with data and information providers.

[0453] This invention provides a system for information providers to securely manage and appropriately monetize their data. The system consists of three components: a server, a terminal, and the information provider who acts as the user.

[0454] The user first uploads data to the system using a device. This device can be a desktop PC, laptop, or mobile device, and must have a standard internet connection. The user selects and uploads data using a dedicated app or web browser on the device, with an intuitive interface.

[0455] The server applies the SHA-256 algorithm to the received data to generate a unique digital fingerprint. This digital fingerprint uniquely identifies the data and protects ownership rights. Next, the server registers the generated digital fingerprint on the blockchain platform. This registration process ensures that data ownership and access records are securely stored and trusted.

[0456] Furthermore, the server operates dedicated monitoring software to detect unauthorized use of data on the internet. This software crawls a wide range of websites and platforms, searching for any matches with the uploaded data. If unauthorized use is detected, the server immediately sends an alert notification to the user, including specific instructions on how to proceed.

[0457] In terms of monetization, the server uses a generative AI model based on Python to analyze transaction and market information. This allows it to dynamically suggest appropriate prices. For example, the server can provide users with specific suggestions such as, "Based on past sales history, we suggest a price of XX for this data."

[0458] To facilitate collaboration with companies, the server accepts partnership requests via a CRM system and uses a generative AI model to select appropriate information providers. This allows users to increase their opportunities to generate new revenue streams.

[0459] As described above, this system solves various challenges faced by information providers and creates an environment where they can manage and provide data with confidence. An example of a prompt using this system would be, "Analyze and report what a fair market price would be for this data." In response to this prompt, the generating AI model provides the user with a market-value suggestion based on historical data.

[0460] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0461] Step 1:

[0462] Users upload their data to the system using a terminal. This data is in digital format and includes music, videos, images, or document files. The terminal sends this data to the server, completing the upload. The output of this process is the original data file stored on the server.

[0463] Step 2:

[0464] The server receives the uploaded data and generates a digital fingerprint using the SHA-256 algorithm. This algorithm converts the input data into a unique hash value, generating a unique proof corresponding to each piece of data. The output is a digital fingerprint for identifying the data.

[0465] Step 3:

[0466] The server registers the generated digital fingerprint on a distributed recording medium, namely the blockchain. The input is the generated digital fingerprint, and a transaction is created using blockchain technology, which is then recorded on the ledger. The output is the completion of registration on the tamper-proof blockchain.

[0467] Step 4:

[0468] The server crawls each website on the internet and monitors for unauthorized use of uploaded data. Inputs are digital fingerprints and crawled website content data, which are compared to identify inconsistencies. Outputs are warning notifications if infringement is detected.

[0469] Step 5:

[0470] The server analyzes transaction and market data using machine learning models to perform dynamic pricing. Inputs are historical sales data and current market data, and a generative AI model is used to calculate the optimal price. The output is a price suggestion for the user.

[0471] Step 6:

[0472] The server receives partnership requests from companies and, through the CRM system, uses a generative AI model to select appropriate information providers. The inputs are the company's partnership requirements and the information provider's profile data. Based on this, a recommendation algorithm operates and outputs a list of optimal candidates. This process gives the user or company the opportunity to collaborate with the candidates.

[0473] (Application Example 1)

[0474] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0475] In today's digital content market, there is a lack of systems that allow content creators to protect their works from misuse and to monetize them appropriately. Furthermore, the lack of means to offer optimal transaction terms and effectively build cooperative relationships with commercial organizations means that content creators are missing out on opportunities to earn legitimate profits.

[0476] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0477] In this invention, the server includes means for inputting data, means for generating unique identification information, means for recording the identification information on a distributed recording medium, means for monitoring unauthorized use of data on an information and communication network, and means for evaluating the data and analyzing market information to present appropriate transaction terms. This enables content creators to protect their works, effectively monetize them, and facilitate cooperation with commercial organizations.

[0478] A "content creator" is someone who creates and disseminates digital works and data.

[0479] "Data" refers to the information and materials input by content creators, which are then processed by the system.

[0480] "Identifying information" refers to unique information generated to uniquely identify data, and its purpose is protection.

[0481] A "distributed recording medium" is a technological foundation that has the characteristic of making it difficult to change information once it is recorded, and includes ledger technology.

[0482] An "information and communication network" refers to a communication infrastructure that enables the exchange and distribution of data, including the internet.

[0483] "Unauthorized use" refers to the act of using data or its contents without permission by someone without authorization.

[0484] "Terms of trade" refer to the conditions and prices proposed when content creators exchange their data in the market.

[0485] A "commercial organization" refers to a broad range of companies and groups involved in economic activities, and is a target for partnerships with content creators.

[0486] This invention is configured as a system for content creators to securely handle their works in the digital space. Users input data using a terminal, which then transmits it to a server.

[0487] The server generates unique identification information based on the data received from the user. This identification information is obtained by creating a digital fingerprint using a hash algorithm. The obtained identification information is recorded using a decentralized recording medium, specifically the Ethereum blockchain. This makes the identification information difficult to tamper with, guaranteeing the reliability of the data.

[0488] Furthermore, the server monitors for unauthorized use of data via the information and communication network. Using web scraping techniques, it continuously searches for similar content elsewhere. If unauthorized use is detected, a notification is immediately sent to the user. This utilizes real-time data processing using AWS Lambda.

[0489] The server further uses Python's Scikit-Learn to evaluate data and analyze market information, then presents users with appropriate trading conditions. This allows users to obtain accurate information based on market trends.

[0490] To facilitate collaboration with commercial organizations, the server has a function to select and suggest the most suitable data generators. This involves performing real-time data analysis using cloud computing and notifying the generators.

[0491] As a concrete example, when a user uploads video content related to natural scenery, identification information is generated through Creative Guardian and recorded on the Ethereum blockchain. If this content is used without permission on social media, the user receives a prompt notification. Furthermore, a price based on market trends is presented, allowing the user to distribute the content with confidence.

[0492] An example of a prompt for the generating AI model might be: "Propose the best price to protect and sell the content under the following conditions: video content, natural scenery, based on market trends in December 2023." This system would create an environment where content creators can confidently offer their work and earn revenue.

[0493] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0494] Step 1:

[0495] The user inputs and uploads digital content using a terminal. The input is the user's content file. The terminal sends this file to the server. The output is data ready for the server to receive. This creates the foundation for proceeding to the next processing step.

[0496] Step 2:

[0497] The server receives uploaded content files and generates a digital fingerprint. User content data is required as input. The server applies a hash algorithm to generate a unique identifier (digital fingerprint) for the content. The generated identifier is obtained as output. This information is used to ensure the integrity of the data.

[0498] Step 3:

[0499] The server records the generated identification information on the Ethereum blockchain. The input is the identification information obtained in the previous step. The server utilizes an API for saving data to the blockchain and records this information on a distributed storage medium. The output is the location information where the identification information is recorded. This ensures that the identification information is not tampered with.

[0500] Step 4:

[0501] The server monitors for misuse on the internet via the information and communication network. Its inputs include recorded identification information and related data. The server uses web scraping techniques to detect similar content on the internet. The output provides warning information if misuse is detected. This enables early detection of misuse.

[0502] Step 5:

[0503] The server evaluates data and analyzes market information to present appropriate trading conditions to the user. Input includes market trend data and user content data. The server uses Python's Scikit-Learn to analyze this data and predicts optimal trading conditions using a generation AI model. The output provides recommended trading conditions, allowing the user to maximize their profits.

[0504] Step 6:

[0505] The user reviews the transaction terms presented on the terminal and makes a final decision. The transaction terms sent from the server are displayed as input. The user reviews the terms through the terminal interface and chooses to accept or modify them. The user's decision information is provided as output. This decision directly impacts the sale of the content.

[0506] This will enable users to effectively facilitate secure content transactions and monetization.

[0507] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0508] This invention enhances the user experience by adding the functionality of an emotion engine to conventional content marketplace systems. In this system, the server, terminal, and user work together to achieve optimal content display and price adjustments that reflect the user's emotions.

[0509] First, a new process incorporating an emotion engine is implemented in the traditional user uploading process using their device. The user's device collects emotion data through the user's webcam and microphone and sends it to the server. The server uses the emotion engine to analyze the collected data and identify the emotions the user is currently experiencing.

[0510] The identified emotion data is reflected in the content the server displays to the user and the content it recommends. For example, if a user is relaxed, the server will prioritize displaying calming content that matches that emotion. Conversely, if a user is excited, it can provide more interactive content.

[0511] Furthermore, by leveraging feedback from the emotion engine, the server can also influence pricing. Specifically, if the server determines that a user has an emotion indicating a willingness to purchase, it can dynamically adjust the price to make it more appealing to the user.

[0512] For example, suppose a user is viewing music content, and the device analyzes the user's facial expressions using an emotion engine and determines that the user is relaxed. In this case, the server recommends music related to relaxation and offers some of them at a special price to make the user's choice easier.

[0513] Thus, the present invention aims to improve the user experience and maximize the benefits for creators and the marketplace as a whole by capturing the user's psychological state and reflecting it in content suggestions and pricing.

[0514] The following describes the processing flow.

[0515] Step 1:

[0516] The user logs into the content marketplace using their device and prepares to view content. At this point, the device activates its webcam and microphone, collecting data on the user's facial expressions and voice tone.

[0517] Step 2:

[0518] User emotion data collected on the device is sent to the server in real time. The server receives this data and uses an emotion engine to perform a detailed emotion analysis. This analysis identifies the specific emotional state the user is currently experiencing, such as joy, sadness, or surprise.

[0519] Step 3:

[0520] The server selects the most suitable content for the user based on the emotional state identified through analysis. For example, if the user indicates a relaxed state, it recommends calming music or quiet video content. It also displays a list of selected content on the user's device.

[0521] Step 4:

[0522] When a user selects content they are interested in from the suggested options, the server displays detailed information about that content, along with a price that takes sentiment analysis into account, on the user's device. For example, if the user is very excited, a special offer may be presented to encourage a purchase.

[0523] Step 5:

[0524] When a user decides to make a purchase, the terminal sends order information to the server. The server processes this information and completes the purchase process. The system also records the user's emotional state and purchase behavior data, which is used to improve the accuracy of future recommendations.

[0525] This entire process allows users to enjoy content that matches their emotions, and also enables the marketplace to achieve higher user satisfaction and more efficient monetization.

[0526] (Example 2)

[0527] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0528] Traditional information sharing platforms failed to provide information that took into account user emotions, and were unable to offer an experience optimized for individual users. Furthermore, they struggled to adjust financial value in response to dynamically changing market conditions, failing to provide an optimal financial environment for both information producers and consumers.

[0529] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0530] In this invention, the server includes means for a user to transmit information, means for analyzing the information and extracting sentiment data, and means for displaying information suitable for the user based on the sentiment data. This enables optimized information provision based on the user's emotions and adjustment of financial value in response to dynamic markets.

[0531] "User" refers to an individual or legal entity that transmits or receives information using this system.

[0532] "Information" refers to data and content that users send or receive through the system.

[0533] "Emotional data" refers to data about the emotional state of users extracted through the analysis of information.

[0534] "Financial value" refers to the transaction price or value associated with information, and it can be dynamically adjusted.

[0535] "Combined technologies" refer to distributed ledger technologies and similar technologies used to record financial values ​​and other digital data.

[0536] "Information creator" refers to an entity that creates and provides information within a marketplace.

[0537] A "server" refers to a central computer system that receives, processes, and transmits information.

[0538] This system involves interaction between users, terminals, and servers to provide information that takes into account the user's emotional state. Users can upload information to the marketplace through the interface.

[0539] The device uses specific hardware components such as a webcam and microphone to collect user emotional data. The collected data is sent to a server in real time using dedicated software called an emotion engine. The emotion engine uses a generative AI model based on machine learning to analyze the received facial and audio data and identify the user's emotional state.

[0540] The server uses an emotion engine to analyze emotional data and select and present the most relevant information to the user. For example, if the server determines that the user is relaxed, music and videos suitable for relaxation will be prioritized. The server also features dynamic pricing, automatically adjusting the financial value of information according to market conditions. This allows it to provide optimal trading conditions that are constantly changing.

[0541] As a concrete example, consider a situation where a user is browsing music content. If the device captures the user's facial expression and analyzes it to indicate that the user is experiencing joy, the server recommends enjoyable music or videos that are appropriate for that emotion. Furthermore, purchase options are presented with pricing optimized for that moment.

[0542] As an example of a prompt message for a generative AI model, you could say, "Generate a list of music content to recommend when the user is determined to be relaxed," which would enable the model to provide information based on that.

[0543] Thus, through the concrete implementation of the invention, users can receive personalized information tailored to their emotions and engage in rational transactions in accordance with market trends.

[0544] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0545] Step 1:

[0546] Users upload information of their choice to the marketplace. In this process, users directly select content such as images, videos, and text via their mobile devices or computers and send the information to the system by clicking a submit button. The input here is the user's information, and the output is the completion of information transmission by the device.

[0547] Step 2:

[0548] During the upload process, the device collects the user's biometric information using a webcam and microphone. Specifically, it captures the user's facial expressions in real time and records audio data. This biometric information serves as input, and the output is obtained by sending it to the server as digital data.

[0549] Step 3:

[0550] The server receives biometric data transmitted from the terminal and performs analysis using an emotion engine. This process uses a generative AI model to process the input biometric data and identify the user's emotional state (e.g., joy, sadness, relaxation). The output is the analyzed emotion data.

[0551] Step 4:

[0552] The server selects and provides the most relevant information to the user based on emotional data. For example, if the analysis determines that the user is in a relaxed state, the server will prioritize recommending music and videos suitable for relaxation. Here, the input is the analyzed emotional data, and the output is the information displayed to the user.

[0553] Step 5:

[0554] The server dynamically adjusts financial value based on market and transactional data. Specifically, if user sentiment indicates a willingness to buy, the server uses prompt messages to generate optimal pricing and presents the user with discount options. The input is market and sentiment data, and the output is dynamically adjusted financial value.

[0555] Step 6:

[0556] Users can review personalized information and adjusted financial values ​​provided by the server and make their own decisions regarding the purchase and use of that information. The user's final decision is based on the information presented as output from the server.

[0557] (Application Example 2)

[0558] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0559] Traditional content distribution platforms lack personalized content recommendations that take into account users' emotional states, and emotion-based pricing, making it difficult to improve the user experience. Furthermore, insufficient measures against content misuse hinder the profitability of content creators.

[0560] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0561] In this invention, the server includes means for sensing the user's psychological state through emotion analysis means, means for presenting optimal information based on the psychological state, and means for dynamic price adjustment based on the psychological state. This enables personalized content recommendations and emotion-based price adjustments that respond to the user's emotions, and in addition, it enables appropriate monitoring of misuse of content.

[0562] "Emotional analysis methods" are technologies that determine a user's psychological state based on their facial expressions and voice, and acquire that data.

[0563] "Psychological state" refers to the user's emotions, mood, and level of excitement, and is evaluated through emotion analysis methods.

[0564] "Means of presenting information" refers to the process of displaying content and pricing information optimized according to the user's psychological state.

[0565] A "dynamic price adjustment mechanism" is a system that changes prices in real time based on the user's psychological state and market data.

[0566] A "content creator" refers to an individual or legal entity that produces digital content and uploads it to a platform.

[0567] A "unique identifier" is a unique number or code assigned to uploaded content, which is managed using database technology.

[0568] "Database technology" refers to systems and platforms that structurally store and manage digital information and efficiently retrieve that information as needed.

[0569] "Unauthorized use" refers to acts such as the unauthorized use of content or the infringement of intellectual property rights.

[0570] "Means of sending notifications" refers to a communication process used to warn or inform relevant parties when fraudulent activity is detected.

[0571] This system senses the user's psychological state and performs a series of processes to recommend content and dynamically adjust prices based on that state. The server uses cameras and microphones built into devices such as smartphones and tablets as means of sentiment analysis. The devices collect data on the user's psychological state from their facial expressions and voice through these devices and transmit it to the server.

[0572] The server uses Google Cloud's "Cloud Vision API" and "Speech-to-Text API" to analyze the received sentiment data. Based on the analysis results, a machine learning model using TensorFlow or PyTorch selects and recommends content that best matches the user's emotions.

[0573] Furthermore, the server uses database technology to manage unique identifiers and features an abuse monitoring system that monitors content misuse in real time. This ensures that notifications are sent immediately if content is misused.

[0574] For example, when a user is enjoying a movie through this system, if the camera and microphone detect that the user is relaxed, the system will recommend a comedy movie and offer it at a special price. In this way, the system provides the optimal entertainment experience according to the user's mood.

[0575] Examples of prompt statements for a generative AI model are as follows:

[0576] "As a way to improve the user's video viewing experience, please provide ideas for a system that analyzes user emotions and suggests the best movies and discounted prices based on those emotions. The emotion analysis would use facial expression data and include real-time updated price adjustments."

[0577] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0578] Step 1:

[0579] The device captures the user's facial expressions and voice through its camera and microphone. It acquires real-time video and audio data of the user as input. This data is temporarily stored on the device before being sent to the server.

[0580] Step 2:

[0581] The server performs sentiment analysis using the received video and audio data. It receives video and audio data transmitted from the terminal as input and analyzes it using Google Cloud's "Cloud Vision API" and "Speech-to-Text API." As a result, it generates sentiment data to identify the user's emotional state (e.g., relaxed, excited).

[0582] Step 3:

[0583] The server uses the analyzed sentiment data to run a recommendation model using TensorFlow or PyTorch. The sentiment data obtained in step 2 is input to the model, and it outputs a list of optimal content based on the user's psychological state.

[0584] Step 4:

[0585] The server adjusts the price of specified content based on dynamic pricing. Using the generated content list as input, it applies a pre-configured pricing algorithm to determine the optimal price. The output is a final content list containing the adjusted prices.

[0586] Step 5:

[0587] The server sends a content list and pricing information optimized for the user's device. This allows the user to browse and purchase content that suits their mood at an appropriate price. The content list and prices obtained in step 4 are used as input, and the information to be presented to the user is sent as output.

[0588] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0589] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0590] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0591] [Fourth Embodiment]

[0592] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0593] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0594] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0595] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0596] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0597] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0598] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0599] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0600] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0601] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0602] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0603] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0604] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0605] This invention provides a marketplace system that enables content creators to properly protect their works and facilitate monetization. This system functions around three main components: a server, terminals, and users (content creators).

[0606] First, the system starts processing when the user uploads their content from their device to the server. Upon receiving this content, the server first generates a digital fingerprint. This digital fingerprint is a technology used to uniquely identify the content, thereby protecting the rights to the work.

[0607] Next, the server records the generated digital fingerprint using blockchain technology. Because blockchain is difficult to tamper with, this ensures the authenticity of the content. Furthermore, it also provides a function to automatically and continuously monitor for misuse of content across the entire internet. If a breach is detected, the server immediately sends a notification to the user prompting them to take the necessary action.

[0608] In terms of monetization, the server analyzes the user's past sales data and market trends to suggest appropriate pricing. Prices are dynamically adjusted, enabling more market-adapted monetization. Users can review the displayed price on their device and make a final decision. Furthermore, an optimized algorithm is applied to ensure that creators receive fair profits.

[0609] Furthermore, the server accepts collaboration requests from companies and recommends appropriate creators accordingly. This allows users to gain more collaboration opportunities and secure new revenue streams.

[0610] For example, when a user uploads their own music content to the system, the server generates an identification fingerprint of the music and creates a record to protect copyright. It also analyzes the popularity and trends of the music and suggests the most effective selling price at that time. As a result, users can confidently offer their work and earn revenue.

[0611] As described above, the present invention is a system that aims to solve the numerous challenges faced by content creators and to create an environment in which they can concentrate on their creative activities.

[0612] The following describes the processing flow.

[0613] Step 1:

[0614] Users upload their content to the marketplace from their devices. The server receives this request and retrieves the content data.

[0615] Step 2:

[0616] The server generates a digital fingerprint from the retrieved content. This digital fingerprint is created as a unique identifier by analyzing the content's properties.

[0617] Step 3:

[0618] The server records the generated digital fingerprint using blockchain technology. This record protects the rights to the content and allows for action to be taken if objections arise at a later date.

[0619] Step 4:

[0620] For content uploaded by users, the server activates an AI function that monitors the internet to ensure it is not being misused. This monitoring is performed regularly, and if similar content is detected, a notification is sent to the user.

[0621] Step 5:

[0622] The server analyzes the user's past sales data and current market trends. Based on this, it calculates the optimal price for uploaded content and proposes it to the user.

[0623] Step 6:

[0624] The user reviews the price offer provided by the server on their device. If the user agrees, they approve the price, and the content sale begins at the applied price.

[0625] Step 7:

[0626] The server tracks sales data and distributes revenue to users based on sales. An optimized algorithm is used to ensure that revenue is distributed fairly.

[0627] Step 8:

[0628] When a collaboration request is received by the server from a company, the server analyzes the request, selects the most suitable creator, and notifies them. The user checks this notification on their device and proceeds with the necessary collaboration procedures.

[0629] (Example 1)

[0630] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0631] There are challenges in efficiently and securely managing data while addressing issues such as the misuse of data created by information providers on the internet and the infringement of their rights, as well as ensuring appropriate pricing and opportunities for collaboration.

[0632] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0633] In this invention, the server includes means for information providers to transmit data, means for generating a unique certificate based on the data, means for registering the unique certificate on a distributed recording medium, means for detecting unauthorized use of the data on an information communication network, means for outputting a notification when unauthorized use is identified, means for analyzing data transaction information and market information and suggesting an appropriate price, and means for selecting and proposing appropriate information providers in order to promote cooperation with corporations. This creates an environment in which information providers can provide data with peace of mind and enables them to obtain new opportunities through optimal pricing and collaboration.

[0634] An "information provider" is an entity that provides data it creates or owns to a system and has it managed and used by the system.

[0635] "Data" refers to digital content, including media files, documents, or other information transmitted by an information provider.

[0636] "Unique proof" is identification information generated based on data, which uniquely identifies that data and protects rights.

[0637] A "distributed recording medium" is a technology for protecting digital information from tampering and for permanently recording it, and typically includes blockchain technology.

[0638] An "information and communication network" refers to the network infrastructure used for sending and receiving data, including the Internet.

[0639] "Unauthorized use" refers to the act of using data without the permission of the information provider, and constitutes an infringement of rights.

[0640] A "notification" is a message sent to the information provider to warn or inform them when unauthorized use is identified.

[0641] "Transaction information" refers to historical data regarding the past sale and use of data.

[0642] "Market information" refers to information about current economic and consumer trends that influence the value and positioning of data.

[0643] A "legal entity" is an organization or company that engages in business partnerships or collaborations with data and information providers.

[0644] This invention provides a system for information providers to securely manage and appropriately monetize their data. The system consists of three components: a server, a terminal, and the information provider who acts as the user.

[0645] The user first uploads data to the system using a device. This device can be a desktop PC, laptop, or mobile device, and must have a standard internet connection. The user selects and uploads data using a dedicated app or web browser on the device, with an intuitive interface.

[0646] The server applies the SHA-256 algorithm to the received data to generate a unique digital fingerprint. This digital fingerprint uniquely identifies the data and protects ownership rights. Next, the server registers the generated digital fingerprint on the blockchain platform. This registration process ensures that data ownership and access records are securely stored and trusted.

[0647] Furthermore, the server operates dedicated monitoring software to detect unauthorized use of data on the internet. This software crawls a wide range of websites and platforms, searching for any matches with the uploaded data. If unauthorized use is detected, the server immediately sends an alert notification to the user, including specific instructions on how to proceed.

[0648] In terms of monetization, the server uses a generative AI model based on Python to analyze transaction and market information. This allows it to dynamically suggest appropriate prices. For example, the server can provide users with specific suggestions such as, "Based on past sales history, we suggest a price of XX for this data."

[0649] To facilitate collaboration with companies, the server accepts partnership requests via a CRM system and uses a generative AI model to select appropriate information providers. This allows users to increase their opportunities to generate new revenue streams.

[0650] As described above, this system solves various challenges faced by information providers and creates an environment where they can manage and provide data with confidence. An example of a prompt using this system would be, "Analyze and report what a fair market price would be for this data." In response to this prompt, the generating AI model provides the user with a market-value suggestion based on historical data.

[0651] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0652] Step 1:

[0653] Users upload their data to the system using a terminal. This data is in digital format and includes music, videos, images, or document files. The terminal sends this data to the server, completing the upload. The output of this process is the original data file stored on the server.

[0654] Step 2:

[0655] The server receives the uploaded data and generates a digital fingerprint using the SHA-256 algorithm. This algorithm converts the input data into a unique hash value, generating a unique proof corresponding to each piece of data. The output is a digital fingerprint for identifying the data.

[0656] Step 3:

[0657] The server registers the generated digital fingerprint on a distributed recording medium, namely the blockchain. The input is the generated digital fingerprint, and a transaction is created using blockchain technology, which is then recorded on the ledger. The output is the completion of registration on the tamper-proof blockchain.

[0658] Step 4:

[0659] The server crawls each website on the internet and monitors for unauthorized use of uploaded data. Inputs are digital fingerprints and crawled website content data, which are compared to identify inconsistencies. Outputs are warning notifications if infringement is detected.

[0660] Step 5:

[0661] The server analyzes transaction and market data using machine learning models to perform dynamic pricing. Inputs are historical sales data and current market data, and a generative AI model is used to calculate the optimal price. The output is a price suggestion for the user.

[0662] Step 6:

[0663] The server receives partnership requests from companies and, through the CRM system, uses a generative AI model to select appropriate information providers. The inputs are the company's partnership requirements and the information provider's profile data. Based on this, a recommendation algorithm operates and outputs a list of optimal candidates. This process gives the user or company the opportunity to collaborate with the candidates.

[0664] (Application Example 1)

[0665] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0666] In today's digital content market, there is a lack of systems that allow content creators to protect their works from misuse and to monetize them appropriately. Furthermore, the lack of means to offer optimal transaction terms and effectively build cooperative relationships with commercial organizations means that content creators are missing out on opportunities to earn legitimate profits.

[0667] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0668] In this invention, the server includes means for inputting data, means for generating unique identification information, means for recording the identification information on a distributed recording medium, means for monitoring unauthorized use of data on an information and communication network, and means for evaluating the data and analyzing market information to present appropriate transaction terms. This enables content creators to protect their works, effectively monetize them, and facilitate cooperation with commercial organizations.

[0669] A "content creator" is someone who creates and disseminates digital works and data.

[0670] "Data" refers to the information and materials input by content creators, which are then processed by the system.

[0671] "Identifying information" refers to unique information generated to uniquely identify data, and its purpose is protection.

[0672] A "distributed recording medium" is a technological foundation that has the characteristic of making it difficult to change information once it is recorded, and includes ledger technology.

[0673] An "information and communication network" refers to a communication infrastructure that enables the exchange and distribution of data, including the internet.

[0674] "Unauthorized use" refers to the act of using data or its contents without permission by someone without authorization.

[0675] "Terms of trade" refer to the conditions and prices proposed when content creators exchange their data in the market.

[0676] A "commercial organization" refers to a broad range of companies and groups involved in economic activities, and is a target for partnerships with content creators.

[0677] This invention is configured as a system for content creators to securely handle their works in the digital space. Users input data using a terminal, which then transmits it to a server.

[0678] The server generates unique identification information based on the data received from the user. This identification information is obtained by creating a digital fingerprint using a hash algorithm. The obtained identification information is recorded using a decentralized recording medium, specifically the Ethereum blockchain. This makes the identification information difficult to tamper with, guaranteeing the reliability of the data.

[0679] Furthermore, the server monitors for unauthorized use of data via the information and communication network. Using web scraping techniques, it continuously searches for similar content elsewhere. If unauthorized use is detected, a notification is immediately sent to the user. This utilizes real-time data processing using AWS Lambda.

[0680] The server further uses Python's Scikit-Learn to evaluate data and analyze market information, then presents users with appropriate trading conditions. This allows users to obtain accurate information based on market trends.

[0681] To facilitate collaboration with commercial organizations, the server has a function to select and suggest the most suitable data generators. This involves performing real-time data analysis using cloud computing and notifying the generators.

[0682] As a concrete example, when a user uploads video content related to natural scenery, identification information is generated through Creative Guardian and recorded on the Ethereum blockchain. If this content is used without permission on social media, the user receives a prompt notification. Furthermore, a price based on market trends is presented, allowing the user to distribute the content with confidence.

[0683] An example of a prompt for the generating AI model might be: "Propose the best price to protect and sell the content under the following conditions: video content, natural scenery, based on market trends in December 2023." This system would create an environment where content creators can confidently offer their work and earn revenue.

[0684] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0685] Step 1:

[0686] The user inputs and uploads digital content using a terminal. The input is the user's content file. The terminal sends this file to the server. The output is data ready for the server to receive. This creates the foundation for proceeding to the next processing step.

[0687] Step 2:

[0688] The server receives uploaded content files and generates a digital fingerprint. User content data is required as input. The server applies a hash algorithm to generate a unique identifier (digital fingerprint) for the content. The generated identifier is obtained as output. This information is used to ensure the integrity of the data.

[0689] Step 3:

[0690] The server records the generated identification information on the Ethereum blockchain. The input is the identification information obtained in the previous step. The server utilizes an API for saving data to the blockchain and records this information on a distributed storage medium. The output is the location information where the identification information is recorded. This ensures that the identification information is not tampered with.

[0691] Step 4:

[0692] The server monitors for misuse on the internet via the information and communication network. Its inputs include recorded identification information and related data. The server uses web scraping techniques to detect similar content on the internet. The output provides warning information if misuse is detected. This enables early detection of misuse.

[0693] Step 5:

[0694] The server evaluates data and analyzes market information to present appropriate trading conditions to the user. Input includes market trend data and user content data. The server uses Python's Scikit-Learn to analyze this data and predicts optimal trading conditions using a generation AI model. The output provides recommended trading conditions, allowing the user to maximize their profits.

[0695] Step 6:

[0696] The user reviews the transaction terms presented on the terminal and makes a final decision. The transaction terms sent from the server are displayed as input. The user reviews the terms through the terminal interface and chooses to accept or modify them. The user's decision information is provided as output. This decision directly impacts the sale of the content.

[0697] This will enable users to effectively facilitate secure content transactions and monetization.

[0698] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0699] This invention enhances the user experience by adding the functionality of an emotion engine to conventional content marketplace systems. In this system, the server, terminal, and user work together to achieve optimal content display and price adjustments that reflect the user's emotions.

[0700] First, a new process incorporating an emotion engine is implemented in the traditional user uploading process using their device. The user's device collects emotion data through the user's webcam and microphone and sends it to the server. The server uses the emotion engine to analyze the collected data and identify the emotions the user is currently experiencing.

[0701] The identified emotion data is reflected in the content the server displays to the user and the content it recommends. For example, if a user is relaxed, the server will prioritize displaying calming content that matches that emotion. Conversely, if a user is excited, it can provide more interactive content.

[0702] Furthermore, by leveraging feedback from the emotion engine, the server can also influence pricing. Specifically, if the server determines that a user has an emotion indicating a willingness to purchase, it can dynamically adjust the price to make it more appealing to the user.

[0703] For example, suppose a user is viewing music content, and the device analyzes the user's facial expressions using an emotion engine and determines that the user is relaxed. In this case, the server recommends music related to relaxation and offers some of them at a special price to make the user's choice easier.

[0704] Thus, the present invention aims to improve the user experience and maximize the benefits for creators and the marketplace as a whole by capturing the user's psychological state and reflecting it in content suggestions and pricing.

[0705] The following describes the processing flow.

[0706] Step 1:

[0707] The user logs into the content marketplace using their device and prepares to view content. At this point, the device activates its webcam and microphone, collecting data on the user's facial expressions and voice tone.

[0708] Step 2:

[0709] User emotion data collected on the device is sent to the server in real time. The server receives this data and uses an emotion engine to perform a detailed emotion analysis. This analysis identifies the specific emotional state the user is currently experiencing, such as joy, sadness, or surprise.

[0710] Step 3:

[0711] The server selects the most suitable content for the user based on the emotional state identified through analysis. For example, if the user indicates a relaxed state, it recommends calming music or quiet video content. It also displays a list of selected content on the user's device.

[0712] Step 4:

[0713] When a user selects content they are interested in from the suggested options, the server displays detailed information about that content, along with a price that takes sentiment analysis into account, on the user's device. For example, if the user is very excited, a special offer may be presented to encourage a purchase.

[0714] Step 5:

[0715] When a user decides to make a purchase, the terminal sends order information to the server. The server processes this information and completes the purchase process. The system also records the user's emotional state and purchase behavior data, which is used to improve the accuracy of future recommendations.

[0716] This entire process allows users to enjoy content that matches their emotions, and also enables the marketplace to achieve higher user satisfaction and more efficient monetization.

[0717] (Example 2)

[0718] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0719] Traditional information sharing platforms failed to provide information that took into account user emotions, and were unable to offer an experience optimized for individual users. Furthermore, they struggled to adjust financial value in response to dynamically changing market conditions, failing to provide an optimal financial environment for both information producers and consumers.

[0720] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0721] In this invention, the server includes means for a user to transmit information, means for analyzing the information and extracting sentiment data, and means for displaying information suitable for the user based on the sentiment data. This enables optimized information provision based on the user's emotions and adjustment of financial value in response to dynamic markets.

[0722] "User" refers to an individual or legal entity that transmits or receives information using this system.

[0723] "Information" refers to data and content that users send or receive through the system.

[0724] "Emotional data" refers to data about the emotional state of users extracted through the analysis of information.

[0725] "Financial value" refers to the transaction price or value associated with information, and it can be dynamically adjusted.

[0726] "Combined technologies" refer to distributed ledger technologies and similar technologies used to record financial values ​​and other digital data.

[0727] "Information creator" refers to an entity that creates and provides information within a marketplace.

[0728] A "server" refers to a central computer system that receives, processes, and transmits information.

[0729] This system involves interaction between users, terminals, and servers to provide information that takes into account the user's emotional state. Users can upload information to the marketplace through the interface.

[0730] The device uses specific hardware components such as a webcam and microphone to collect user emotional data. The collected data is sent to a server in real time using dedicated software called an emotion engine. The emotion engine uses a generative AI model based on machine learning to analyze the received facial and audio data and identify the user's emotional state.

[0731] The server uses an emotion engine to analyze emotional data and select and present the most relevant information to the user. For example, if the server determines that the user is relaxed, music and videos suitable for relaxation will be prioritized. The server also features dynamic pricing, automatically adjusting the financial value of information according to market conditions. This allows it to provide optimal trading conditions that are constantly changing.

[0732] As a concrete example, consider a situation where a user is browsing music content. If the device captures the user's facial expression and analyzes it to indicate that the user is experiencing joy, the server recommends enjoyable music or videos that are appropriate for that emotion. Furthermore, purchase options are presented with pricing optimized for that moment.

[0733] As an example of a prompt message for a generative AI model, you could say, "Generate a list of music content to recommend when the user is determined to be relaxed," which would enable the model to provide information based on that.

[0734] Thus, through the concrete implementation of the invention, users can receive personalized information tailored to their emotions and engage in rational transactions in accordance with market trends.

[0735] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0736] Step 1:

[0737] Users upload information of their choice to the marketplace. In this process, users directly select content such as images, videos, and text via their mobile devices or computers and send the information to the system by clicking a submit button. The input here is the user's information, and the output is the completion of information transmission by the device.

[0738] Step 2:

[0739] During the upload process, the device collects the user's biometric information using a webcam and microphone. Specifically, it captures the user's facial expressions in real time and records audio data. This biometric information serves as input, and the output is obtained by sending it to the server as digital data.

[0740] Step 3:

[0741] The server receives biometric data transmitted from the terminal and performs analysis using an emotion engine. This process uses a generative AI model to process the input biometric data and identify the user's emotional state (e.g., joy, sadness, relaxation). The output is the analyzed emotion data.

[0742] Step 4:

[0743] The server selects and provides the most relevant information to the user based on emotional data. For example, if the analysis determines that the user is in a relaxed state, the server will prioritize recommending music and videos suitable for relaxation. Here, the input is the analyzed emotional data, and the output is the information displayed to the user.

[0744] Step 5:

[0745] The server dynamically adjusts financial value based on market and transactional data. Specifically, if user sentiment indicates a willingness to buy, the server uses prompt messages to generate optimal pricing and presents the user with discount options. The input is market and sentiment data, and the output is dynamically adjusted financial value.

[0746] Step 6:

[0747] Users can review personalized information and adjusted financial values ​​provided by the server and make their own decisions regarding the purchase and use of that information. The user's final decision is based on the information presented as output from the server.

[0748] (Application Example 2)

[0749] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0750] Traditional content distribution platforms lack personalized content recommendations that take into account users' emotional states, and emotion-based pricing, making it difficult to improve the user experience. Furthermore, insufficient measures against content misuse hinder the profitability of content creators.

[0751] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0752] In this invention, the server includes means for sensing the user's psychological state through emotion analysis means, means for presenting optimal information based on the psychological state, and means for dynamic price adjustment based on the psychological state. This enables personalized content recommendations and emotion-based price adjustments that respond to the user's emotions, and in addition, it enables appropriate monitoring of misuse of content.

[0753] "Emotional analysis methods" are technologies that determine a user's psychological state based on their facial expressions and voice, and acquire that data.

[0754] "Psychological state" refers to the user's emotions, mood, and level of excitement, and is evaluated through emotion analysis methods.

[0755] "Means of presenting information" refers to the process of displaying content and pricing information optimized according to the user's psychological state.

[0756] A "dynamic price adjustment mechanism" is a system that changes prices in real time based on the user's psychological state and market data.

[0757] A "content creator" refers to an individual or legal entity that produces digital content and uploads it to a platform.

[0758] A "unique identifier" is a unique number or code assigned to uploaded content, which is managed using database technology.

[0759] "Database technology" refers to systems and platforms that structurally store and manage digital information and efficiently retrieve that information as needed.

[0760] "Unauthorized use" refers to acts such as the unauthorized use of content or the infringement of intellectual property rights.

[0761] "Means of sending notifications" refers to a communication process used to warn or inform relevant parties when fraudulent activity is detected.

[0762] This system senses the user's psychological state and performs a series of processes to recommend content and dynamically adjust prices based on that state. The server uses cameras and microphones built into devices such as smartphones and tablets as means of sentiment analysis. The devices collect data on the user's psychological state from their facial expressions and voice through these devices and transmit it to the server.

[0763] The server uses Google Cloud's "Cloud Vision API" and "Speech-to-Text API" to analyze the received sentiment data. Based on the analysis results, a machine learning model using TensorFlow or PyTorch selects and recommends content that best matches the user's emotions.

[0764] Furthermore, the server uses database technology to manage unique identifiers and features an abuse monitoring system that monitors content misuse in real time. This ensures that notifications are sent immediately if content is misused.

[0765] For example, when a user is enjoying a movie through this system, if the camera and microphone detect that the user is relaxed, the system will recommend a comedy movie and offer it at a special price. In this way, the system provides the optimal entertainment experience according to the user's mood.

[0766] Examples of prompt statements for a generative AI model are as follows:

[0767] "As a way to improve the user's video viewing experience, please provide ideas for a system that analyzes user emotions and suggests the best movies and discounted prices based on those emotions. The emotion analysis would use facial expression data and include real-time updated price adjustments."

[0768] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0769] Step 1:

[0770] The device captures the user's facial expressions and voice through its camera and microphone. It acquires real-time video and audio data of the user as input. This data is temporarily stored on the device before being sent to the server.

[0771] Step 2:

[0772] The server performs sentiment analysis using the received video and audio data. It receives video and audio data transmitted from the terminal as input and analyzes it using Google Cloud's "Cloud Vision API" and "Speech-to-Text API." As a result, it generates sentiment data to identify the user's emotional state (e.g., relaxed, excited).

[0773] Step 3:

[0774] The server uses the analyzed sentiment data to run a recommendation model using TensorFlow or PyTorch. The sentiment data obtained in step 2 is input to the model, and it outputs a list of optimal content based on the user's psychological state.

[0775] Step 4:

[0776] The server adjusts the price of specified content based on dynamic pricing. Using the generated content list as input, it applies a pre-configured pricing algorithm to determine the optimal price. The output is a final content list containing the adjusted prices.

[0777] Step 5:

[0778] The server sends a content list and pricing information optimized for the user's device. This allows the user to browse and purchase content that suits their mood at an appropriate price. The content list and prices obtained in step 4 are used as input, and the information to be presented to the user is sent as output.

[0779] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0780] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0781] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0782] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0783] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0784] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0785] The inside of the Emotion Map 400 represents what's in your mind, while the outside represents what you're doing. Therefore, the further you go out the 400-coordinate scale, the more visible your emotions become (the more they manifest in your actions).

[0786] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0787] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0788] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0789] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0790] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0791] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0792] 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.

[0793] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0794] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0795] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0796] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0797] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0798] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0799] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0800] The following is further disclosed regarding the embodiments described above.

[0801] (Claim 1)

[0802] Means for content creators to upload content,

[0803] Means for generating a unique identifier based on the aforementioned content,

[0804] Means for recording the aforementioned unique identifier in ledger technology,

[0805] A means of monitoring the unauthorized use of the aforementioned content on the internet,

[0806] A means of sending notifications when unauthorized use is detected,

[0807] A system that includes this.

[0808] (Claim 2)

[0809] The system according to claim 1, further comprising means for analyzing sales data and market data of the aforementioned content and proposing an optimal price.

[0810] (Claim 3)

[0811] The system according to claim 1, further comprising means for selecting and proposing the most suitable content creator in order to support collaboration with companies.

[0812] "Example 1"

[0813] (Claim 1)

[0814] Means for information providers to transmit data,

[0815] Means for generating a unique proof based on the aforementioned data,

[0816] Means for registering the aforementioned unique proof in a distributed recording medium,

[0817] A means for detecting unauthorized use of the data on an information and communication network,

[0818] A means of outputting a notification when unauthorized use is identified,

[0819] A system that includes this.

[0820] (Claim 2)

[0821] The system according to claim 1, further comprising means for analyzing transaction information and market information of the aforementioned data and suggesting an appropriate price.

[0822] (Claim 3)

[0823] The system according to claim 1, further comprising means for selecting and proposing appropriate information providers in order to promote cooperation with corporations.

[0824] "Application Example 1"

[0825] (Claim 1)

[0826] A means for content creators to input data,

[0827] A means for generating unique identification information based on the aforementioned data,

[0828] means for recording the aforementioned identification information on a distributed recording medium,

[0829] Means for monitoring the unauthorized use of the aforementioned data on an information and communication network,

[0830] A means of sending notifications when fraudulent use is detected,

[0831] A means of evaluating the aforementioned data and analyzing market information to present appropriate trading conditions,

[0832] A system that includes this.

[0833] (Claim 2)

[0834] The system according to claim 1, further comprising means for confirming and deciding on the presented transaction conditions on the user's operating terminal.

[0835] (Claim 3)

[0836] The system according to claim 1, further comprising means for selecting and proposing the most suitable data generator in order to build cooperative relationships with commercial organizations.

[0837] "Example 2 of combining an emotion engine"

[0838] (Claim 1)

[0839] Means for users to transmit information,

[0840] A means for analyzing the aforementioned information and extracting emotional data,

[0841] A means for displaying information suitable for the user based on the aforementioned sentiment data,

[0842] A means for dynamically adjusting financial value based on the aforementioned information,

[0843] Means for recording the aforementioned financial value in composite technology,

[0844] A system that includes this.

[0845] (Claim 2)

[0846] The system according to claim 1, further comprising means for further analyzing sales data and market data using the aforementioned sentiment data and proposing an optimal price.

[0847] (Claim 3)

[0848] The system according to claim 1, further comprising means for selecting and proposing the most suitable information generator in order to support collaboration with other organizations.

[0849] "Application example 2 when combining with an emotional engine"

[0850] (Claim 1)

[0851] A means of sensing the user's psychological state through emotion analysis,

[0852] A means for presenting optimal information based on the aforementioned psychological state,

[0853] A dynamic price adjustment means based on the aforementioned psychological state,

[0854] A means for content creators to upload their content,

[0855] Means for generating a unique identifier based on the aforementioned content,

[0856] Means for recording the aforementioned unique identifier in a database technology,

[0857] A means of monitoring the unauthorized use of the aforementioned content online,

[0858] A means of sending notifications when fraudulent use is detected,

[0859] A system that includes this.

[0860] (Claim 2)

[0861] The system according to claim 1, further comprising means for analyzing the aforementioned consumer sentiment data and consumer preference data and proposing an optimal price.

[0862] (Claim 3)

[0863] The system according to claim 1, further comprising means for selecting and proposing the most suitable content creator in order to support collaboration with business entities. [Explanation of Symbols]

[0864] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for content creators to input data, A means for generating unique identification information based on the aforementioned data, means for recording the aforementioned identification information on a distributed recording medium, A means for monitoring the unauthorized use of the aforementioned data on an information and communication network, A means of sending notifications when fraudulent use is detected, A means of evaluating the aforementioned data and analyzing market information to present appropriate trading conditions, A system that includes this.

2. The system according to claim 1, further comprising means for confirming and deciding on the presented transaction conditions on the user's operating terminal.

3. The system according to claim 1, further comprising means for selecting and proposing the most suitable data generator in order to build cooperative relationships with commercial organizations.

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