System

Abstract

A system is provided.SOLUTION: A system, comprising: means for uploading generated content onto the Internet; means for running artificial intelligence to extract features of the generated content; means for receiving buyer need information; means for running artificial intelligence to match the generated content with buyers based on the need information; means for making payments in virtual currency; and means for compensating sellers according to the number of matches.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In conventional digital content trading systems, sellers had to go through complicated procedures such as providing detailed descriptions and setting prices in order to sell their products, which placed a heavy burden on them. It was also difficult for buyers to find the product that best suited their needs from the vast number of options available, making it difficult to conduct efficient transactions. Furthermore, differences in currency often became a barrier in international transactions, making smooth transactions difficult. [Means for solving the problem]

[0005] This invention solves the above-mentioned problems by providing a system including means for uploading generated content to the Internet, means for executing artificial intelligence to extract features of the generated content, means for receiving buyer needs information, means for executing artificial intelligence to match the generated content with buyers based on the needs information, means for making payments in virtual currency, and means for paying rewards to sellers according to the number of matches. This allows sellers to easily provide content, makes it easy for buyers to find products that best suit their needs, and further facilitates international transactions.

[0006] "Generated content" refers to information or data in digital form created by generative artificial intelligence or other means.

[0007] The term "Internet" refers to a global network in which multiple computer networks are interconnected and used for data communication.

[0008] "Means of uploading" refers to the technology or process used to transmit data or information from a local environment over a network to a remote server for storage.

[0009] "Artificial intelligence for feature extraction" refers to machine learning models and algorithms used to identify and classify useful features and metadata in digital content.

[0010] "Buyer" means any person or entity seeking to purchase goods or services on the Platform.

[0011] "Needs information" refers to information that describes or enters the requirements and wishes of a purchaser regarding the products or services they want.

[0012] "Artificial intelligence for matching" refers to machine learning models and algorithms that optimally match buyer needs information with seller-generated content.

[0013] "Virtual currency" refers to digital currency that is generated based on cryptographic technology, does not have the status of legal tender, and is traded electronically.

[0014] "Payment instrument" means the mechanism by which funds are electronically transferred between a buyer and a seller to pay for a transaction.

[0015] "Remuneration payment instrument" refers to a mechanism for electronically transferring remuneration based on a contract for specific results or services provided. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11]FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] The present invention relates to a system for efficiently trading generated content over the Internet, and provides a means for smoothly trading digital content between sellers and buyers.

[0038] System Configuration

[0039] The system of this invention mainly consists of a server, a seller's terminal, and a buyer's terminal. The server is a central control device that communicates with and processes multiple terminals via the Internet. The terminals are devices through which users input or output data via an interface.

[0040] Seller-initiated content uploads

[0041] Device: The seller uses their device to access the platform interface. They select the "New Listing" button and fill out the form to upload their digital content (e.g., image files, 3D models, software).

[0042] Terminal: When the seller selects a file and clicks the upload button, the file and the entered information are sent to the server.

[0043] Server: The server receives this data and stores it in storage. A generative AI module is then invoked to extract features from the uploaded file and tag it appropriately.

[0044] Server: The extracted feature information and tags are stored in a database for later use in searching and matching.

[0045] Inputting buyer needs and matching

[0046] Device: Buyers access the platform using their own device and enter their requirements and needs for the desired product in the search bar, for example, "I want digital art of fantasy landscapes."

[0047] Terminal: When the buyer clicks the search button, their needs information is sent to the server.

[0048] Server: The server passes the received needs information to the generation AI module, which performs optimal matching. The generation AI module compares the needs information with the listing information in the database and lists the best-matching listing data.

[0049] Server: The matching results are sent to the buyer's device and displayed on the buyer's screen.

[0050] Checkout and payment

[0051] Terminal: The buyer selects the desired product from the displayed matching results and clicks the "Purchase" button, which will display the payment page.

[0052] Terminal: The buyer enters their cryptocurrency wallet information on the payment page and clicks the "Pay" button.

[0053] Server: The server receives the payment information and passes it to the payment module, which debits the specified cryptocurrency from the buyer's wallet and completes the transaction.

[0054] Payment module: verifies the success of the transaction and sends the result back to the server.

[0055] Payment of rewards to sellers

[0056] Server: Based on the information on successful transactions, the server calculates the seller's reward. The reward is determined based on the number of matches and the transaction amount.

[0057] Payment module: Pays the calculated reward to the seller's wallet in virtual currency.

[0058] Server: Updates the seller's dashboard with transaction history and reward information, and notifies the seller that the reward has been paid.

[0059] Specific examples

[0060] For example, Seller A uploads digital art of a "fantasy landscape," and the generative AI module extracts and tags features such as "fantasy" and "landscape." If Buyer B inputs, "I want digital art of a fantasy landscape," the generative AI module recommends Seller A's digital art as the most suitable product and displays it on Buyer B's screen. When Buyer B selects the product and pays with virtual currency, Seller A receives a reward.

[0061] The processing flow will be explained below.

[0062] Electronic data upload by seller

[0063] Step 1:

[0064] Sellers log in to the platform using their own devices, enter their login information and click the "Login" button.

[0065] Step 2:

[0066] The seller clicks the "New Listing" button on their My Page, which displays the upload form.

[0067] Step 3:

[0068] Sellers enter the category and product description on the form and upload electronic data files by dragging and dropping or selecting them from the file selection dialog.

[0069] Step 4:

[0070] When the seller clicks the "Upload" button, the entered information and file are sent to the server.

[0071] Step 5:

[0072] The server stores the received information and files in storage, then invokes the generative AI module to extract and tag the file features.

[0073] Step 6:

[0074] The server stores the characteristic information and tags in a database and registers them as listing information.

[0075] Inputting buyer needs and matching

[0076] Step 1:

[0077] Buyers access the platform using their own devices, go to the search page and enter their needs and desired products in the search bar.

[0078] Step 2:

[0079] When the purchaser clicks the "Search" button, the needs information is sent to the server.

[0080] Step 3:

[0081] The server passes the received needs information to the generation AI module, which searches the database for optimal listing information based on the needs information.

[0082] Step 4:

[0083] The generation AI module returns the matching results to the server, which then sends the matching results to the buyer's terminal and displays them.

[0084] Checkout and payment

[0085] Step 1:

[0086] The buyer selects the desired product from the displayed matching results and clicks the "Purchase" button.

[0087] Step 2:

[0088] The server receives the purchaser's selection and sends data to display the checkout page.

[0089] Step 3:

[0090] The buyer enters their cryptocurrency wallet information on the payment page and clicks the "Pay" button.

[0091] Step 4:

[0092] The server receives the payment information and forwards it to the payment module, which debits the specified cryptocurrency from the buyer's wallet to complete the transaction.

[0093] Step 5:

[0094] The payment module verifies the success of the transaction and sends the result back to the server, which notifies the buyer that the purchase has been completed.

[0095] Payment of rewards to sellers

[0096] Step 1:

[0097] The server calculates the seller's reward based on the information of successful transactions. The reward is determined according to the number of successful matches and the transaction amount.

[0098] Step 2:

[0099] The settlement module pays the calculated reward in virtual currency to the seller's wallet.

[0100] Step 3:

[0101] The server updates the transaction history and reward information on the seller's dashboard and notifies the seller that the reward payment has been completed.

[0102] Example 1

[0103] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0104] Conventional digital content trading systems struggled to efficiently handle the entire process of uploading content, extracting its features, matching it with buyer needs, settlement, and paying commissions to sellers. Furthermore, they lacked the ability to accurately interpret buyer needs and recommend appropriate products. Furthermore, there was no guarantee that payments in virtual currency or subsequent commission payments to sellers would be carried out smoothly. This hindered the smooth flow of transactions, preventing satisfaction for both sellers and buyers.

[0105] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0106] In this invention, the server includes means for uploading the generated content to the Internet, means for executing artificial intelligence to extract features of the generated content, means for receiving needs information of buyers, means for executing artificial intelligence to match the generated content with buyers based on the needs information, means for making payments in virtual currency, means for paying a reward to the seller according to the number of matches, means for extracting and tagging features of the generated content, and means for presenting optimal matching results based on the buyer's needs. This enables transactions between sellers and buyers to be carried out efficiently and smoothly, thereby improving the satisfaction of both parties and the success rate of transactions.

[0107] "Generated Content" means media in digital form that is created by Users and uploaded to the Platform.

[0108] "Means for uploading onto the Internet" refers to the software and hardware mechanisms for transmitting the generated content from the user's terminal to a server and publishing it on the Internet.

[0109] "Artificial intelligence for feature extraction" refers to algorithms and technologies that automatically identify the characteristics and attributes of uploaded content and obtain relevant information.

[0110] "Needs information" is information that indicates the conditions and requests that a purchaser has for a particular digital content.

[0111] "Artificial intelligence for matching" refers to algorithms and technologies that compare buyer needs information with generated content to find the best match.

[0112] A "virtual currency payment instrument" is a software and hardware mechanism that allows a transaction to be paid for and a purchase to be completed using virtual currency.

[0113] "Payment mechanism" means the software and hardware mechanism for paying a commission to a seller after a transaction is completed.

[0114] "Tagging" is the process of adding keywords or labels to content based on its characteristics to facilitate searching and categorization.

[0115] "Means for presenting optimal matching results based on needs" refers to the algorithms and technologies for searching for optimal content based on the needs information entered by the purchaser and presenting the results to the purchaser.

[0116] The present invention is a system for efficiently trading generated digital content, which is composed of a server, a seller's terminal, and a buyer's terminal. The server is a central device that communicates with multiple terminals via the Internet and controls the overall process. The terminals are devices through which users input or output data via an interface.

[0117] Seller-initiated content uploads

[0118] 1. Device: The seller accesses the platform interface using their device. The seller selects the "New Listing" button and fills in the required information in the form to upload digital content (e.g., image files, 3D models, software).

[0119] Example: Seller A logs into the platform from his / her computer and uploads a digital artwork of a "fantastic landscape."

[0120] Example prompt: Press the "New Listing" button and enter content information.

[0121] 2. Terminal: When the seller selects a file and clicks the upload button, the file and the entered information are sent to the server.

[0122] Content feature extraction and tagging

[0123] 3. Server: The server receives the files and meta information sent by the seller and stores them in a temporary storage area.

[0124] 4. Server: The server calls the generative AI module to analyze the uploaded content file. The generative AI module uses image processing algorithms to extract features such as color, shape, and theme, and then tag them appropriately.

[0125] Specific operation: The generation AI module generates tags such as "fantastic" and "landscape."

[0126] Example prompt: Extract file characteristics and generate appropriate tags.

[0127] 4. Server: Stores the extracted feature information and tags in a database so that they can be used for searching and matching.

[0128] Inputting buyer needs and matching

[0129] 1. Device: Buyers access the platform using their own device and enter their desired product requirements and needs in the search bar.

[0130] Example: Buyer B types into his computer, "I want digital art of a fantasy landscape."

[0131] Example prompt: Enter your needs in the product search bar.

[0132] 2. Terminal: When the buyer clicks the search button, their needs information is sent to the server.

[0133] 3. Server: The server passes the received needs information to the generation AI module, which performs optimal matching processing. The generation AI module compares the needs information with the listing information in the database and lists the most suitable listing data.

[0134] 4. Server: The matching results are sent to the buyer's device and displayed on the buyer's screen.

[0135] Example: The server recommends seller A's "fantastic landscape painting" to buyer B's needs.

[0136] Example prompt: List the products that best meet your needs.

[0137] Checkout and payment

[0138] 1. Terminal: The buyer selects the desired product from the displayed matching results and clicks the "Purchase" button, which displays the payment page.

[0139] Example: Buyer B selects a "fantastic landscape painting" and completes the payment procedure using virtual currency.

[0140] Example prompt: Please select a product and proceed with your purchase.

[0141] 2. Terminal: The buyer enters their cryptocurrency wallet information on the payment page and clicks the "Pay" button.

[0142] 3. Server: The server receives the payment information and passes it to the payment module, which debits the cryptocurrency from the buyer's wallet and completes the transaction.

[0143] 4. Payment module: Checks the success of the transaction and sends the result back to the server.

[0144] 5. Server: The server notifies the buyer's terminal that the transaction is complete.

[0145] Payment of rewards to sellers

[0146] 1. Server: Based on the successful transaction information, the server calculates the reward for the seller. The reward is determined based on the number of matches and the transaction amount.

[0147] 2. Payment module: Pays the calculated reward to the seller's wallet in cryptocurrency.

[0148] 3. Server: Updates the seller's dashboard with transaction history and reward information, and notifies the seller that the reward has been paid.

[0149] The above process flow ensures that digital content uploaded by sellers is delivered to buyers efficiently, ensuring smooth transactions. Furthermore, the generative AI module extracts features and tags them to ensure proper matching.

[0150] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0151] Step 1:

[0152] Seller Login

[0153] Input: The username and password entered on the seller's device.

[0154] How it works: The server validates the login information through the authentication module, searching the user database to see if a matching username and password combination exists.

[0155] Output: If authentication is successful, the seller will be shown the dashboard screen. If authentication is unsuccessful, a login error message will be displayed.

[0156] Step 2:

[0157] Uploading content

[0158] Input: Digital content (image files, 3D models, software) and meta information (title, description, price, etc.) uploaded from the seller's device.

[0159] How it works: The server receives the uploaded file and meta information and stores it in a temporary storage area.

[0160] Output: Success message and URL to save the file temporarily on the server.

[0161] Step 3:

[0162] Feature Extraction and Tagging

[0163] Input: Uploaded digital content files and their meta information.

[0164] How it works: The server calls the generative AI module to analyze the file, extracting features such as color, shape, and theme, and automatically generating appropriate tags.

[0165] Output: Feature information and generated tags. For example, tags such as "fantastic" and "landscape."

[0166] Step 4:

[0167] Database storage

[0168] Input: Feature information and tags.

[0169] How it works: The server stores the generated features and tags in a database, making them available for later searching and matching.

[0170] Output: Data stored in a database.

[0171] Step 5:

[0172] Buyer Login

[0173] Input: The username and password entered on the buyer's device.

[0174] How it works: The server validates the login information through the authentication module, searching the user database to see if a matching username and password combination exists.

[0175] Output: If authentication is successful, the buyer will be redirected to the dashboard screen. If authentication is unsuccessful, a login error message will be displayed.

[0176] Step 6:

[0177] Needs input

[0178] Input: The requirements and needs of the desired product entered by the buyer on their device. For example, "I want digital art of a fantasy landscape."

[0179] Behavior: The server temporarily stores the received needs information and prepares it for the next matching process.

[0180] Output: Temporarily saved needs information.

[0181] Step 7:

[0182] Matching process

[0183] Input: Temporarily saved needs information and listing information in the database.

[0184] How it works: The server calls the generation AI module, compares the needs information with the listing data in the database, and makes the best match to list the listing data that best suits the buyer.

[0185] Output: Listed listing data as a result of matching.

[0186] Step 8:

[0187] Matching results displayed

[0188] Input: The result of the match.

[0189] Operation: The server sends the matching results to the buyer's device and displays them on the buyer's screen.

[0190] Output: Matching results displayed on the buyer's device.

[0191] Step 9:

[0192] Product selection and purchase

[0193] Input: Product data and payment information (cryptocurrency wallet information) selected from the buyer's device.

[0194] How it works: After the buyer clicks the "Purchase" button, the server displays the payment page and receives payment information.

[0195] Output: Transaction data and payment information.

[0196] Step 10:

[0197] Payment Processing

[0198] Input: Cryptocurrency wallet information and transaction data provided by the buyer.

[0199] Action: The server uses the payment module to perform a virtual currency debit. If successful, the transaction is completed.

[0200] Output: Confirmation of payment completion and notification of transaction completion.

[0201] Step 11:

[0202] Remuneration calculation

[0203] Input: Successful transaction data.

[0204] How it works: The server calculates the seller's reward based on the transaction data. The reward is determined based on the number of matches and the transaction amount.

[0205] Output: The calculated reward amount.

[0206] Step 12:

[0207] Reward payment

[0208] Input: Calculated reward amount and seller wallet information.

[0209] How it works: The server uses the payment module to pay the reward in cryptocurrency to the seller's wallet. It then verifies that the payment was successful.

[0210] Output: Confirmation of payment completion.

[0211] Step 13:

[0212] Remuneration notification

[0213] Input: Completion information for reward payment.

[0214] What it does: The server updates the seller's dashboard with transaction history and reward information, and notifies them that the reward has been paid.

[0215] Output: Compensation information and transaction history displayed on the seller's dashboard.

[0216] (Application example 1)

[0217] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0218] In digital content trading, there is a demand for technology that allows for efficient and smooth transactions between sellers and buyers. In particular, there are challenges in quickly and accurately providing buyers with content that meets their needs from a vast amount of digital content, and in smoothly paying sellers. There is also a need for a method that allows for easy uploading via smartphone and automatic tag generation.

[0219] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0220] In this invention, the server includes means for uploading generated content to the Internet, means for executing artificial intelligence to extract features of the generated content, means for receiving needs information of buyers, means for executing artificial intelligence to match the generated content with buyers based on the needs information, means for making payments in virtual currency, means for paying a reward to the seller according to the number of matches, means for uploading digital content using a smartphone app, means for executing artificial intelligence to extract features from the uploaded digital content and automatically generate tags, and means for storing the generated tags and feature information in a database. This enables efficient transactions of digital content and improves usability for sellers and buyers.

[0221] "Generated content" is information or data created in digital form.

[0222] The "Internet" is a global communications medium for sending and receiving information over networks.

[0223] "Artificial intelligence for feature extraction" refers to techniques for identifying relevant characteristics from digital content and analyzing that information.

[0224] "Purchaser" means an individual or entity seeking to purchase digital content.

[0225] "Needs Information" refers to the requirements and conditions regarding the specific digital content that a purchaser desires.

[0226] "Artificial intelligence for matching" is a technology that optimally matches buyer needs information with the digital content being offered.

[0227] "Virtual currency" is a currency that is traded in digital form and is used as a means of payment online.

[0228] "Remuneration" refers to the consideration or profit that a seller receives from a transaction.

[0229] A "smartphone app" is a software program that runs on a smartphone.

[0230] A "tag" is a keyword or label added to digital content to make it easier to identify it.

[0231] A "database" is a system for efficiently storing, managing, and making searchable information.

[0232] This invention relates to a system for efficiently trading generated content over the Internet. Specifically, it is a platform where sellers upload digital content using a smartphone app, the features of that content are extracted and tagged using artificial intelligence (generative AI model), and buyers can search for and purchase content based on their needs.

[0233] System configuration and operation overview:

[0234] The system mainly consists of the following components:

[0235] 1. Server: A central device that stores data, processes data, performs artificial intelligence, and handles cryptocurrency payments.

[0236] 2. Seller's device (smartphone): Upload digital content.

[0237] 3. Buyer's device (smartphone, PC, etc.): Enter your needs information and search for and purchase content.

[0238] Seller Content Upload Instructions:

[0239] 1. Seller's device: Sellers use the smartphone app interface to upload digital content (e.g., image files, 3D models, music). To upload, they use the "New Listing" button and enter the required information.

[0240] 2. Server: Receives uploaded files and input information, stores them in storage, and then runs a generative AI model to extract features from the generated content.

[0241] 3. Server: Analyzes the content features using a generative AI model and adds appropriate tags. These features and tags are stored in a database.

[0242] Buyer needs input and matching procedure:

[0243] 1. Buyer's device: Buyers access the platform through a smartphone app or web interface and enter their desired content needs, such as a specific request for "digital art of fantasy landscapes."

[0244] 2. Server: Receives needs information and uses the generative AI model to match it with content in the database.

[0245] 3. Server: The optimal matching results are sent to the buyer's device, and the buyer can select the desired content from the displayed list.

[0246] Checkout and payment:

[0247] 1. Buyer's device: The buyer selects the content they want and clicks the "Purchase" button, which displays the payment page.

[0248] 2. Server: Receives information when a buyer makes a payment using a cryptocurrency wallet, completes the transaction using the payment module, verifies the success of the transaction, and notifies the buyer and seller of the result.

[0249] Seller Payment:

[0250] 1. Server: If the transaction is successful, calculate the seller's reward and pay it in virtual currency using the payment module.

[0251] 2. Server: Updates the transaction history and reward information on the seller's dashboard and notifies the seller that the reward has been paid.

[0252] Hardware and software used:

[0253] Hardware: Servers (e.g., AWS EC2), smartphones (iOS / Android)

[0254] Software: Python and Flask (web framework), TensorFlow / Keras (generative AI model) on the server side, Swift (iOS) or Java / Kotlin (Android) on the smartphone app side

[0255] Examples:

[0256] Seller A uploads a digital piece of art of a "fantastic landscape" using a smartphone app, and the generative AI model automatically generates tags such as "fantastic" and "landscape."

[0257] When Buyer B enters "I want digital art of fantasy landscapes," the AI ​​model recommends content from Seller A and displays it on Buyer B's screen.

[0258] When Buyer B selects a product and pays with virtual currency, Seller A is paid a reward in virtual currency.

[0259] Example prompt sentence:

[0260] "Analyze the visual features of an input digital image and generate appropriate tags based on those features."

[0261] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0262] Step 1:

[0263] Seller's device:

[0264] Sellers select the "New Listing" button on the smartphone app and upload digital content (e.g., image files, 3D models, music), while also entering the required information (title, description, price, etc.).

[0265] Step 2:

[0266] Seller's device:

[0267] When the seller clicks the upload button, the selected file and the entered information are sent to the server. The file information and metadata are packaged and sent as an HTTP request.

[0268] Step 3:

[0269] server:

[0270] The server receives the uploaded file and metadata and stores them in the specified storage. Once the storage is complete, it calls the generative AI model to extract the features of the uploaded file. Specifically, the saved file path is passed as input to the generative AI model, and the resulting feature data is output.

[0271] Step 4:

[0272] server:

[0273] The generative AI model analyzes the visual characteristics of the input file and generates appropriate tags. Specifically, it uses an image processing algorithm to extract features and then generates tags based on those features. In this process, the file path is given as input data and a tag list is obtained as output data.

[0274] Step 5:

[0275] server:

[0276] The extracted feature data and generated tags are stored in a database, which stores file paths, generated tags, file metadata, etc. The stored data is used for later searches and matching.

[0277] Step 6:

[0278] Buyer's device:

[0279] Buyers access the platform through a smartphone app or web interface and enter their desired digital content needs information. The needs information is entered in text format, and when the buyer clicks the search button, the information is sent to the server.

[0280] Step 7:

[0281] server:

[0282] The server receives the buyer's needs information and uses a generative AI model to match it with content in the database. The needs information is passed as input data to the generative AI model, and the optimal matching result is obtained as output data. Specifically, the needs information is analyzed using natural language processing technology and related content in the database is searched for.

[0283] Step 8:

[0284] server:

[0285] The matching results obtained from the generative AI model are sent to the buyer's device and displayed to the buyer. A list of matching results is generated as output data and displayed on the buyer's screen.

[0286] Step 9:

[0287] Buyer's device:

[0288] The buyer selects the desired content from the matching results and clicks the "Purchase" button. This action displays the payment page. The buyer enters their cryptocurrency wallet information and clicks the "Pay" button.

[0289] Step 10:

[0290] server:

[0291] The server receives the buyer's payment information and completes the transaction using the payment module. Specifically, it withdraws the specified cryptocurrency from the buyer's wallet, checks whether the transaction is successful, and then notifies the buyer and seller of the transaction result.

[0292] Step 11:

[0293] server:

[0294] If the transaction is successful, the seller's reward is calculated and paid in virtual currency using the payment module, which is then transferred to the seller's wallet.

[0295] Step 12:

[0296] server:

[0297] The transaction history and reward information will be updated on the seller's dashboard, and a notification will be sent to notify the seller that the reward payment has been completed. Sellers can check their transaction history and reward details by checking their dashboard.

[0298] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0299] The present invention relates to a system for efficiently trading generated content over the Internet, and realizes optimal recommendations through emotion recognition by combining an emotion engine to facilitate smooth trading of digital content between sellers and buyers.

[0300] System Configuration

[0301] The system of the present invention is composed of a server, a seller's terminal, a buyer's terminal, and an emotion engine. The server is a central control device that communicates with multiple terminals via the Internet and performs various processes. The terminals are devices through which users input and output data, and the emotion engine is a system for recognizing and analyzing user emotions in real time.

[0302] Seller-initiated content uploads

[0303] Device: Sellers log in to the platform using their own devices. Enter the required information in the login form and click the "Login" button.

[0304] Device: Sellers click the "New Listing" button on their My Page to go to the screen where they can upload their digital content. Here, they can enter the category and product description and select the digital data file.

[0305] Terminal: When the seller clicks the "Upload" button, the entered information and electronic data file are sent to the server.

[0306] Server: The server stores the received information and electronic data files in storage, then invokes the generative AI module to extract and tag the file features.

[0307] Server: The extracted feature information and tags are saved in a database and registered as listing information.

[0308] Inputting buyer needs and matching

[0309] Device: The buyer visits the platform's search page and enters their needs and desired digital content into the search bar.

[0310] Terminal: When the buyer clicks the "Search" button, the needs information is sent to the server.

[0311] Server: The server passes the received needs information to the generation AI module to search for the best listing information. The generation AI module compares this needs information with the listing information in the database and lists the best-matching listing data.

[0312] Server: The matching results are sent to the buyer's device and displayed on the buyer's screen.

[0313] Checkout and payment

[0314] Terminal: The buyer selects the desired product from the displayed matching results and clicks the "Purchase" button.

[0315] Server: The server receives the buyer's selection and sends the data to display the checkout page.

[0316] Terminal: The buyer enters their cryptocurrency wallet information on the payment page and clicks the "Pay" button.

[0317] Server: The server receives the payment information and passes it to the payment module, which debits the cryptocurrency from the buyer's wallet and completes the transaction.

[0318] Payment module: verifies the success of the transaction and sends the result back to the server, which then notifies the buyer that the purchase is complete.

[0319] Payment of rewards to sellers

[0320] Server: Based on the information of successful transactions, calculates the reward for the seller and determines the reward according to the number of successful matches and the transaction amount.

[0321] Payment module: Pays the calculated reward to the seller's wallet in virtual currency.

[0322] Server: Updates the seller's dashboard with transaction history and reward information, and notifies the seller that the reward has been paid.

[0323] Emotion engine integration

[0324] Emotion engine: Analyzes camera footage and audio data acquired from the user's device in real time to recognize the user's emotional state, such as happiness, sadness, surprise, etc.

[0325] Server: Based on the emotion data received from the emotion engine, the server adjusts the matching algorithm of the generative AI module to make recommendations that are optimal for the user's emotional state.

[0326] On your device: Shows matching listings based on your sentiment.

[0327] Specific examples

[0328] For example, if seller A uploads a digital art piece of "fantastic landscape painting," the generative AI module extracts and tags features such as "fantastic" and "landscape." If buyer B searches for "I want digital art of fantasy landscapes," the generative AI module will recommend seller A's digital art piece as the most suitable product, and if the emotion engine detects buyer B's happy emotions, it will prioritize products that are likely to further increase engagement based on those emotions. When buyer B selects a product and pays with virtual currency, seller A will receive a reward. During this process, seller A's reward may increase as the emotion engine improves the recommendation accuracy.

[0329] The processing flow will be explained below.

[0330] Electronic data upload by seller

[0331] Step 1:

[0332] Sellers log in to the platform using their own devices, enter their login information and click the "Login" button.

[0333] Step 2:

[0334] The seller clicks the "New Listing" button on their My Page, which displays the upload form.

[0335] Step 3:

[0336] Sellers enter the category and product description on the form and upload electronic data files by dragging and dropping or selecting them from the file selection dialog.

[0337] Step 4:

[0338] When the seller clicks the "Upload" button, the entered information and file are sent to the server.

[0339] Step 5:

[0340] The server stores the received information and files in storage, then invokes the generative AI module to extract and tag the file features.

[0341] Step 6:

[0342] The server stores the characteristic information and tags in a database and registers them as listing information.

[0343] Inputting buyer needs and matching

[0344] Step 1:

[0345] Buyers access the platform using their own devices, go to the search page and enter their needs and desired products in the search bar.

[0346] Step 2:

[0347] When the purchaser clicks the "Search" button, the needs information is sent to the server.

[0348] Step 3:

[0349] The server passes the received needs information to the generation AI module, which searches the database for optimal listing information based on the needs information.

[0350] Step 4:

[0351] The generation AI module returns the matching results to the server, which then sends the matching results to the buyer's terminal and displays them.

[0352] Checkout and payment

[0353] Step 1:

[0354] The buyer selects the desired product from the displayed matching results and clicks the "Purchase" button.

[0355] Step 2:

[0356] The server receives the purchaser's selection and sends data to display the checkout page.

[0357] Step 3:

[0358] The buyer enters their cryptocurrency wallet information on the payment page and clicks the "Pay" button.

[0359] Step 4:

[0360] The server receives the payment information and forwards it to the payment module, which debits the specified cryptocurrency from the buyer's wallet to complete the transaction.

[0361] Step 5:

[0362] The payment module verifies the success of the transaction and sends the result back to the server, which notifies the buyer that the purchase has been completed.

[0363] Payment of rewards to sellers

[0364] Step 1:

[0365] The server calculates the seller's reward based on the information of successful transactions. The reward is determined according to the number of successful matches and the transaction amount.

[0366] Step 2:

[0367] The settlement module pays the calculated reward in virtual currency to the seller's wallet.

[0368] Step 3:

[0369] The server updates the transaction history and reward information on the seller's dashboard and notifies the seller that the reward payment has been completed.

[0370] Emotion engine integration

[0371] Step 1:

[0372] The emotion engine analyzes camera footage and audio data acquired from the user's device in real time to recognize the user's emotional state.

[0373] Step 2:

[0374] The emotion engine transmits the recognized emotion data to the server.

[0375] Step 3:

[0376] The server adjusts the matching algorithm of the generation AI module based on the emotional data and makes recommendations that are optimal for the user's emotional state.

[0377] Step 4:

[0378] The server transmits the recommendation results based on the emotional state to the user's terminal and displays them.

[0379] Specific examples

[0380] Step 1:

[0381] Seller A uploads a digital piece of art of a "fantastic landscape painting," and the generative AI module extracts and tags features such as "fantastic" and "landscape."

[0382] Step 2:

[0383] When Buyer B searches for "I want digital art of fantasy landscapes," the generative AI module recommends Seller A's digital art as the most suitable product.

[0384] Step 3:

[0385] The emotion engine detects Buyer B's happy emotions and prioritizes displaying products that are likely to increase engagement based on those emotions.

[0386] Step 4:

[0387] When Buyer B selects a product and pays with virtual currency, Seller A receives a reward.

[0388] Step 5:

[0389] The server utilizes data from the emotion engine to learn and improve the accuracy of the recommendation algorithm.

[0390] Example 2

[0391] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0392] Current digital content trading systems face challenges such as low matching accuracy between sellers and buyers and a lack of personalized user experience. Furthermore, payment methods are limited, making smooth payments using virtual currencies difficult. Therefore, there is a demand for improved matching accuracy that takes user emotions into account, as well as dynamic payment functions using virtual currencies.

[0393] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0394] In this invention, the server includes a means for uploading the generated content to the Internet, a means for executing artificial intelligence to extract features of the generated content, and a means for receiving buyer needs information. This allows the server to recognize the user's emotional state in real time and adjust the matching algorithm, a means for making payments in virtual currency, and a means for paying rewards to sellers according to the number of matches. This improves the accuracy of matching, facilitates transactions between sellers and buyers, and enables smooth payments using virtual currency.

[0395] "Generated content" refers to data or works in digital form that are created using artificial intelligence or other digital technologies.

[0396] "Artificial intelligence" refers to technology that enables computer systems to imitate human intelligence, process and analyze data, and achieve more advanced decision-making and automation through self-learning.

[0397] "Purchaser needs information" refers to information that a user inputs explicitly or implicitly regarding the conditions and requirements for the product or service that the user desires.

[0398] An "emotion engine" refers to algorithms and technologies that recognize and analyze a user's emotional state in real time and adjust the system's behavior based on the results.

[0399] "Virtual currency" refers to a currency that uses cryptography to ensure the security of transactions and allows value to be exchanged digitally without the involvement of a central authority.

[0400] "Matching algorithm" refers to the calculation procedures and logic used to compare the buyer's needs information with the characteristics of the content generated by the seller and find the optimal combination.

[0401] "Reward" refers to the consideration or profit that an exhibitor receives when the content provided by the exhibitor is purchased.

[0402] "Receiving needs information" refers to the system taking in and processing information about the buyer's wishes and requirements.

[0403] The present invention relates to a system for efficiently trading generated content over the Internet. The system of the present invention comprises a server, a seller's terminal, a buyer's terminal, and an emotion engine. The server is a central control device that communicates with multiple terminals via the Internet and performs various processes. The terminals are devices through which users input and output, and the emotion engine is a system for recognizing and analyzing user emotions in real time.

[0404] First, the seller accesses the platform using their own device, enters the required information in the login form, and clicks the "Login" button. The server receives this login information, verifies the user information using the authentication module, and if authentication is successful, the seller is redirected to their personal page.

[0405] Next, when the seller clicks the "New Listing" button on their My Page, they are taken to the listing screen. Here, they enter the category and product description and select the electronic data file to be listed. When the seller clicks the "Upload" button, the entered information and the selected electronic data file are sent to the server. The server saves the received information and electronic data file in storage.

[0406] The server passes the saved electronic data file to a generation AI module, which extracts the file's characteristics. For example, a specific painting's data may be tagged with "fantastic" or "landscape." The extracted characteristic information and tags are stored in a database and registered as listing information. Once registration is complete, a notification of upload completion is displayed on the seller's device.

[0407] Meanwhile, buyers access the platform using their devices and enter keywords for the digital content they desire in the search bar. When the buyer clicks the "Search" button, the entered needs information is sent to the server. The server passes the received needs information to the generation AI module, which searches for the most suitable listing information. The generation AI module compares this information with the listing information in the database and lists the most suitable listing data. The matching results are sent to the buyer's device and displayed on the screen.

[0408] When a buyer selects the desired product and clicks the "Purchase" button, the selection information is sent to the server. The server receives the selected product information and sends data to display the payment page to the buyer. The buyer enters their virtual currency wallet information on the payment page and clicks the "Pay" button. The server receives the payment information and passes it to the payment module. The payment module deducts the virtual currency from the buyer's wallet and completes the transaction. Once the success of the transaction is confirmed, the result is sent back to the server, and the buyer is notified that the purchase procedure has been completed.

[0409] Based on the successful transaction information, the server calculates the reward for the seller and pays the reward in virtual currency to the seller's wallet through the payment module. The server then updates the transaction history and reward information on the seller's dashboard and notifies the seller that the reward payment has been completed.

[0410] The emotion engine analyzes camera footage and audio data acquired from the user's device in real time to recognize the user's emotional state. For example, it identifies the user's emotions such as joy, sadness, and surprise. The server adjusts the matching algorithm of the generation AI module based on the emotion data received from the emotion engine, and makes recommendations that are optimal for the user's emotional state. The adjusted matching results are displayed on the device, allowing the user to receive appropriate recommendations based on their emotions.

[0411] Specific examples

[0412] For example, if seller A uploads a digital art piece of "fantastic landscape painting," the generative AI module extracts and tags features such as "fantastic" and "landscape." If buyer B searches for "I want digital art of fantasy landscapes," the generative AI module will recommend seller A's digital art piece as the most suitable product. If the emotion engine detects buyer B's happy emotions, it will prioritize products that are likely to further increase engagement based on those emotions. When buyer B selects a product and pays with virtual currency, seller A will receive a reward. During this process, seller A's reward may increase as the emotion engine improves the recommendation accuracy.

[0413] Prompt Sentence Examples

[0414] Please explain, step by step, how the digital content of the fantastical landscape painting uploaded by Seller A matches the needs of Buyer B, and how the emotion engine uses Buyer B's emotions to make the optimal recommendation.

[0415] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0416] Step 1: Seller Login

[0417] Input: Username and password provided by the seller's device.

[0418] Server: Receives the submitted login information and passes it to the authentication module to verify the user information.

[0419] Output: If authentication is successful, the seller is redirected to their My Page and the display data of their My Page is sent to the terminal.

[0420] Specific operation: The seller enters the required information into the login form and clicks the "Login" button. The server receives this and verifies it with the user information in the database. Once verification is complete, the seller's personal page is generated and the data is sent to the terminal.

[0421] Step 2: New listing

[0422] Input: Category, product description, and electronic data file provided by the seller's terminal.

[0423] Terminal: When the seller clicks the "New Listing" button, the new listing screen will be displayed.

[0424] Specific operation: The seller enters the category and product description on the new listing screen and selects the electronic data file. When the seller clicks the "Upload" button, this information is sent to the server.

[0425] Step 3: Upload content

[0426] Input: Category, product description, and electronic data file sent from the seller's terminal.

[0427] Server: Stores received information and electronic data files in storage.

[0428] Output: The listing information is saved to storage.

[0429] Specific operation: The server writes and saves the received information and data file in the database storage. Once the saving is complete, it sends a notification to the seller that the upload is complete.

[0430] Step 4: Feature extraction and tagging

[0431] Input: Electronic data files stored in storage.

[0432] Server: Passes stored electronic data files to the generation AI module, which extracts file features.

[0433] Output: The extracted features and tags are stored in a database.

[0434] How it works: The generative AI module analyzes the data file and, for example, if it is a landscape painting, assigns tags such as "fantastic" or "landscape." These feature information and tags are then registered in a database.

[0435] Step 5: Enter your buyer's needs

[0436] Input: Search keywords provided by the buyer's device.

[0437] User (Buyer): The buyer enters the keywords for the desired content in the search bar and clicks the "Search" button.

[0438] Output: The input needs information is sent to the server.

[0439] Specific operation: The purchaser's device sends the entered keywords to the server, which prepares to pass them to the generation AI module.

[0440] Step 6: Submit your needs information

[0441] Input: The search term entered by the buyer.

[0442] Server: Passes the received needs information to the generation AI module.

[0443] Output: Matches that are compared with listings in the database.

[0444] Specific operation: The server provides the buyer's needs information to the generation AI module, which compares it with the listing information in the database and lists the most matching listing data.

[0445] Step 7: Viewing the matching results

[0446] Input: Matching results output from the generative AI module.

[0447] Server: Sends the matching results to the buyer's device.

[0448] Output: Matching results displayed on the buyer's device.

[0449] Specific operation: The buyer's device displays the matching results received from the server, and the buyer can review the results and select the desired product.

[0450] Step 8: Product Selection

[0451] Input: Information about the product selected by the buyer.

[0452] User (Buyer): The buyer selects the product they want and clicks the "Purchase" button.

[0453] Output: Product selection information is sent to the server.

[0454] Specific operation: The purchaser's device sends information about the selected product to the server.

[0455] Step 9: Enter your payment information

[0456] Input: Payment page data provided by the server, cryptocurrency wallet information entered by the buyer.

[0457] Server: Receives the selected product information and sends the payment page data to the buyer.

[0458] Output: The payment page is displayed on the buyer's device.

[0459] Specific operation: The payment page is displayed on the buyer's device, and the buyer enters their wallet information and clicks the "Pay" button, which is then sent to the server.

[0460] Step 10: Payment Processing

[0461] Input: Buyer's payment information.

[0462] Server: Receives payment information and passes it to the payment module.

[0463] Output: The payment is completed and a transaction success message is sent back to the server.

[0464] Specific operation: The payment module debits the virtual currency from the buyer's wallet, confirms whether the transaction is successful, and returns the transaction success information to the server. The server then notifies the buyer that the purchase procedure has been completed.

[0465] Step 11: Compensation calculation and determination

[0466] Input: Information about successful transactions.

[0467] Server: Based on the information of successful transactions, calculates and determines the remuneration to the seller.

[0468] Output: Calculated reward information.

[0469] Specific operation: The server analyzes the transaction information and calculates the seller's reward. The calculated reward information is sent to the payment module in the next step.

[0470] Step 12: Payment

[0471] Input: Calculated reward information.

[0472] Payment module: Pays the calculated reward in cryptocurrency to the seller's wallet.

[0473] Output: Information that the reward payment has been completed is sent back to the server.

[0474] Specific operation: The payment module transfers the reward to the seller's cryptocurrency wallet. This information is sent back to the server, which then notifies the completion of the reward payment.

[0475] Step 13: Update your trading history and rewards

[0476] Input: Information regarding payment completion.

[0477] Server: Updates the seller's dashboard with transaction history and reward information.

[0478] Output: Latest transaction history and reward information displayed on the seller dashboard.

[0479] Specific behavior: The server updates the seller's dashboard data to show the new transaction history and reward information.

[0480] Step 14: Obtaining Emotion Data

[0481] Input: Camera footage and audio data obtained from the buyer's device.

[0482] Emotion engine: Analyzes the user's emotional state in real time from camera footage and audio data.

[0483] Output: Recognized emotion data.

[0484] How it works: The emotion engine analyzes video and audio to identify emotions such as joy, sadness, and surprise, which are then sent to the server in real time.

[0485] Step 15: Analyze the emotion data

[0486] Input: Emotion data sent from the emotion engine.

[0487] Server: Receives emotion data and passes it to the generation AI module.

[0488] Output: A matching algorithm tuned based on emotion data.

[0489] How it works: The server analyzes the emotion data and passes it to the generative AI module, which then recommends products that reflect the user's emotional state.

[0490] Step 16: Adjusting the recommendation algorithm

[0491] Input: Emotion data and user needs information.

[0492] Generative AI module: Adjusts the matching algorithm based on emotion data.

[0493] Output: The adjusted recommendation results.

[0494] What it does: If users are happy, the algorithm adjusts to prioritize products that increase engagement. Adjusted matching results are generated.

[0495] Step 17: Displaying matching results (reflecting emotions)

[0496] Input: Adjusted recommendation results.

[0497] Server: Sends the adjusted matching results to the device.

[0498] Output: The best recommendation results displayed on the buyer's device.

[0499] How it works: The server sends the matching results prioritized based on emotions to the buyer's device, allowing the buyer to select products based on this.

[0500] (Application example 2)

[0501] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0502] Conventional digital content trading systems recommend content without considering the user's emotional state, resulting in low user satisfaction and inefficient trading. Furthermore, it is difficult to recommend appropriate content, making it difficult to provide optimal content that meets the buyer's needs.

[0503] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for uploading generated content to the Internet, means for executing artificial intelligence to extract features of the generated content, means for receiving needs information of purchasers, means for executing artificial intelligence to match the generated content with purchasers based on the needs information, means for making payments in virtual currency, means for detecting the emotional state of purchasers in real time and using an emotion recognition engine to recommend generated content based on that, and means for paying a reward to the seller according to the number of matches. This enables optimal content recommendations based on the user's emotions, thereby improving user satisfaction.

[0504] "Generated content" means information or data created by a user or creator and stored in digital form.

[0505] The "Internet" is a huge communications network that connects computers and networks around the world to each other and allows the exchange of information.

[0506] "Uploading" refers to the act of transferring data stored on a local computer or device to a remote server or online platform.

[0507] "Feature extraction" is the process of extracting specific information or attributes from content, and is often done automatically using artificial intelligence.

[0508] "Artificial intelligence" refers to computer systems and software that can mimic human intellectual activity and perform tasks such as problem solving, learning, and reasoning.

[0509] "Purchaser needs information" is information about the desired product or service entered by a user who wishes to make a purchase.

[0510] "Matching" refers to the act of matching the buyer's wants and needs with the products and services offered.

[0511] "Virtual currency" is a currency that is traded digitally and is often managed using blockchain technology.

[0512] "Settlement" refers to the process of paying for a transaction.

[0513] An "emotion recognition engine" is a system that recognizes a user's emotional state in real time by analyzing their camera footage and audio data.

[0514] "Emotional state" refers to the psychological and sensory state expressed by the user, including joy, sadness, surprise, etc.

[0515] "Recommendation" refers to the act of suggesting suitable products or services to a user.

[0516] "Paying compensation" refers to the act of paying compensation, such as money or virtual currency, for goods or services provided.

[0517] This invention is a system for smoothly trading generated digital content over the Internet, and in particular, by combining it with an emotion recognition engine, it realizes optimal content recommendations based on the user's emotional state.

[0518] The server is implemented as a system including the following means:

[0519] 1. A means of uploading generated content to the Internet

[0520] 2. Means for implementing artificial intelligence to extract features of the generated content.

[0521] 3. Means of receiving information on buyer needs

[0522] 4. A means for executing artificial intelligence to match the generated content with a purchaser based on the needs information.

[0523] 5. Means of making payments with virtual currency

[0524] 6. Using an emotion recognition engine to detect the buyer's emotional state in real time and recommend generated content based on that.

[0525] 7. A means for paying a reward to the seller according to the number of matches

[0526] Specifically, the system operates as follows.

[0527] Seller-initiated content uploads

[0528] Sellers log in to the platform using their own devices and upload their digital content. The uploaded content is then analyzed by an artificial intelligence module on the server, and the information is stored in a database for later use in matching and recommendations.

[0529] Inputting buyer needs and matching

[0530] The purchaser inputs and sends information about the content they need from their own device. The server receives this information, compares it with content in the database using an artificial intelligence module, and generates the best matching results.

[0531] Buyer Emotion Recognition

[0532] The system uses an emotion recognition engine to detect the buyer's emotional state in real time, analyzing the user's emotional state based on information obtained from the camera and microphone, and adjusting the content recommendations accordingly.

[0533] For example, if a purchaser is "smiling after watching a fantasy movie," similar fantasy works will be preferentially recommended based on that emotional state. In this way, providing content that matches the user's emotions can increase user satisfaction.

[0534] Specific examples

[0535] For example, if seller A uploads a digital art piece of "fantastic landscape painting," the generative AI module extracts and tags features such as "fantastic" and "landscape." If buyer B searches for "I want digital art of fantasy landscapes," the generative AI module will recommend seller A's digital art piece as the most suitable product, and if the emotion engine detects buyer B's happy emotions, it will prioritize products that are likely to further increase engagement based on those emotions. When buyer B selects a product and pays with virtual currency, seller A will receive a reward. During this process, seller A's reward may increase as the emotion engine improves the recommendation accuracy.

[0536] Prompt Sentence Examples

[0537] "We recommend the best content to users who smile after watching a fantasy movie, and process their purchases with virtual currency."

[0538] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0539] Step 1:

[0540] The seller logs in to the platform using their own device. Authentication is performed by entering the required information in the login form and clicking the "Login" button. The input at this stage is the user's authentication information, and the output is the result of authentication success or failure.

[0541] Step 2:

[0542] When a seller logs in to their account, they go to their My Page and click the "New Listing" button. This will display the digital content upload screen. The input data is the digital content file to be listed and its description information, and the output is a notification that the upload was successful.

[0543] Step 3:

[0544] The server stores the received content data in storage. It then invokes a generative AI module to automatically extract and tag the features of the uploaded content. The input is the uploaded digital content, and the output is its feature information and tags.

[0545] Step 4:

[0546] Purchasers access the service from their own devices and enter information about the digital content they are looking for on the search page. The input data includes search keywords and desired conditions, and the output is a click event on the search button to display matching results.

[0547] Step 5:

[0548] The server receives the needs information sent by the purchaser and passes it to the generation AI module. The generation AI module matches the needs information with registered content in the database and generates an optimal recommended content list. The input is the purchaser's needs information, and the output is a list of matched content.

[0549] Step 6:

[0550] The buyer's device is equipped with a camera and microphone, and an emotion recognition engine analyzes this data in real time. The input is camera footage and audio data, and the output is recognized emotional data. Based on this emotional data, the server displays a recommendation list of content that best suits the buyer's emotional state from the matching results.

[0551] Step 7:

[0552] The buyer selects the desired content from the recommended content and clicks the "Purchase" button. The input is the ID of the selected content, and the output is a transition to the payment page.

[0553] Step 8:

[0554] The buyer enters the cryptocurrency wallet information on the payment page and clicks the "Pay" button. The server then receives the payment information and passes it to the payment module. The input is the wallet information, and the output is the payment result.

[0555] Step 9:

[0556] The payment module processes and completes the payment in virtual currency. A notification of successful payment is sent back to the server, and the server notifies the buyer that the transaction has been completed. At this stage, a success notification from the payment module is input, and a transaction success notification is output.

[0557] Step 10:

[0558] The server calculates the reward to the seller based on the successful transaction information and pays the reward in virtual currency using the payment module. The input is the transaction information and the output is the payment of the reward to the seller's wallet.

[0559] Step 11:

[0560] The server updates the transaction history and reward information to the seller's dashboard and notifies the seller that the reward payment has been completed. The input is reward payment information, and the output is a notification and dashboard update.

[0561] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0562] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0563] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0564] [Second embodiment]

[0565] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0566] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0567] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0568] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0569] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0570] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0571] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0572] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0573] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0574] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0575] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0576] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0577] The present invention relates to a system for efficiently trading generated content over the Internet, and provides a means for smoothly trading digital content between sellers and buyers.

[0578] System Configuration

[0579] The system of this invention mainly consists of a server, a seller's terminal, and a buyer's terminal. The server is a central control device that communicates with and processes multiple terminals via the Internet. The terminals are devices through which users input or output data via an interface.

[0580] Seller-initiated content uploads

[0581] Device: The seller uses their device to access the platform interface. They select the "New Listing" button and fill out the form to upload their digital content (e.g., image files, 3D models, software).

[0582] Terminal: When the seller selects a file and clicks the upload button, the file and the entered information are sent to the server.

[0583] Server: The server receives this data and stores it in storage. A generative AI module is then invoked to extract features from the uploaded file and tag it appropriately.

[0584] Server: The extracted feature information and tags are stored in a database for later use in searching and matching.

[0585] Inputting buyer needs and matching

[0586] Device: Buyers access the platform using their own device and enter their requirements and needs for the desired product in the search bar, for example, "I want digital art of fantasy landscapes."

[0587] Terminal: When the buyer clicks the search button, their needs information is sent to the server.

[0588] Server: The server passes the received needs information to the generation AI module, which performs optimal matching. The generation AI module compares the needs information with the listing information in the database and lists the best-matching listing data.

[0589] Server: The matching results are sent to the buyer's device and displayed on the buyer's screen.

[0590] Checkout and payment

[0591] Terminal: The buyer selects the desired product from the displayed matching results and clicks the "Purchase" button, which will display the payment page.

[0592] Terminal: The buyer enters their cryptocurrency wallet information on the payment page and clicks the "Pay" button.

[0593] Server: The server receives the payment information and passes it to the payment module, which debits the specified cryptocurrency from the buyer's wallet and completes the transaction.

[0594] Payment module: verifies the success of the transaction and sends the result back to the server.

[0595] Payment of rewards to sellers

[0596] Server: Based on the information on successful transactions, the server calculates the seller's reward. The reward is determined based on the number of matches and the transaction amount.

[0597] Payment module: Pays the calculated reward to the seller's wallet in virtual currency.

[0598] Server: Updates the seller's dashboard with transaction history and reward information, and notifies the seller that the reward has been paid.

[0599] Specific examples

[0600] For example, Seller A uploads digital art of a "fantasy landscape," and the generative AI module extracts and tags features such as "fantasy" and "landscape." If Buyer B inputs, "I want digital art of a fantasy landscape," the generative AI module recommends Seller A's digital art as the most suitable product and displays it on Buyer B's screen. When Buyer B selects the product and pays with virtual currency, Seller A receives a reward.

[0601] The processing flow will be explained below.

[0602] Electronic data upload by seller

[0603] Step 1:

[0604] Sellers log in to the platform using their own devices, enter their login information and click the "Login" button.

[0605] Step 2:

[0606] The seller clicks the "New Listing" button on their My Page, which displays the upload form.

[0607] Step 3:

[0608] Sellers enter the category and product description on the form and upload electronic data files by dragging and dropping or selecting them from the file selection dialog.

[0609] Step 4:

[0610] When the seller clicks the "Upload" button, the entered information and file are sent to the server.

[0611] Step 5:

[0612] The server stores the received information and files in storage, then invokes the generative AI module to extract and tag the file features.

[0613] Step 6:

[0614] The server stores the characteristic information and tags in a database and registers them as listing information.

[0615] Inputting buyer needs and matching

[0616] Step 1:

[0617] Buyers access the platform using their own devices, go to the search page and enter their needs and desired products in the search bar.

[0618] Step 2:

[0619] When the purchaser clicks the "Search" button, the needs information is sent to the server.

[0620] Step 3:

[0621] The server passes the received needs information to the generation AI module, which searches the database for optimal listing information based on the needs information.

[0622] Step 4:

[0623] The generation AI module returns the matching results to the server, which then sends the matching results to the buyer's terminal and displays them.

[0624] Checkout and payment

[0625] Step 1:

[0626] The buyer selects the desired product from the displayed matching results and clicks the "Purchase" button.

[0627] Step 2:

[0628] The server receives the purchaser's selection and sends data to display the checkout page.

[0629] Step 3:

[0630] The buyer enters their cryptocurrency wallet information on the payment page and clicks the "Pay" button.

[0631] Step 4:

[0632] The server receives the payment information and forwards it to the payment module, which debits the specified cryptocurrency from the buyer's wallet to complete the transaction.

[0633] Step 5:

[0634] The payment module verifies the success of the transaction and sends the result back to the server, which notifies the buyer that the purchase has been completed.

[0635] Payment of rewards to sellers

[0636] Step 1:

[0637] The server calculates the seller's reward based on the information of successful transactions. The reward is determined according to the number of successful matches and the transaction amount.

[0638] Step 2:

[0639] The settlement module pays the calculated reward in virtual currency to the seller's wallet.

[0640] Step 3:

[0641] The server updates the transaction history and reward information on the seller's dashboard and notifies the seller that the reward payment has been completed.

[0642] Example 1

[0643] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0644] Conventional digital content trading systems struggled to efficiently handle the entire process of uploading content, extracting its features, matching it with buyer needs, settlement, and paying commissions to sellers. Furthermore, they lacked the ability to accurately interpret buyer needs and recommend appropriate products. Furthermore, there was no guarantee that payments in virtual currency or subsequent commission payments to sellers would be carried out smoothly. This hindered the smooth flow of transactions, preventing satisfaction for both sellers and buyers.

[0645] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0646] In this invention, the server includes means for uploading the generated content to the Internet, means for executing artificial intelligence to extract features of the generated content, means for receiving needs information of buyers, means for executing artificial intelligence to match the generated content with buyers based on the needs information, means for making payments in virtual currency, means for paying a reward to the seller according to the number of matches, means for extracting and tagging features of the generated content, and means for presenting optimal matching results based on the buyer's needs. This enables transactions between sellers and buyers to be carried out efficiently and smoothly, thereby improving the satisfaction of both parties and the success rate of transactions.

[0647] "Generated Content" means media in digital form that is created by Users and uploaded to the Platform.

[0648] "Means for uploading onto the Internet" refers to the software and hardware mechanisms for transmitting the generated content from the user's terminal to a server and publishing it on the Internet.

[0649] "Artificial intelligence for feature extraction" refers to algorithms and technologies that automatically identify the characteristics and attributes of uploaded content and obtain relevant information.

[0650] "Needs information" is information that indicates the conditions and requests that a purchaser has for a particular digital content.

[0651] "Artificial intelligence for matching" refers to algorithms and technologies that compare buyer needs information with generated content to find the best match.

[0652] A "virtual currency payment instrument" is a software and hardware mechanism that allows a transaction to be paid for and a purchase to be completed using virtual currency.

[0653] "Payment mechanism" means the software and hardware mechanism for paying a commission to a seller after a transaction is completed.

[0654] "Tagging" is the process of adding keywords or labels to content based on its characteristics to facilitate searching and categorization.

[0655] "Means for presenting optimal matching results based on needs" refers to the algorithms and technologies for searching for optimal content based on the needs information entered by the purchaser and presenting the results to the purchaser.

[0656] The present invention is a system for efficiently trading generated digital content, which is composed of a server, a seller's terminal, and a buyer's terminal. The server is a central device that communicates with multiple terminals via the Internet and controls the overall process. The terminals are devices through which users input or output data via an interface.

[0657] Seller-initiated content uploads

[0658] 1. Device: The seller accesses the platform interface using their device. The seller selects the "New Listing" button and fills in the required information in the form to upload digital content (e.g., image files, 3D models, software).

[0659] Example: Seller A logs into the platform from his / her computer and uploads a digital artwork of a "fantastic landscape."

[0660] Example prompt: Press the "New Listing" button and enter content information.

[0661] 2. Terminal: When the seller selects a file and clicks the upload button, the file and the entered information are sent to the server.

[0662] Content feature extraction and tagging

[0663] 3. Server: The server receives the files and meta information sent by the seller and stores them in a temporary storage area.

[0664] 4. Server: The server calls the generative AI module to analyze the uploaded content file. The generative AI module uses image processing algorithms to extract features such as color, shape, and theme, and then tag them appropriately.

[0665] Specific operation: The generation AI module generates tags such as "fantastic" and "landscape."

[0666] Example prompt: Extract file characteristics and generate appropriate tags.

[0667] 4. Server: Stores the extracted feature information and tags in a database so that they can be used for searching and matching.

[0668] Inputting buyer needs and matching

[0669] 1. Device: Buyers access the platform using their own device and enter their desired product requirements and needs in the search bar.

[0670] Example: Buyer B types into his computer, "I want digital art of a fantasy landscape."

[0671] Example prompt: Enter your needs in the product search bar.

[0672] 2. Terminal: When the buyer clicks the search button, their needs information is sent to the server.

[0673] 3. Server: The server passes the received needs information to the generation AI module, which performs optimal matching processing. The generation AI module compares the needs information with the listing information in the database and lists the most suitable listing data.

[0674] 4. Server: The matching results are sent to the buyer's device and displayed on the buyer's screen.

[0675] Example: The server recommends seller A's "fantastic landscape painting" to buyer B's needs.

[0676] Example prompt: List the products that best meet your needs.

[0677] Checkout and payment

[0678] 1. Terminal: The buyer selects the desired product from the displayed matching results and clicks the "Purchase" button, which displays the payment page.

[0679] Example: Buyer B selects a "fantastic landscape painting" and completes the payment procedure using virtual currency.

[0680] Example prompt: Please select a product and proceed with your purchase.

[0681] 2. Terminal: The buyer enters their cryptocurrency wallet information on the payment page and clicks the "Pay" button.

[0682] 3. Server: The server receives the payment information and passes it to the payment module, which debits the cryptocurrency from the buyer's wallet and completes the transaction.

[0683] 4. Payment module: Checks the success of the transaction and sends the result back to the server.

[0684] 5. Server: The server notifies the buyer's terminal that the transaction is complete.

[0685] Payment of rewards to sellers

[0686] 1. Server: Based on the successful transaction information, the server calculates the reward for the seller. The reward is determined based on the number of matches and the transaction amount.

[0687] 2. Payment module: Pays the calculated reward to the seller's wallet in cryptocurrency.

[0688] 3. Server: Updates the seller's dashboard with transaction history and reward information, and notifies the seller that the reward has been paid.

[0689] The above process flow ensures that digital content uploaded by sellers is delivered to buyers efficiently, ensuring smooth transactions. Furthermore, the generative AI module extracts features and tags them to ensure proper matching.

[0690] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0691] Step 1:

[0692] Seller Login

[0693] Input: The username and password entered on the seller's device.

[0694] How it works: The server validates the login information through the authentication module, searching the user database to see if a matching username and password combination exists.

[0695] Output: If authentication is successful, the seller will be shown the dashboard screen. If authentication is unsuccessful, a login error message will be displayed.

[0696] Step 2:

[0697] Uploading content

[0698] Input: Digital content (image files, 3D models, software) and meta information (title, description, price, etc.) uploaded from the seller's device.

[0699] How it works: The server receives the uploaded file and meta information and stores it in a temporary storage area.

[0700] Output: Success message and URL to save the file temporarily on the server.

[0701] Step 3:

[0702] Feature Extraction and Tagging

[0703] Input: Uploaded digital content files and their meta information.

[0704] How it works: The server calls the generative AI module to analyze the file, extracting features such as color, shape, and theme, and automatically generating appropriate tags.

[0705] Output: Feature information and generated tags. For example, tags such as "fantastic" and "landscape."

[0706] Step 4:

[0707] Database storage

[0708] Input: Feature information and tags.

[0709] How it works: The server stores the generated features and tags in a database, making them available for later searching and matching.

[0710] Output: Data stored in a database.

[0711] Step 5:

[0712] Buyer Login

[0713] Input: The username and password entered on the buyer's device.

[0714] How it works: The server validates the login information through the authentication module, searching the user database to see if a matching username and password combination exists.

[0715] Output: If authentication is successful, the buyer will be redirected to the dashboard screen. If authentication is unsuccessful, a login error message will be displayed.

[0716] Step 6:

[0717] Needs input

[0718] Input: The requirements and needs of the desired product entered by the buyer on their device. For example, "I want digital art of a fantasy landscape."

[0719] Behavior: The server temporarily stores the received needs information and prepares it for the next matching process.

[0720] Output: Temporarily saved needs information.

[0721] Step 7:

[0722] Matching process

[0723] Input: Temporarily saved needs information and listing information in the database.

[0724] How it works: The server calls the generation AI module, compares the needs information with the listing data in the database, and makes the best match to list the listing data that best suits the buyer.

[0725] Output: Listed listing data as a result of matching.

[0726] Step 8:

[0727] Matching results displayed

[0728] Input: The result of the match.

[0729] Operation: The server sends the matching results to the buyer's device and displays them on the buyer's screen.

[0730] Output: Matching results displayed on the buyer's device.

[0731] Step 9:

[0732] Product selection and purchase

[0733] Input: Product data and payment information (cryptocurrency wallet information) selected from the buyer's device.

[0734] How it works: After the buyer clicks the "Purchase" button, the server displays the payment page and receives payment information.

[0735] Output: Transaction data and payment information.

[0736] Step 10:

[0737] Payment Processing

[0738] Input: Cryptocurrency wallet information and transaction data provided by the buyer.

[0739] Action: The server uses the payment module to perform a virtual currency debit. If successful, the transaction is completed.

[0740] Output: Confirmation of payment completion and notification of transaction completion.

[0741] Step 11:

[0742] Remuneration calculation

[0743] Input: Successful transaction data.

[0744] How it works: The server calculates the seller's reward based on the transaction data. The reward is determined based on the number of matches and the transaction amount.

[0745] Output: The calculated reward amount.

[0746] Step 12:

[0747] Reward payment

[0748] Input: Calculated reward amount and seller wallet information.

[0749] How it works: The server uses the payment module to pay the reward in cryptocurrency to the seller's wallet. It then verifies that the payment was successful.

[0750] Output: Confirmation of payment completion.

[0751] Step 13:

[0752] Remuneration notification

[0753] Input: Completion information for reward payment.

[0754] What it does: The server updates the seller's dashboard with transaction history and reward information, and notifies them that the reward has been paid.

[0755] Output: Compensation information and transaction history displayed on the seller's dashboard.

[0756] (Application example 1)

[0757] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0758] In digital content trading, there is a demand for technology that allows for efficient and smooth transactions between sellers and buyers. In particular, there are challenges in quickly and accurately providing buyers with content that meets their needs from a vast amount of digital content, and in smoothly paying sellers. There is also a need for a method that allows for easy uploading via smartphone and automatic tag generation.

[0759] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0760] In this invention, the server includes means for uploading generated content to the Internet, means for executing artificial intelligence to extract features of the generated content, means for receiving needs information of buyers, means for executing artificial intelligence to match the generated content with buyers based on the needs information, means for making payments in virtual currency, means for paying a reward to the seller according to the number of matches, means for uploading digital content using a smartphone app, means for executing artificial intelligence to extract features from the uploaded digital content and automatically generate tags, and means for storing the generated tags and feature information in a database. This enables efficient transactions of digital content and improves usability for sellers and buyers.

[0761] "Generated content" is information or data created in digital form.

[0762] The "Internet" is a global communications medium for sending and receiving information over networks.

[0763] "Artificial intelligence for feature extraction" refers to techniques for identifying relevant characteristics from digital content and analyzing that information.

[0764] "Purchaser" means an individual or entity seeking to purchase digital content.

[0765] "Needs Information" refers to the requirements and conditions regarding the specific digital content that a purchaser desires.

[0766] "Artificial intelligence for matching" is a technology that optimally matches buyer needs information with the digital content being offered.

[0767] "Virtual currency" is a currency that is traded in digital form and is used as a means of payment online.

[0768] "Remuneration" refers to the consideration or profit that a seller receives from a transaction.

[0769] A "smartphone app" is a software program that runs on a smartphone.

[0770] A "tag" is a keyword or label added to digital content to make it easier to identify it.

[0771] A "database" is a system for efficiently storing, managing, and making searchable information.

[0772] This invention relates to a system for efficiently trading generated content over the Internet. Specifically, it is a platform where sellers upload digital content using a smartphone app, the features of that content are extracted and tagged using artificial intelligence (generative AI model), and buyers can search for and purchase content based on their needs.

[0773] System configuration and operation overview:

[0774] The system mainly consists of the following components:

[0775] 1. Server: A central device that stores data, processes data, performs artificial intelligence, and handles cryptocurrency payments.

[0776] 2. Seller's device (smartphone): Upload digital content.

[0777] 3. Buyer's device (smartphone, PC, etc.): Enter your needs information and search for and purchase content.

[0778] Seller Content Upload Instructions:

[0779] 1. Seller's device: Sellers use the smartphone app interface to upload digital content (e.g., image files, 3D models, music). To upload, they use the "New Listing" button and enter the required information.

[0780] 2. Server: Receives uploaded files and input information, stores them in storage, and then runs a generative AI model to extract features from the generated content.

[0781] 3. Server: Analyzes the content features using a generative AI model and adds appropriate tags. These features and tags are stored in a database.

[0782] Buyer needs input and matching procedure:

[0783] 1. Buyer's device: Buyers access the platform through a smartphone app or web interface and enter their desired content needs, such as a specific request for "digital art of fantasy landscapes."

[0784] 2. Server: Receives needs information and uses the generative AI model to match it with content in the database.

[0785] 3. Server: The optimal matching results are sent to the buyer's device, and the buyer can select the desired content from the displayed list.

[0786] Checkout and payment:

[0787] 1. Buyer's device: The buyer selects the content they want and clicks the "Purchase" button, which displays the payment page.

[0788] 2. Server: Receives information when a buyer makes a payment using a cryptocurrency wallet, completes the transaction using the payment module, verifies the success of the transaction, and notifies the buyer and seller of the result.

[0789] Seller Payment:

[0790] 1. Server: If the transaction is successful, calculate the seller's reward and pay it in virtual currency using the payment module.

[0791] 2. Server: Updates the transaction history and reward information on the seller's dashboard and notifies the seller that the reward has been paid.

[0792] Hardware and software used:

[0793] Hardware: Servers (e.g., AWS EC2), smartphones (iOS / Android)

[0794] Software: Python and Flask (web framework), TensorFlow / Keras (generative AI model) on the server side, Swift (iOS) or Java / Kotlin (Android) on the smartphone app side

[0795] Examples:

[0796] Seller A uploads a digital piece of art of a "fantastic landscape" using a smartphone app, and the generative AI model automatically generates tags such as "fantastic" and "landscape."

[0797] When Buyer B enters "I want digital art of fantasy landscapes," the AI ​​model recommends content from Seller A and displays it on Buyer B's screen.

[0798] When Buyer B selects a product and pays with virtual currency, Seller A is paid a reward in virtual currency.

[0799] Example prompt sentence:

[0800] "Analyze the visual features of an input digital image and generate appropriate tags based on those features."

[0801] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0802] Step 1:

[0803] Seller's device:

[0804] Sellers select the "New Listing" button on the smartphone app and upload digital content (e.g., image files, 3D models, music), while also entering the required information (title, description, price, etc.).

[0805] Step 2:

[0806] Seller's device:

[0807] When the seller clicks the upload button, the selected file and the entered information are sent to the server. The file information and metadata are packaged and sent as an HTTP request.

[0808] Step 3:

[0809] server:

[0810] The server receives the uploaded file and metadata and stores them in the specified storage. Once the storage is complete, it calls the generative AI model to extract the features of the uploaded file. Specifically, the saved file path is passed as input to the generative AI model, and the resulting feature data is output.

[0811] Step 4:

[0812] server:

[0813] The generative AI model analyzes the visual characteristics of the input file and generates appropriate tags. Specifically, it uses an image processing algorithm to extract features and then generates tags based on those features. In this process, the file path is given as input data and a tag list is obtained as output data.

[0814] Step 5:

[0815] server:

[0816] The extracted feature data and generated tags are stored in a database, which stores file paths, generated tags, file metadata, etc. The stored data is used for later searches and matching.

[0817] Step 6:

[0818] Buyer's device:

[0819] Buyers access the platform through a smartphone app or web interface and enter their desired digital content needs information. The needs information is entered in text format, and when the buyer clicks the search button, the information is sent to the server.

[0820] Step 7:

[0821] server:

[0822] The server receives the buyer's needs information and uses a generative AI model to match it with content in the database. The needs information is passed as input data to the generative AI model, and the optimal matching result is obtained as output data. Specifically, the needs information is analyzed using natural language processing technology and related content in the database is searched for.

[0823] Step 8:

[0824] server:

[0825] The matching results obtained from the generative AI model are sent to the buyer's device and displayed to the buyer. A list of matching results is generated as output data and displayed on the buyer's screen.

[0826] Step 9:

[0827] Buyer's device:

[0828] The buyer selects the desired content from the matching results and clicks the "Purchase" button. This action displays the payment page. The buyer enters their cryptocurrency wallet information and clicks the "Pay" button.

[0829] Step 10:

[0830] server:

[0831] The server receives the buyer's payment information and completes the transaction using the payment module. Specifically, it withdraws the specified cryptocurrency from the buyer's wallet, checks whether the transaction is successful, and then notifies the buyer and seller of the transaction result.

[0832] Step 11:

[0833] server:

[0834] If the transaction is successful, the seller's reward is calculated and paid in virtual currency using the payment module, which is then transferred to the seller's wallet.

[0835] Step 12:

[0836] server:

[0837] The transaction history and reward information will be updated on the seller's dashboard, and a notification will be sent to notify the seller that the reward payment has been completed. Sellers can check their transaction history and reward details by checking their dashboard.

[0838] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0839] The present invention relates to a system for efficiently trading generated content over the Internet, and realizes optimal recommendations through emotion recognition by combining an emotion engine to facilitate smooth trading of digital content between sellers and buyers.

[0840] System Configuration

[0841] The system of the present invention is composed of a server, a seller's terminal, a buyer's terminal, and an emotion engine. The server is a central control device that communicates with multiple terminals via the Internet and performs various processes. The terminals are devices through which users input and output data, and the emotion engine is a system for recognizing and analyzing user emotions in real time.

[0842] Seller-initiated content uploads

[0843] Device: Sellers log in to the platform using their own devices. Enter the required information in the login form and click the "Login" button.

[0844] Device: Sellers click the "New Listing" button on their My Page to go to the screen where they can upload their digital content. Here, they can enter the category and product description and select the digital data file.

[0845] Terminal: When the seller clicks the "Upload" button, the entered information and electronic data file are sent to the server.

[0846] Server: The server stores the received information and electronic data files in storage, then invokes the generative AI module to extract and tag the file features.

[0847] Server: The extracted feature information and tags are saved in a database and registered as listing information.

[0848] Inputting buyer needs and matching

[0849] Device: The buyer visits the platform's search page and enters their needs and desired digital content into the search bar.

[0850] Terminal: When the buyer clicks the "Search" button, the needs information is sent to the server.

[0851] Server: The server passes the received needs information to the generation AI module to search for the best listing information. The generation AI module compares this needs information with the listing information in the database and lists the best-matching listing data.

[0852] Server: The matching results are sent to the buyer's device and displayed on the buyer's screen.

[0853] Checkout and payment

[0854] Terminal: The buyer selects the desired product from the displayed matching results and clicks the "Purchase" button.

[0855] Server: The server receives the buyer's selection and sends the data to display the checkout page.

[0856] Terminal: The buyer enters their cryptocurrency wallet information on the payment page and clicks the "Pay" button.

[0857] Server: The server receives the payment information and passes it to the payment module, which debits the cryptocurrency from the buyer's wallet and completes the transaction.

[0858] Payment module: verifies the success of the transaction and sends the result back to the server, which then notifies the buyer that the purchase is complete.

[0859] Payment of rewards to sellers

[0860] Server: Based on the information of successful transactions, calculates the reward for the seller and determines the reward according to the number of successful matches and the transaction amount.

[0861] Payment module: Pays the calculated reward to the seller's wallet in virtual currency.

[0862] Server: Updates the seller's dashboard with transaction history and reward information, and notifies the seller that the reward has been paid.

[0863] Emotion engine integration

[0864] Emotion engine: Analyzes camera footage and audio data acquired from the user's device in real time to recognize the user's emotional state, such as happiness, sadness, surprise, etc.

[0865] Server: Based on the emotion data received from the emotion engine, the server adjusts the matching algorithm of the generative AI module to make recommendations that are optimal for the user's emotional state.

[0866] On your device: Shows matching listings based on your sentiment.

[0867] Specific examples

[0868] For example, if seller A uploads a digital art piece of "fantastic landscape painting," the generative AI module extracts and tags features such as "fantastic" and "landscape." If buyer B searches for "I want digital art of fantasy landscapes," the generative AI module will recommend seller A's digital art piece as the most suitable product, and if the emotion engine detects buyer B's happy emotions, it will prioritize products that are likely to further increase engagement based on those emotions. When buyer B selects a product and pays with virtual currency, seller A will receive a reward. During this process, seller A's reward may increase as the emotion engine improves the recommendation accuracy.

[0869] The processing flow will be explained below.

[0870] Electronic data upload by seller

[0871] Step 1:

[0872] Sellers log in to the platform using their own devices, enter their login information and click the "Login" button.

[0873] Step 2:

[0874] The seller clicks the "New Listing" button on their My Page, which displays the upload form.

[0875] Step 3:

[0876] Sellers enter the category and product description on the form and upload electronic data files by dragging and dropping or selecting them from the file selection dialog.

[0877] Step 4:

[0878] When the seller clicks the "Upload" button, the entered information and file are sent to the server.

[0879] Step 5:

[0880] The server stores the received information and files in storage, then invokes the generative AI module to extract and tag the file features.

[0881] Step 6:

[0882] The server stores the characteristic information and tags in a database and registers them as listing information.

[0883] Inputting buyer needs and matching

[0884] Step 1:

[0885] Buyers access the platform using their own devices, go to the search page and enter their needs and desired products in the search bar.

[0886] Step 2:

[0887] When the purchaser clicks the "Search" button, the needs information is sent to the server.

[0888] Step 3:

[0889] The server passes the received needs information to the generation AI module, which searches the database for optimal listing information based on the needs information.

[0890] Step 4:

[0891] The generation AI module returns the matching results to the server, which then sends the matching results to the buyer's terminal and displays them.

[0892] Checkout and payment

[0893] Step 1:

[0894] The buyer selects the desired product from the displayed matching results and clicks the "Purchase" button.

[0895] Step 2:

[0896] The server receives the purchaser's selection and sends data to display the checkout page.

[0897] Step 3:

[0898] The buyer enters their cryptocurrency wallet information on the payment page and clicks the "Pay" button.

[0899] Step 4:

[0900] The server receives the payment information and forwards it to the payment module, which debits the specified cryptocurrency from the buyer's wallet to complete the transaction.

[0901] Step 5:

[0902] The payment module verifies the success of the transaction and sends the result back to the server, which notifies the buyer that the purchase has been completed.

[0903] Payment of rewards to sellers

[0904] Step 1:

[0905] The server calculates the seller's reward based on the information of successful transactions. The reward is determined according to the number of successful matches and the transaction amount.

[0906] Step 2:

[0907] The settlement module pays the calculated reward in virtual currency to the seller's wallet.

[0908] Step 3:

[0909] The server updates the transaction history and reward information on the seller's dashboard and notifies the seller that the reward payment has been completed.

[0910] Emotion engine integration

[0911] Step 1:

[0912] The emotion engine analyzes camera footage and audio data acquired from the user's device in real time to recognize the user's emotional state.

[0913] Step 2:

[0914] The emotion engine transmits the recognized emotion data to the server.

[0915] Step 3:

[0916] The server adjusts the matching algorithm of the generation AI module based on the emotional data and makes recommendations that are optimal for the user's emotional state.

[0917] Step 4:

[0918] The server transmits the recommendation results based on the emotional state to the user's terminal and displays them.

[0919] Specific examples

[0920] Step 1:

[0921] Seller A uploads a digital piece of art of a "fantastic landscape painting," and the generative AI module extracts and tags features such as "fantastic" and "landscape."

[0922] Step 2:

[0923] When Buyer B searches for "I want digital art of fantasy landscapes," the generative AI module recommends Seller A's digital art as the most suitable product.

[0924] Step 3:

[0925] The emotion engine detects Buyer B's happy emotions and prioritizes displaying products that are likely to increase engagement based on those emotions.

[0926] Step 4:

[0927] When Buyer B selects a product and pays with virtual currency, Seller A receives a reward.

[0928] Step 5:

[0929] The server utilizes data from the emotion engine to learn and improve the accuracy of the recommendation algorithm.

[0930] Example 2

[0931] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0932] Current digital content trading systems face challenges such as low matching accuracy between sellers and buyers and a lack of personalized user experience. Furthermore, payment methods are limited, making smooth payments using virtual currencies difficult. Therefore, there is a demand for improved matching accuracy that takes user emotions into account, as well as dynamic payment functions using virtual currencies.

[0933] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0934] In this invention, the server includes a means for uploading the generated content to the Internet, a means for executing artificial intelligence to extract features of the generated content, and a means for receiving buyer needs information. This allows the server to recognize the user's emotional state in real time and adjust the matching algorithm, a means for making payments in virtual currency, and a means for paying rewards to sellers according to the number of matches. This improves the accuracy of matching, facilitates transactions between sellers and buyers, and enables smooth payments using virtual currency.

[0935] "Generated content" refers to data or works in digital form that are created using artificial intelligence or other digital technologies.

[0936] "Artificial intelligence" refers to technology that enables computer systems to imitate human intelligence, process and analyze data, and achieve more advanced decision-making and automation through self-learning.

[0937] "Purchaser needs information" refers to information that a user inputs explicitly or implicitly regarding the conditions and requirements for the product or service that the user desires.

[0938] An "emotion engine" refers to algorithms and technologies that recognize and analyze a user's emotional state in real time and adjust the system's behavior based on the results.

[0939] "Virtual currency" refers to a currency that uses cryptography to ensure the security of transactions and allows value to be exchanged digitally without the involvement of a central authority.

[0940] "Matching algorithm" refers to the calculation procedures and logic used to compare the buyer's needs information with the characteristics of the content generated by the seller and find the optimal combination.

[0941] "Reward" refers to the consideration or profit that an exhibitor receives when the content provided by the exhibitor is purchased.

[0942] "Receiving needs information" refers to the system taking in and processing information about the buyer's wishes and requirements.

[0943] The present invention relates to a system for efficiently trading generated content over the Internet. The system of the present invention comprises a server, a seller's terminal, a buyer's terminal, and an emotion engine. The server is a central control device that communicates with multiple terminals via the Internet and performs various processes. The terminals are devices through which users input and output, and the emotion engine is a system for recognizing and analyzing user emotions in real time.

[0944] First, the seller accesses the platform using their own device, enters the required information in the login form, and clicks the "Login" button. The server receives this login information, verifies the user information using the authentication module, and if authentication is successful, the seller is redirected to their personal page.

[0945] Next, when the seller clicks the "New Listing" button on their My Page, they are taken to the listing screen. Here, they enter the category and product description and select the electronic data file to be listed. When the seller clicks the "Upload" button, the entered information and the selected electronic data file are sent to the server. The server saves the received information and electronic data file in storage.

[0946] The server passes the saved electronic data file to a generation AI module, which extracts the file's characteristics. For example, a specific painting's data may be tagged with "fantastic" or "landscape." The extracted characteristic information and tags are stored in a database and registered as listing information. Once registration is complete, a notification of upload completion is displayed on the seller's device.

[0947] Meanwhile, buyers access the platform using their devices and enter keywords for the digital content they desire in the search bar. When the buyer clicks the "Search" button, the entered needs information is sent to the server. The server passes the received needs information to the generation AI module, which searches for the most suitable listing information. The generation AI module compares this information with the listing information in the database and lists the most suitable listing data. The matching results are sent to the buyer's device and displayed on the screen.

[0948] When a buyer selects the desired product and clicks the "Purchase" button, the selection information is sent to the server. The server receives the selected product information and sends data to display the payment page to the buyer. The buyer enters their virtual currency wallet information on the payment page and clicks the "Pay" button. The server receives the payment information and passes it to the payment module. The payment module deducts the virtual currency from the buyer's wallet and completes the transaction. Once the success of the transaction is confirmed, the result is sent back to the server, and the buyer is notified that the purchase procedure has been completed.

[0949] Based on the successful transaction information, the server calculates the reward for the seller and pays the reward in virtual currency to the seller's wallet through the payment module. The server then updates the transaction history and reward information on the seller's dashboard and notifies the seller that the reward payment has been completed.

[0950] The emotion engine analyzes camera footage and audio data acquired from the user's device in real time to recognize the user's emotional state. For example, it identifies the user's emotions such as joy, sadness, and surprise. The server adjusts the matching algorithm of the generation AI module based on the emotion data received from the emotion engine, and makes recommendations that are optimal for the user's emotional state. The adjusted matching results are displayed on the device, allowing the user to receive appropriate recommendations based on their emotions.

[0951] Specific examples

[0952] For example, if seller A uploads a digital art piece of "fantastic landscape painting," the generative AI module extracts and tags features such as "fantastic" and "landscape." If buyer B searches for "I want digital art of fantasy landscapes," the generative AI module will recommend seller A's digital art piece as the most suitable product. If the emotion engine detects buyer B's happy emotions, it will prioritize products that are likely to further increase engagement based on those emotions. When buyer B selects a product and pays with virtual currency, seller A will receive a reward. During this process, seller A's reward may increase as the emotion engine improves the recommendation accuracy.

[0953] Prompt Sentence Examples

[0954] Please explain, step by step, how the digital content of the fantastical landscape painting uploaded by Seller A matches the needs of Buyer B, and how the emotion engine uses Buyer B's emotions to make the optimal recommendation.

[0955] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0956] Step 1: Seller Login

[0957] Input: Username and password provided by the seller's device.

[0958] Server: Receives the submitted login information and passes it to the authentication module to verify the user information.

[0959] Output: If authentication is successful, the seller is redirected to their My Page and the display data of their My Page is sent to the terminal.

[0960] Specific operation: The seller enters the required information into the login form and clicks the "Login" button. The server receives this and verifies it with the user information in the database. Once verification is complete, the seller's personal page is generated and the data is sent to the terminal.

[0961] Step 2: New listing

[0962] Input: Category, product description, and electronic data file provided by the seller's terminal.

[0963] Terminal: When the seller clicks the "New Listing" button, the new listing screen will be displayed.

[0964] Specific operation: The seller enters the category and product description on the new listing screen and selects the electronic data file. When the seller clicks the "Upload" button, this information is sent to the server.

[0965] Step 3: Upload content

[0966] Input: Category, product description, and electronic data file sent from the seller's terminal.

[0967] Server: Stores received information and electronic data files in storage.

[0968] Output: The listing information is saved to storage.

[0969] Specific operation: The server writes and saves the received information and data file in the database storage. Once the saving is complete, it sends a notification to the seller that the upload is complete.

[0970] Step 4: Feature extraction and tagging

[0971] Input: Electronic data files stored in storage.

[0972] Server: Passes stored electronic data files to the generation AI module, which extracts file features.

[0973] Output: The extracted features and tags are stored in a database.

[0974] How it works: The generative AI module analyzes the data file and, for example, if it is a landscape painting, assigns tags such as "fantastic" or "landscape." These feature information and tags are then registered in a database.

[0975] Step 5: Enter your buyer's needs

[0976] Input: Search keywords provided by the buyer's device.

[0977] User (Buyer): The buyer enters the keywords for the desired content in the search bar and clicks the "Search" button.

[0978] Output: The input needs information is sent to the server.

[0979] Specific operation: The purchaser's device sends the entered keywords to the server, which prepares to pass them to the generation AI module.

[0980] Step 6: Submit your needs information

[0981] Input: The search term entered by the buyer.

[0982] Server: Passes the received needs information to the generation AI module.

[0983] Output: Matches that are compared with listings in the database.

[0984] Specific operation: The server provides the buyer's needs information to the generation AI module, which compares it with the listing information in the database and lists the most matching listing data.

[0985] Step 7: Viewing the matching results

[0986] Input: Matching results output from the generative AI module.

[0987] Server: Sends the matching results to the buyer's device.

[0988] Output: Matching results displayed on the buyer's device.

[0989] Specific operation: The buyer's device displays the matching results received from the server, and the buyer can review the results and select the desired product.

[0990] Step 8: Product Selection

[0991] Input: Information about the product selected by the buyer.

[0992] User (Buyer): The buyer selects the product they want and clicks the "Purchase" button.

[0993] Output: Product selection information is sent to the server.

[0994] Specific operation: The purchaser's device sends information about the selected product to the server.

[0995] Step 9: Enter your payment information

[0996] Input: Payment page data provided by the server, cryptocurrency wallet information entered by the buyer.

[0997] Server: Receives the selected product information and sends the payment page data to the buyer.

[0998] Output: The payment page is displayed on the buyer's device.

[0999] Specific operation: The payment page is displayed on the buyer's device, and the buyer enters their wallet information and clicks the "Pay" button, which is then sent to the server.

[1000] Step 10: Payment Processing

[1001] Input: Buyer's payment information.

[1002] Server: Receives payment information and passes it to the payment module.

[1003] Output: The payment is completed and a transaction success message is sent back to the server.

[1004] Specific operation: The payment module debits the virtual currency from the buyer's wallet, confirms whether the transaction is successful, and returns the transaction success information to the server. The server then notifies the buyer that the purchase procedure has been completed.

[1005] Step 11: Compensation calculation and determination

[1006] Input: Information about successful transactions.

[1007] Server: Based on the information of successful transactions, calculates and determines the remuneration to the seller.

[1008] Output: Calculated reward information.

[1009] Specific operation: The server analyzes the transaction information and calculates the seller's reward. The calculated reward information is sent to the payment module in the next step.

[1010] Step 12: Payment

[1011] Input: Calculated reward information.

[1012] Payment module: Pays the calculated reward in cryptocurrency to the seller's wallet.

[1013] Output: Information that the reward payment has been completed is sent back to the server.

[1014] Specific operation: The payment module transfers the reward to the seller's cryptocurrency wallet. This information is sent back to the server, which then notifies the completion of the reward payment.

[1015] Step 13: Update your trading history and rewards

[1016] Input: Information regarding payment completion.

[1017] Server: Updates the seller's dashboard with transaction history and reward information.

[1018] Output: Latest transaction history and reward information displayed on the seller dashboard.

[1019] Specific behavior: The server updates the seller's dashboard data to show the new transaction history and reward information.

[1020] Step 14: Obtaining Emotion Data

[1021] Input: Camera footage and audio data obtained from the buyer's device.

[1022] Emotion engine: Analyzes the user's emotional state in real time from camera footage and audio data.

[1023] Output: Recognized emotion data.

[1024] How it works: The emotion engine analyzes video and audio to identify emotions such as joy, sadness, and surprise, which are then sent to the server in real time.

[1025] Step 15: Analyze the emotion data

[1026] Input: Emotion data sent from the emotion engine.

[1027] Server: Receives emotion data and passes it to the generation AI module.

[1028] Output: A matching algorithm tuned based on emotion data.

[1029] How it works: The server analyzes the emotion data and passes it to the generative AI module, which then recommends products that reflect the user's emotional state.

[1030] Step 16: Adjusting the recommendation algorithm

[1031] Input: Emotion data and user needs information.

[1032] Generative AI module: Adjusts the matching algorithm based on emotion data.

[1033] Output: The adjusted recommendation results.

[1034] What it does: If users are happy, the algorithm adjusts to prioritize products that increase engagement. Adjusted matching results are generated.

[1035] Step 17: Displaying matching results (reflecting emotions)

[1036] Input: Adjusted recommendation results.

[1037] Server: Sends the adjusted matching results to the device.

[1038] Output: The best recommendation results displayed on the buyer's device.

[1039] How it works: The server sends the matching results prioritized based on emotions to the buyer's device, allowing the buyer to select products based on this.

[1040] (Application example 2)

[1041] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1042] Conventional digital content trading systems recommend content without considering the user's emotional state, resulting in low user satisfaction and inefficient trading. Furthermore, it is difficult to recommend appropriate content, making it difficult to provide optimal content that meets the buyer's needs.

[1043] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for uploading generated content to the Internet, means for executing artificial intelligence to extract features of the generated content, means for receiving needs information of purchasers, means for executing artificial intelligence to match the generated content with purchasers based on the needs information, means for making payments in virtual currency, means for detecting the emotional state of purchasers in real time and using an emotion recognition engine to recommend generated content based on that, and means for paying a reward to the seller according to the number of matches. This enables optimal content recommendations based on the user's emotions, thereby improving user satisfaction.

[1044] "Generated content" means information or data created by a user or creator and stored in digital form.

[1045] The "Internet" is a huge communications network that connects computers and networks around the world to each other and allows the exchange of information.

[1046] "Uploading" refers to the act of transferring data stored on a local computer or device to a remote server or online platform.

[1047] "Feature extraction" is the process of extracting specific information or attributes from content, and is often done automatically using artificial intelligence.

[1048] "Artificial intelligence" refers to computer systems and software that can mimic human intellectual activity and perform tasks such as problem solving, learning, and reasoning.

[1049] "Purchaser needs information" is information about the desired product or service entered by a user who wishes to make a purchase.

[1050] "Matching" refers to the act of matching the buyer's wants and needs with the products and services offered.

[1051] "Virtual currency" is a currency that is traded digitally and is often managed using blockchain technology.

[1052] "Settlement" refers to the process of paying for a transaction.

[1053] An "emotion recognition engine" is a system that recognizes a user's emotional state in real time by analyzing their camera footage and audio data.

[1054] "Emotional state" refers to the psychological and sensory state expressed by the user, including joy, sadness, surprise, etc.

[1055] "Recommendation" refers to the act of suggesting suitable products or services to a user.

[1056] "Paying compensation" refers to the act of paying compensation, such as money or virtual currency, for goods or services provided.

[1057] This invention is a system for smoothly trading generated digital content over the Internet, and in particular, by combining it with an emotion recognition engine, it realizes optimal content recommendations based on the user's emotional state.

[1058] The server is implemented as a system including the following means:

[1059] 1. A means of uploading generated content to the Internet

[1060] 2. Means for implementing artificial intelligence to extract features of the generated content.

[1061] 3. Means of receiving information on buyer needs

[1062] 4. A means for executing artificial intelligence to match the generated content with a purchaser based on the needs information.

[1063] 5. Means of making payments with virtual currency

[1064] 6. Using an emotion recognition engine to detect the buyer's emotional state in real time and recommend generated content based on that.

[1065] 7. A means for paying a reward to the seller according to the number of matches

[1066] Specifically, the system operates as follows.

[1067] Seller-initiated content uploads

[1068] Sellers log in to the platform using their own devices and upload their digital content. The uploaded content is then analyzed by an artificial intelligence module on the server, and the information is stored in a database for later use in matching and recommendations.

[1069] Inputting buyer needs and matching

[1070] The purchaser inputs and sends information about the content they need from their own device. The server receives this information, compares it with content in the database using an artificial intelligence module, and generates the best matching results.

[1071] Buyer Emotion Recognition

[1072] The system uses an emotion recognition engine to detect the buyer's emotional state in real time, analyzing the user's emotional state based on information obtained from the camera and microphone, and adjusting the content recommendations accordingly.

[1073] For example, if a purchaser is "smiling after watching a fantasy movie," similar fantasy works will be preferentially recommended based on that emotional state. In this way, providing content that matches the user's emotions can increase user satisfaction.

[1074] Specific examples

[1075] For example, if seller A uploads a digital art piece of "fantastic landscape painting," the generative AI module extracts and tags features such as "fantastic" and "landscape." If buyer B searches for "I want digital art of fantasy landscapes," the generative AI module will recommend seller A's digital art piece as the most suitable product, and if the emotion engine detects buyer B's happy emotions, it will prioritize products that are likely to further increase engagement based on those emotions. When buyer B selects a product and pays with virtual currency, seller A will receive a reward. During this process, seller A's reward may increase as the emotion engine improves the recommendation accuracy.

[1076] Prompt Sentence Examples

[1077] "We recommend the best content to users who smile after watching a fantasy movie, and process their purchases with virtual currency."

[1078] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1079] Step 1:

[1080] The seller logs in to the platform using their own device. Authentication is performed by entering the required information in the login form and clicking the "Login" button. The input at this stage is the user's authentication information, and the output is the result of authentication success or failure.

[1081] Step 2:

[1082] When a seller logs in to their account, they go to their My Page and click the "New Listing" button. This will display the digital content upload screen. The input data is the digital content file to be listed and its description information, and the output is a notification that the upload was successful.

[1083] Step 3:

[1084] The server stores the received content data in storage. It then invokes a generative AI module to automatically extract and tag the features of the uploaded content. The input is the uploaded digital content, and the output is its feature information and tags.

[1085] Step 4:

[1086] Purchasers access the service from their own devices and enter information about the digital content they are looking for on the search page. The input data includes search keywords and desired conditions, and the output is a click event on the search button to display matching results.

[1087] Step 5:

[1088] The server receives the needs information sent by the purchaser and passes it to the generation AI module. The generation AI module matches the needs information with registered content in the database and generates an optimal recommended content list. The input is the purchaser's needs information, and the output is a list of matched content.

[1089] Step 6:

[1090] The buyer's device is equipped with a camera and microphone, and an emotion recognition engine analyzes this data in real time. The input is camera footage and audio data, and the output is recognized emotional data. Based on this emotional data, the server displays a recommendation list of content that best suits the buyer's emotional state from the matching results.

[1091] Step 7:

[1092] The buyer selects the desired content from the recommended content and clicks the "Purchase" button. The input is the ID of the selected content, and the output is a transition to the payment page.

[1093] Step 8:

[1094] The buyer enters the cryptocurrency wallet information on the payment page and clicks the "Pay" button. The server then receives the payment information and passes it to the payment module. The input is the wallet information, and the output is the payment result.

[1095] Step 9:

[1096] The payment module processes and completes the payment in virtual currency. A notification of successful payment is sent back to the server, and the server notifies the buyer that the transaction has been completed. At this stage, a success notification from the payment module is input, and a transaction success notification is output.

[1097] Step 10:

[1098] The server calculates the reward to the seller based on the successful transaction information and pays the reward in virtual currency using the payment module. The input is the transaction information and the output is the payment of the reward to the seller's wallet.

[1099] Step 11:

[1100] The server updates the transaction history and reward information to the seller's dashboard and notifies the seller that the reward payment has been completed. The input is reward payment information, and the output is a notification and dashboard update.

[1101] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1102] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1103] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1104] [Third embodiment]

[1105] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1106] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1107] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1108] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1109] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1110] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1111] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1112] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1113] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1114] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1115] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1116] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1117] The present invention relates to a system for efficiently trading generated content over the Internet, and provides a means for smoothly trading digital content between sellers and buyers.

[1118] System Configuration

[1119] The system of this invention mainly consists of a server, a seller's terminal, and a buyer's terminal. The server is a central control device that communicates with and processes multiple terminals via the Internet. The terminals are devices through which users input or output data via an interface.

[1120] Seller-initiated content uploads

[1121] Device: The seller uses their device to access the platform interface. They select the "New Listing" button and fill out the form to upload their digital content (e.g., image files, 3D models, software).

[1122] Terminal: When the seller selects a file and clicks the upload button, the file and the entered information are sent to the server.

[1123] Server: The server receives this data and stores it in storage. A generative AI module is then invoked to extract features from the uploaded file and tag it appropriately.

[1124] Server: The extracted feature information and tags are stored in a database for later use in searching and matching.

[1125] Inputting buyer needs and matching

[1126] Device: Buyers access the platform using their own device and enter their requirements and needs for the desired product in the search bar, for example, "I want digital art of fantasy landscapes."

[1127] Terminal: When the buyer clicks the search button, their needs information is sent to the server.

[1128] Server: The server passes the received needs information to the generation AI module, which performs optimal matching. The generation AI module compares the needs information with the listing information in the database and lists the best-matching listing data.

[1129] Server: The matching results are sent to the buyer's device and displayed on the buyer's screen.

[1130] Checkout and payment

[1131] Terminal: The buyer selects the desired product from the displayed matching results and clicks the "Purchase" button, which will display the payment page.

[1132] Terminal: The buyer enters their cryptocurrency wallet information on the payment page and clicks the "Pay" button.

[1133] Server: The server receives the payment information and passes it to the payment module, which debits the specified cryptocurrency from the buyer's wallet and completes the transaction.

[1134] Payment module: verifies the success of the transaction and sends the result back to the server.

[1135] Payment of rewards to sellers

[1136] Server: Based on the information on successful transactions, the server calculates the seller's reward. The reward is determined based on the number of matches and the transaction amount.

[1137] Payment module: Pays the calculated reward to the seller's wallet in virtual currency.

[1138] Server: Updates the seller's dashboard with transaction history and reward information, and notifies the seller that the reward has been paid.

[1139] Specific examples

[1140] For example, Seller A uploads digital art of a "fantasy landscape," and the generative AI module extracts and tags features such as "fantasy" and "landscape." If Buyer B inputs, "I want digital art of a fantasy landscape," the generative AI module recommends Seller A's digital art as the most suitable product and displays it on Buyer B's screen. When Buyer B selects the product and pays with virtual currency, Seller A receives a reward.

[1141] The processing flow will be explained below.

[1142] Electronic data upload by seller

[1143] Step 1:

[1144] Sellers log in to the platform using their own devices, enter their login information and click the "Login" button.

[1145] Step 2:

[1146] The seller clicks the "New Listing" button on their My Page, which displays the upload form.

[1147] Step 3:

[1148] Sellers enter the category and product description on the form and upload electronic data files by dragging and dropping or selecting them from the file selection dialog.

[1149] Step 4:

[1150] When the seller clicks the "Upload" button, the entered information and file are sent to the server.

[1151] Step 5:

[1152] The server stores the received information and files in storage, then invokes the generative AI module to extract and tag the file features.

[1153] Step 6:

[1154] The server stores the characteristic information and tags in a database and registers them as listing information.

[1155] Inputting buyer needs and matching

[1156] Step 1:

[1157] Buyers access the platform using their own devices, go to the search page and enter their needs and desired products in the search bar.

[1158] Step 2:

[1159] When the purchaser clicks the "Search" button, the needs information is sent to the server.

[1160] Step 3:

[1161] The server passes the received needs information to the generation AI module, which searches the database for optimal listing information based on the needs information.

[1162] Step 4:

[1163] The generation AI module returns the matching results to the server, which then sends the matching results to the buyer's terminal and displays them.

[1164] Checkout and payment

[1165] Step 1:

[1166] The buyer selects the desired product from the displayed matching results and clicks the "Purchase" button.

[1167] Step 2:

[1168] The server receives the purchaser's selection and sends data to display the checkout page.

[1169] Step 3:

[1170] The buyer enters their cryptocurrency wallet information on the payment page and clicks the "Pay" button.

[1171] Step 4:

[1172] The server receives the payment information and forwards it to the payment module, which debits the specified cryptocurrency from the buyer's wallet to complete the transaction.

[1173] Step 5:

[1174] The payment module verifies the success of the transaction and sends the result back to the server, which notifies the buyer that the purchase has been completed.

[1175] Payment of rewards to sellers

[1176] Step 1:

[1177] The server calculates the seller's reward based on the information of successful transactions. The reward is determined according to the number of successful matches and the transaction amount.

[1178] Step 2:

[1179] The settlement module pays the calculated reward in virtual currency to the seller's wallet.

[1180] Step 3:

[1181] The server updates the transaction history and reward information on the seller's dashboard and notifies the seller that the reward payment has been completed.

[1182] Example 1

[1183] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1184] Conventional digital content trading systems struggled to efficiently handle the entire process of uploading content, extracting its features, matching it with buyer needs, settlement, and paying commissions to sellers. Furthermore, they lacked the ability to accurately interpret buyer needs and recommend appropriate products. Furthermore, there was no guarantee that payments in virtual currency or subsequent commission payments to sellers would be carried out smoothly. This hindered the smooth flow of transactions, preventing satisfaction for both sellers and buyers.

[1185] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1186] In this invention, the server includes means for uploading the generated content to the Internet, means for executing artificial intelligence to extract features of the generated content, means for receiving needs information of buyers, means for executing artificial intelligence to match the generated content with buyers based on the needs information, means for making payments in virtual currency, means for paying a reward to the seller according to the number of matches, means for extracting and tagging features of the generated content, and means for presenting optimal matching results based on the buyer's needs. This enables transactions between sellers and buyers to be carried out efficiently and smoothly, thereby improving the satisfaction of both parties and the success rate of transactions.

[1187] "Generated Content" means media in digital form that is created by Users and uploaded to the Platform.

[1188] "Means for uploading onto the Internet" refers to the software and hardware mechanisms for transmitting the generated content from the user's terminal to a server and publishing it on the Internet.

[1189] "Artificial intelligence for feature extraction" refers to algorithms and technologies that automatically identify the characteristics and attributes of uploaded content and obtain relevant information.

[1190] "Needs information" is information that indicates the conditions and requests that a purchaser has for a particular digital content.

[1191] "Artificial intelligence for matching" refers to algorithms and technologies that compare buyer needs information with generated content to find the best match.

[1192] A "virtual currency payment instrument" is a software and hardware mechanism that allows a transaction to be paid for and a purchase to be completed using virtual currency.

[1193] "Payment mechanism" means the software and hardware mechanism for paying a commission to a seller after a transaction is completed.

[1194] "Tagging" is the process of adding keywords or labels to content based on its characteristics to facilitate searching and categorization.

[1195] "Means for presenting optimal matching results based on needs" refers to the algorithms and technologies for searching for optimal content based on the needs information entered by the purchaser and presenting the results to the purchaser.

[1196] The present invention is a system for efficiently trading generated digital content, which is composed of a server, a seller's terminal, and a buyer's terminal. The server is a central device that communicates with multiple terminals via the Internet and controls the overall process. The terminals are devices through which users input or output data via an interface.

[1197] Seller-initiated content uploads

[1198] 1. Device: The seller accesses the platform interface using their device. The seller selects the "New Listing" button and fills in the required information in the form to upload digital content (e.g., image files, 3D models, software).

[1199] Example: Seller A logs into the platform from his / her computer and uploads a digital artwork of a "fantastic landscape."

[1200] Example prompt: Press the "New Listing" button and enter content information.

[1201] 2. Terminal: When the seller selects a file and clicks the upload button, the file and the entered information are sent to the server.

[1202] Content feature extraction and tagging

[1203] 3. Server: The server receives the files and meta information sent by the seller and stores them in a temporary storage area.

[1204] 4. Server: The server calls the generative AI module to analyze the uploaded content file. The generative AI module uses image processing algorithms to extract features such as color, shape, and theme, and then tag them appropriately.

[1205] Specific operation: The generation AI module generates tags such as "fantastic" and "landscape."

[1206] Example prompt: Extract file characteristics and generate appropriate tags.

[1207] 4. Server: Stores the extracted feature information and tags in a database so that they can be used for searching and matching.

[1208] Inputting buyer needs and matching

[1209] 1. Device: Buyers access the platform using their own device and enter their desired product requirements and needs in the search bar.

[1210] Example: Buyer B types into his computer, "I want digital art of a fantasy landscape."

[1211] Example prompt: Enter your needs in the product search bar.

[1212] 2. Terminal: When the buyer clicks the search button, their needs information is sent to the server.

[1213] 3. Server: The server passes the received needs information to the generation AI module, which performs optimal matching processing. The generation AI module compares the needs information with the listing information in the database and lists the most suitable listing data.

[1214] 4. Server: The matching results are sent to the buyer's device and displayed on the buyer's screen.

[1215] Example: The server recommends seller A's "fantastic landscape painting" to buyer B's needs.

[1216] Example prompt: List the products that best meet your needs.

[1217] Checkout and payment

[1218] 1. Terminal: The buyer selects the desired product from the displayed matching results and clicks the "Purchase" button, which displays the payment page.

[1219] Example: Buyer B selects a "fantastic landscape painting" and completes the payment procedure using virtual currency.

[1220] Example prompt: Please select a product and proceed with your purchase.

[1221] 2. Terminal: The buyer enters their cryptocurrency wallet information on the payment page and clicks the "Pay" button.

[1222] 3. Server: The server receives the payment information and passes it to the payment module, which debits the cryptocurrency from the buyer's wallet and completes the transaction.

[1223] 4. Payment module: Checks the success of the transaction and sends the result back to the server.

[1224] 5. Server: The server notifies the buyer's terminal that the transaction is complete.

[1225] Payment of rewards to sellers

[1226] 1. Server: Based on the successful transaction information, the server calculates the reward for the seller. The reward is determined based on the number of matches and the transaction amount.

[1227] 2. Payment module: Pays the calculated reward to the seller's wallet in cryptocurrency.

[1228] 3. Server: Updates the seller's dashboard with transaction history and reward information, and notifies the seller that the reward has been paid.

[1229] The above process flow ensures that digital content uploaded by sellers is delivered to buyers efficiently, ensuring smooth transactions. Furthermore, the generative AI module extracts features and tags them to ensure proper matching.

[1230] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1231] Step 1:

[1232] Seller Login

[1233] Input: The username and password entered on the seller's device.

[1234] How it works: The server validates the login information through the authentication module, searching the user database to see if a matching username and password combination exists.

[1235] Output: If authentication is successful, the seller will be shown the dashboard screen. If authentication is unsuccessful, a login error message will be displayed.

[1236] Step 2:

[1237] Uploading content

[1238] Input: Digital content (image files, 3D models, software) and meta information (title, description, price, etc.) uploaded from the seller's device.

[1239] How it works: The server receives the uploaded file and meta information and stores it in a temporary storage area.

[1240] Output: Success message and URL to save the file temporarily on the server.

[1241] Step 3:

[1242] Feature Extraction and Tagging

[1243] Input: Uploaded digital content files and their meta information.

[1244] How it works: The server calls the generative AI module to analyze the file, extracting features such as color, shape, and theme, and automatically generating appropriate tags.

[1245] Output: Feature information and generated tags. For example, tags such as "fantastic" and "landscape."

[1246] Step 4:

[1247] Database storage

[1248] Input: Feature information and tags.

[1249] How it works: The server stores the generated features and tags in a database, making them available for later searching and matching.

[1250] Output: Data stored in a database.

[1251] Step 5:

[1252] Buyer Login

[1253] Input: The username and password entered on the buyer's device.

[1254] How it works: The server validates the login information through the authentication module, searching the user database to see if a matching username and password combination exists.

[1255] Output: If authentication is successful, the buyer will be redirected to the dashboard screen. If authentication is unsuccessful, a login error message will be displayed.

[1256] Step 6:

[1257] Needs input

[1258] Input: The requirements and needs of the desired product entered by the buyer on their device. For example, "I want digital art of a fantasy landscape."

[1259] Behavior: The server temporarily stores the received needs information and prepares it for the next matching process.

[1260] Output: Temporarily saved needs information.

[1261] Step 7:

[1262] Matching process

[1263] Input: Temporarily saved needs information and listing information in the database.

[1264] How it works: The server calls the generation AI module, compares the needs information with the listing data in the database, and makes the best match to list the listing data that best suits the buyer.

[1265] Output: Listed listing data as a result of matching.

[1266] Step 8:

[1267] Matching results displayed

[1268] Input: The result of the match.

[1269] Operation: The server sends the matching results to the buyer's device and displays them on the buyer's screen.

[1270] Output: Matching results displayed on the buyer's device.

[1271] Step 9:

[1272] Product selection and purchase

[1273] Input: Product data and payment information (cryptocurrency wallet information) selected from the buyer's device.

[1274] How it works: After the buyer clicks the "Purchase" button, the server displays the payment page and receives payment information.

[1275] Output: Transaction data and payment information.

[1276] Step 10:

[1277] Payment Processing

[1278] Input: Cryptocurrency wallet information and transaction data provided by the buyer.

[1279] Action: The server uses the payment module to perform a virtual currency debit. If successful, the transaction is completed.

[1280] Output: Confirmation of payment completion and notification of transaction completion.

[1281] Step 11:

[1282] Remuneration calculation

[1283] Input: Successful transaction data.

[1284] How it works: The server calculates the seller's reward based on the transaction data. The reward is determined based on the number of matches and the transaction amount.

[1285] Output: The calculated reward amount.

[1286] Step 12:

[1287] Reward payment

[1288] Input: Calculated reward amount and seller wallet information.

[1289] How it works: The server uses the payment module to pay the reward in cryptocurrency to the seller's wallet. It then verifies that the payment was successful.

[1290] Output: Confirmation of payment completion.

[1291] Step 13:

[1292] Remuneration notification

[1293] Input: Completion information for reward payment.

[1294] What it does: The server updates the seller's dashboard with transaction history and reward information, and notifies them that the reward has been paid.

[1295] Output: Compensation information and transaction history displayed on the seller's dashboard.

[1296] (Application example 1)

[1297] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1298] In digital content trading, there is a demand for technology that allows for efficient and smooth transactions between sellers and buyers. In particular, there are challenges in quickly and accurately providing buyers with content that meets their needs from a vast amount of digital content, and in smoothly paying sellers. There is also a need for a method that allows for easy uploading via smartphone and automatic tag generation.

[1299] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1300] In this invention, the server includes means for uploading generated content to the Internet, means for executing artificial intelligence to extract features of the generated content, means for receiving needs information of buyers, means for executing artificial intelligence to match the generated content with buyers based on the needs information, means for making payments in virtual currency, means for paying a reward to the seller according to the number of matches, means for uploading digital content using a smartphone app, means for executing artificial intelligence to extract features from the uploaded digital content and automatically generate tags, and means for storing the generated tags and feature information in a database. This enables efficient transactions of digital content and improves usability for sellers and buyers.

[1301] "Generated content" is information or data created in digital form.

[1302] The "Internet" is a global communications medium for sending and receiving information over networks.

[1303] "Artificial intelligence for feature extraction" refers to techniques for identifying relevant characteristics from digital content and analyzing that information.

[1304] "Purchaser" means an individual or entity seeking to purchase digital content.

[1305] "Needs Information" refers to the requirements and conditions regarding the specific digital content that a purchaser desires.

[1306] "Artificial intelligence for matching" is a technology that optimally matches buyer needs information with the digital content being offered.

[1307] "Virtual currency" is a currency that is traded in digital form and is used as a means of payment online.

[1308] "Remuneration" refers to the consideration or profit that a seller receives from a transaction.

[1309] A "smartphone app" is a software program that runs on a smartphone.

[1310] A "tag" is a keyword or label added to digital content to make it easier to identify it.

[1311] A "database" is a system for efficiently storing, managing, and making searchable information.

[1312] This invention relates to a system for efficiently trading generated content over the Internet. Specifically, it is a platform where sellers upload digital content using a smartphone app, the features of that content are extracted and tagged using artificial intelligence (generative AI model), and buyers can search for and purchase content based on their needs.

[1313] System configuration and operation overview:

[1314] The system mainly consists of the following components:

[1315] 1. Server: A central device that stores data, processes data, performs artificial intelligence, and handles cryptocurrency payments.

[1316] 2. Seller's device (smartphone): Upload digital content.

[1317] 3. Buyer's device (smartphone, PC, etc.): Enter your needs information and search for and purchase content.

[1318] Seller Content Upload Instructions:

[1319] 1. Seller's device: Sellers use the smartphone app interface to upload digital content (e.g., image files, 3D models, music). To upload, they use the "New Listing" button and enter the required information.

[1320] 2. Server: Receives uploaded files and input information, stores them in storage, and then runs a generative AI model to extract features from the generated content.

[1321] 3. Server: Analyzes the content features using a generative AI model and adds appropriate tags. These features and tags are stored in a database.

[1322] Buyer needs input and matching procedure:

[1323] 1. Buyer's device: Buyers access the platform through a smartphone app or web interface and enter their desired content needs, such as a specific request for "digital art of fantasy landscapes."

[1324] 2. Server: Receives needs information and uses the generative AI model to match it with content in the database.

[1325] 3. Server: The optimal matching results are sent to the buyer's device, and the buyer can select the desired content from the displayed list.

[1326] Checkout and payment:

[1327] 1. Buyer's device: The buyer selects the content they want and clicks the "Purchase" button, which displays the payment page.

[1328] 2. Server: Receives information when a buyer makes a payment using a cryptocurrency wallet, completes the transaction using the payment module, verifies the success of the transaction, and notifies the buyer and seller of the result.

[1329] Seller Payment:

[1330] 1. Server: If the transaction is successful, calculate the seller's reward and pay it in virtual currency using the payment module.

[1331] 2. Server: Updates the transaction history and reward information on the seller's dashboard and notifies the seller that the reward has been paid.

[1332] Hardware and software used:

[1333] Hardware: Servers (e.g., AWS EC2), smartphones (iOS / Android)

[1334] Software: Python and Flask (web framework), TensorFlow / Keras (generative AI model) on the server side, Swift (iOS) or Java / Kotlin (Android) on the smartphone app side

[1335] Examples:

[1336] Seller A uploads a digital piece of art of a "fantastic landscape" using a smartphone app, and the generative AI model automatically generates tags such as "fantastic" and "landscape."

[1337] When Buyer B enters "I want digital art of fantasy landscapes," the AI ​​model recommends content from Seller A and displays it on Buyer B's screen.

[1338] When Buyer B selects a product and pays with virtual currency, Seller A is paid a reward in virtual currency.

[1339] Example prompt sentence:

[1340] "Analyze the visual features of an input digital image and generate appropriate tags based on those features."

[1341] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1342] Step 1:

[1343] Seller's device:

[1344] Sellers select the "New Listing" button on the smartphone app and upload digital content (e.g., image files, 3D models, music), while also entering the required information (title, description, price, etc.).

[1345] Step 2:

[1346] Seller's device:

[1347] When the seller clicks the upload button, the selected file and the entered information are sent to the server. The file information and metadata are packaged and sent as an HTTP request.

[1348] Step 3:

[1349] server:

[1350] The server receives the uploaded file and metadata and stores them in the specified storage. Once the storage is complete, it calls the generative AI model to extract the features of the uploaded file. Specifically, the saved file path is passed as input to the generative AI model, and the resulting feature data is output.

[1351] Step 4:

[1352] server:

[1353] The generative AI model analyzes the visual characteristics of the input file and generates appropriate tags. Specifically, it uses an image processing algorithm to extract features and then generates tags based on those features. In this process, the file path is given as input data and a tag list is obtained as output data.

[1354] Step 5:

[1355] server:

[1356] The extracted feature data and generated tags are stored in a database, which stores file paths, generated tags, file metadata, etc. The stored data is used for later searches and matching.

[1357] Step 6:

[1358] Buyer's device:

[1359] Buyers access the platform through a smartphone app or web interface and enter their desired digital content needs information. The needs information is entered in text format, and when the buyer clicks the search button, the information is sent to the server.

[1360] Step 7:

[1361] server:

[1362] The server receives the buyer's needs information and uses a generative AI model to match it with content in the database. The needs information is passed as input data to the generative AI model, and the optimal matching result is obtained as output data. Specifically, the needs information is analyzed using natural language processing technology and related content in the database is searched for.

[1363] Step 8:

[1364] server:

[1365] The matching results obtained from the generative AI model are sent to the buyer's device and displayed to the buyer. A list of matching results is generated as output data and displayed on the buyer's screen.

[1366] Step 9:

[1367] Buyer's device:

[1368] The buyer selects the desired content from the matching results and clicks the "Purchase" button. This action displays the payment page. The buyer enters their cryptocurrency wallet information and clicks the "Pay" button.

[1369] Step 10:

[1370] server:

[1371] The server receives the buyer's payment information and completes the transaction using the payment module. Specifically, it withdraws the specified cryptocurrency from the buyer's wallet, checks whether the transaction is successful, and then notifies the buyer and seller of the transaction result.

[1372] Step 11:

[1373] server:

[1374] If the transaction is successful, the seller's reward is calculated and paid in virtual currency using the payment module, which is then transferred to the seller's wallet.

[1375] Step 12:

[1376] server:

[1377] The transaction history and reward information will be updated on the seller's dashboard, and a notification will be sent to notify the seller that the reward payment has been completed. Sellers can check their transaction history and reward details by checking their dashboard.

[1378] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1379] The present invention relates to a system for efficiently trading generated content over the Internet, and realizes optimal recommendations through emotion recognition by combining an emotion engine to facilitate smooth trading of digital content between sellers and buyers.

[1380] System Configuration

[1381] The system of the present invention is composed of a server, a seller's terminal, a buyer's terminal, and an emotion engine. The server is a central control device that communicates with multiple terminals via the Internet and performs various processes. The terminals are devices through which users input and output data, and the emotion engine is a system for recognizing and analyzing user emotions in real time.

[1382] Seller-initiated content uploads

[1383] Device: Sellers log in to the platform using their own devices. Enter the required information in the login form and click the "Login" button.

[1384] Device: Sellers click the "New Listing" button on their My Page to go to the screen where they can upload their digital content. Here, they can enter the category and product description and select the digital data file.

[1385] Terminal: When the seller clicks the "Upload" button, the entered information and electronic data file are sent to the server.

[1386] Server: The server stores the received information and electronic data files in storage, then invokes the generative AI module to extract and tag the file features.

[1387] Server: The extracted feature information and tags are saved in a database and registered as listing information.

[1388] Inputting buyer needs and matching

[1389] Device: The buyer visits the platform's search page and enters their needs and desired digital content into the search bar.

[1390] Terminal: When the buyer clicks the "Search" button, the needs information is sent to the server.

[1391] Server: The server passes the received needs information to the generation AI module to search for the best listing information. The generation AI module compares this needs information with the listing information in the database and lists the best-matching listing data.

[1392] Server: The matching results are sent to the buyer's device and displayed on the buyer's screen.

[1393] Checkout and payment

[1394] Terminal: The buyer selects the desired product from the displayed matching results and clicks the "Purchase" button.

[1395] Server: The server receives the buyer's selection and sends the data to display the checkout page.

[1396] Terminal: The buyer enters their cryptocurrency wallet information on the payment page and clicks the "Pay" button.

[1397] Server: The server receives the payment information and passes it to the payment module, which debits the cryptocurrency from the buyer's wallet and completes the transaction.

[1398] Payment module: verifies the success of the transaction and sends the result back to the server, which then notifies the buyer that the purchase is complete.

[1399] Payment of rewards to sellers

[1400] Server: Based on the information of successful transactions, calculates the reward for the seller and determines the reward according to the number of successful matches and the transaction amount.

[1401] Payment module: Pays the calculated reward to the seller's wallet in virtual currency.

[1402] Server: Updates the seller's dashboard with transaction history and reward information, and notifies the seller that the reward has been paid.

[1403] Emotion engine integration

[1404] Emotion engine: Analyzes camera footage and audio data acquired from the user's device in real time to recognize the user's emotional state, such as happiness, sadness, surprise, etc.

[1405] Server: Based on the emotion data received from the emotion engine, the server adjusts the matching algorithm of the generative AI module to make recommendations that are optimal for the user's emotional state.

[1406] On your device: Shows matching listings based on your sentiment.

[1407] Specific examples

[1408] For example, if seller A uploads a digital art piece of "fantastic landscape painting," the generative AI module extracts and tags features such as "fantastic" and "landscape." If buyer B searches for "I want digital art of fantasy landscapes," the generative AI module will recommend seller A's digital art piece as the most suitable product, and if the emotion engine detects buyer B's happy emotions, it will prioritize products that are likely to further increase engagement based on those emotions. When buyer B selects a product and pays with virtual currency, seller A will receive a reward. During this process, seller A's reward may increase as the emotion engine improves the recommendation accuracy.

[1409] The processing flow will be explained below.

[1410] Electronic data upload by seller

[1411] Step 1:

[1412] Sellers log in to the platform using their own devices, enter their login information and click the "Login" button.

[1413] Step 2:

[1414] The seller clicks the "New Listing" button on their My Page, which displays the upload form.

[1415] Step 3:

[1416] Sellers enter the category and product description on the form and upload electronic data files by dragging and dropping or selecting them from the file selection dialog.

[1417] Step 4:

[1418] When the seller clicks the "Upload" button, the entered information and file are sent to the server.

[1419] Step 5:

[1420] The server stores the received information and files in storage, then invokes the generative AI module to extract and tag the file features.

[1421] Step 6:

[1422] The server stores the characteristic information and tags in a database and registers them as listing information.

[1423] Inputting buyer needs and matching

[1424] Step 1:

[1425] Buyers access the platform using their own devices, go to the search page and enter their needs and desired products in the search bar.

[1426] Step 2:

[1427] When the purchaser clicks the "Search" button, the needs information is sent to the server.

[1428] Step 3:

[1429] The server passes the received needs information to the generation AI module, which searches the database for optimal listing information based on the needs information.

[1430] Step 4:

[1431] The generation AI module returns the matching results to the server, which then sends the matching results to the buyer's terminal and displays them.

[1432] Checkout and payment

[1433] Step 1:

[1434] The buyer selects the desired product from the displayed matching results and clicks the "Purchase" button.

[1435] Step 2:

[1436] The server receives the purchaser's selection and sends data to display the checkout page.

[1437] Step 3:

[1438] The buyer enters their cryptocurrency wallet information on the payment page and clicks the "Pay" button.

[1439] Step 4:

[1440] The server receives the payment information and forwards it to the payment module, which debits the specified cryptocurrency from the buyer's wallet to complete the transaction.

[1441] Step 5:

[1442] The payment module verifies the success of the transaction and sends the result back to the server, which notifies the buyer that the purchase has been completed.

[1443] Payment of rewards to sellers

[1444] Step 1:

[1445] The server calculates the seller's reward based on the information of successful transactions. The reward is determined according to the number of successful matches and the transaction amount.

[1446] Step 2:

[1447] The settlement module pays the calculated reward in virtual currency to the seller's wallet.

[1448] Step 3:

[1449] The server updates the transaction history and reward information on the seller's dashboard and notifies the seller that the reward payment has been completed.

[1450] Emotion engine integration

[1451] Step 1:

[1452] The emotion engine analyzes camera footage and audio data acquired from the user's device in real time to recognize the user's emotional state.

[1453] Step 2:

[1454] The emotion engine transmits the recognized emotion data to the server.

[1455] Step 3:

[1456] The server adjusts the matching algorithm of the generation AI module based on the emotional data and makes recommendations that are optimal for the user's emotional state.

[1457] Step 4:

[1458] The server transmits the recommendation results based on the emotional state to the user's terminal and displays them.

[1459] Specific examples

[1460] Step 1:

[1461] Seller A uploads a digital piece of art of a "fantastic landscape painting," and the generative AI module extracts and tags features such as "fantastic" and "landscape."

[1462] Step 2:

[1463] When Buyer B searches for "I want digital art of fantasy landscapes," the generative AI module recommends Seller A's digital art as the most suitable product.

[1464] Step 3:

[1465] The emotion engine detects Buyer B's happy emotions and prioritizes displaying products that are likely to increase engagement based on those emotions.

[1466] Step 4:

[1467] When Buyer B selects a product and pays with virtual currency, Seller A receives a reward.

[1468] Step 5:

[1469] The server utilizes data from the emotion engine to learn and improve the accuracy of the recommendation algorithm.

[1470] Example 2

[1471] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1472] Current digital content trading systems face challenges such as low matching accuracy between sellers and buyers and a lack of personalized user experience. Furthermore, payment methods are limited, making smooth payments using virtual currencies difficult. Therefore, there is a demand for improved matching accuracy that takes user emotions into account, as well as dynamic payment functions using virtual currencies.

[1473] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1474] In this invention, the server includes a means for uploading the generated content to the Internet, a means for executing artificial intelligence to extract features of the generated content, and a means for receiving buyer needs information. This allows the server to recognize the user's emotional state in real time and adjust the matching algorithm, a means for making payments in virtual currency, and a means for paying rewards to sellers according to the number of matches. This improves the accuracy of matching, facilitates transactions between sellers and buyers, and enables smooth payments using virtual currency.

[1475] "Generated content" refers to data or works in digital form that are created using artificial intelligence or other digital technologies.

[1476] "Artificial intelligence" refers to technology that enables computer systems to imitate human intelligence, process and analyze data, and achieve more advanced decision-making and automation through self-learning.

[1477] "Purchaser needs information" refers to information that a user inputs explicitly or implicitly regarding the conditions and requirements for the product or service that the user desires.

[1478] An "emotion engine" refers to algorithms and technologies that recognize and analyze a user's emotional state in real time and adjust the system's behavior based on the results.

[1479] "Virtual currency" refers to a currency that uses cryptography to ensure the security of transactions and allows value to be exchanged digitally without the involvement of a central authority.

[1480] "Matching algorithm" refers to the calculation procedures and logic used to compare the buyer's needs information with the characteristics of the content generated by the seller and find the optimal combination.

[1481] "Reward" refers to the consideration or profit that an exhibitor receives when the content provided by the exhibitor is purchased.

[1482] "Receiving needs information" refers to the system taking in and processing information about the buyer's wishes and requirements.

[1483] The present invention relates to a system for efficiently trading generated content over the Internet. The system of the present invention comprises a server, a seller's terminal, a buyer's terminal, and an emotion engine. The server is a central control device that communicates with multiple terminals via the Internet and performs various processes. The terminals are devices through which users input and output, and the emotion engine is a system for recognizing and analyzing user emotions in real time.

[1484] First, the seller accesses the platform using their own device, enters the required information in the login form, and clicks the "Login" button. The server receives this login information, verifies the user information using the authentication module, and if authentication is successful, the seller is redirected to their personal page.

[1485] Next, when the seller clicks the "New Listing" button on their My Page, they are taken to the listing screen. Here, they enter the category and product description and select the electronic data file to be listed. When the seller clicks the "Upload" button, the entered information and the selected electronic data file are sent to the server. The server saves the received information and electronic data file in storage.

[1486] The server passes the saved electronic data file to a generation AI module, which extracts the file's characteristics. For example, a specific painting's data may be tagged with "fantastic" or "landscape." The extracted characteristic information and tags are stored in a database and registered as listing information. Once registration is complete, a notification of upload completion is displayed on the seller's device.

[1487] Meanwhile, buyers access the platform using their devices and enter keywords for the digital content they desire in the search bar. When the buyer clicks the "Search" button, the entered needs information is sent to the server. The server passes the received needs information to the generation AI module, which searches for the most suitable listing information. The generation AI module compares this information with the listing information in the database and lists the most suitable listing data. The matching results are sent to the buyer's device and displayed on the screen.

[1488] When a buyer selects the desired product and clicks the "Purchase" button, the selection information is sent to the server. The server receives the selected product information and sends data to display the payment page to the buyer. The buyer enters their virtual currency wallet information on the payment page and clicks the "Pay" button. The server receives the payment information and passes it to the payment module. The payment module deducts the virtual currency from the buyer's wallet and completes the transaction. Once the success of the transaction is confirmed, the result is sent back to the server, and the buyer is notified that the purchase procedure has been completed.

[1489] Based on the successful transaction information, the server calculates the reward for the seller and pays the reward in virtual currency to the seller's wallet through the payment module. The server then updates the transaction history and reward information on the seller's dashboard and notifies the seller that the reward payment has been completed.

[1490] The emotion engine analyzes camera footage and audio data acquired from the user's device in real time to recognize the user's emotional state. For example, it identifies the user's emotions such as joy, sadness, and surprise. The server adjusts the matching algorithm of the generation AI module based on the emotion data received from the emotion engine, and makes recommendations that are optimal for the user's emotional state. The adjusted matching results are displayed on the device, allowing the user to receive appropriate recommendations based on their emotions.

[1491] Specific examples

[1492] For example, if seller A uploads a digital art piece of "fantastic landscape painting," the generative AI module extracts and tags features such as "fantastic" and "landscape." If buyer B searches for "I want digital art of fantasy landscapes," the generative AI module will recommend seller A's digital art piece as the most suitable product. If the emotion engine detects buyer B's happy emotions, it will prioritize products that are likely to further increase engagement based on those emotions. When buyer B selects a product and pays with virtual currency, seller A will receive a reward. During this process, seller A's reward may increase as the emotion engine improves the recommendation accuracy.

[1493] Prompt Sentence Examples

[1494] Please explain, step by step, how the digital content of the fantastical landscape painting uploaded by Seller A matches the needs of Buyer B, and how the emotion engine uses Buyer B's emotions to make the optimal recommendation.

[1495] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1496] Step 1: Seller Login

[1497] Input: Username and password provided by the seller's device.

[1498] Server: Receives the submitted login information and passes it to the authentication module to verify the user information.

[1499] Output: If authentication is successful, the seller is redirected to their My Page and the display data of their My Page is sent to the terminal.

[1500] Specific operation: The seller enters the required information into the login form and clicks the "Login" button. The server receives this and verifies it with the user information in the database. Once verification is complete, the seller's personal page is generated and the data is sent to the terminal.

[1501] Step 2: New listing

[1502] Input: Category, product description, and electronic data file provided by the seller's terminal.

[1503] Terminal: When the seller clicks the "New Listing" button, the new listing screen will be displayed.

[1504] Specific operation: The seller enters the category and product description on the new listing screen and selects the electronic data file. When the seller clicks the "Upload" button, this information is sent to the server.

[1505] Step 3: Upload content

[1506] Input: Category, product description, and electronic data file sent from the seller's terminal.

[1507] Server: Stores received information and electronic data files in storage.

[1508] Output: The listing information is saved to storage.

[1509] Specific operation: The server writes and saves the received information and data file in the database storage. Once the saving is complete, it sends a notification to the seller that the upload is complete.

[1510] Step 4: Feature extraction and tagging

[1511] Input: Electronic data files stored in storage.

[1512] Server: Passes stored electronic data files to the generation AI module, which extracts file features.

[1513] Output: The extracted features and tags are stored in a database.

[1514] How it works: The generative AI module analyzes the data file and, for example, if it is a landscape painting, assigns tags such as "fantastic" or "landscape." These feature information and tags are then registered in a database.

[1515] Step 5: Enter your buyer's needs

[1516] Input: Search keywords provided by the buyer's device.

[1517] User (Buyer): The buyer enters the keywords for the desired content in the search bar and clicks the "Search" button.

[1518] Output: The input needs information is sent to the server.

[1519] Specific operation: The purchaser's device sends the entered keywords to the server, which prepares to pass them to the generation AI module.

[1520] Step 6: Submit your needs information

[1521] Input: The search term entered by the buyer.

[1522] Server: Passes the received needs information to the generation AI module.

[1523] Output: Matches that are compared with listings in the database.

[1524] Specific operation: The server provides the buyer's needs information to the generation AI module, which compares it with the listing information in the database and lists the most matching listing data.

[1525] Step 7: Viewing the matching results

[1526] Input: Matching results output from the generative AI module.

[1527] Server: Sends the matching results to the buyer's device.

[1528] Output: Matching results displayed on the buyer's device.

[1529] Specific operation: The buyer's device displays the matching results received from the server, and the buyer can review the results and select the desired product.

[1530] Step 8: Product Selection

[1531] Input: Information about the product selected by the buyer.

[1532] User (Buyer): The buyer selects the product they want and clicks the "Purchase" button.

[1533] Output: Product selection information is sent to the server.

[1534] Specific operation: The purchaser's device sends information about the selected product to the server.

[1535] Step 9: Enter your payment information

[1536] Input: Payment page data provided by the server, cryptocurrency wallet information entered by the buyer.

[1537] Server: Receives the selected product information and sends the payment page data to the buyer.

[1538] Output: The payment page is displayed on the buyer's device.

[1539] Specific operation: The payment page is displayed on the buyer's device, and the buyer enters their wallet information and clicks the "Pay" button, which is then sent to the server.

[1540] Step 10: Payment Processing

[1541] Input: Buyer's payment information.

[1542] Server: Receives payment information and passes it to the payment module.

[1543] Output: The payment is completed and a transaction success message is sent back to the server.

[1544] Specific operation: The payment module debits the virtual currency from the buyer's wallet, confirms whether the transaction is successful, and returns the transaction success information to the server. The server then notifies the buyer that the purchase procedure has been completed.

[1545] Step 11: Compensation calculation and determination

[1546] Input: Information about successful transactions.

[1547] Server: Based on the information of successful transactions, calculates and determines the remuneration to the seller.

[1548] Output: Calculated reward information.

[1549] Specific operation: The server analyzes the transaction information and calculates the seller's reward. The calculated reward information is sent to the payment module in the next step.

[1550] Step 12: Payment

[1551] Input: Calculated reward information.

[1552] Payment module: Pays the calculated reward in cryptocurrency to the seller's wallet.

[1553] Output: Information that the reward payment has been completed is sent back to the server.

[1554] Specific operation: The payment module transfers the reward to the seller's cryptocurrency wallet. This information is sent back to the server, which then notifies the completion of the reward payment.

[1555] Step 13: Update your trading history and rewards

[1556] Input: Information regarding payment completion.

[1557] Server: Updates the seller's dashboard with transaction history and reward information.

[1558] Output: Latest transaction history and reward information displayed on the seller dashboard.

[1559] Specific behavior: The server updates the seller's dashboard data to show the new transaction history and reward information.

[1560] Step 14: Obtaining Emotion Data

[1561] Input: Camera footage and audio data obtained from the buyer's device.

[1562] Emotion engine: Analyzes the user's emotional state in real time from camera footage and audio data.

[1563] Output: Recognized emotion data.

[1564] How it works: The emotion engine analyzes video and audio to identify emotions such as joy, sadness, and surprise, which are then sent to the server in real time.

[1565] Step 15: Analyze the emotion data

[1566] Input: Emotion data sent from the emotion engine.

[1567] Server: Receives emotion data and passes it to the generation AI module.

[1568] Output: A matching algorithm tuned based on emotion data.

[1569] How it works: The server analyzes the emotion data and passes it to the generative AI module, which then recommends products that reflect the user's emotional state.

[1570] Step 16: Adjusting the recommendation algorithm

[1571] Input: Emotion data and user needs information.

[1572] Generative AI module: Adjusts the matching algorithm based on emotion data.

[1573] Output: The adjusted recommendation results.

[1574] What it does: If users are happy, the algorithm adjusts to prioritize products that increase engagement. Adjusted matching results are generated.

[1575] Step 17: Displaying matching results (reflecting emotions)

[1576] Input: Adjusted recommendation results.

[1577] Server: Sends the adjusted matching results to the device.

[1578] Output: The best recommendation results displayed on the buyer's device.

[1579] How it works: The server sends the matching results prioritized based on emotions to the buyer's device, allowing the buyer to select products based on this.

[1580] (Application example 2)

[1581] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1582] Conventional digital content trading systems recommend content without considering the user's emotional state, resulting in low user satisfaction and inefficient trading. Furthermore, it is difficult to recommend appropriate content, making it difficult to provide optimal content that meets the buyer's needs.

[1583] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for uploading generated content to the Internet, means for executing artificial intelligence to extract features of the generated content, means for receiving needs information of purchasers, means for executing artificial intelligence to match the generated content with purchasers based on the needs information, means for making payments in virtual currency, means for detecting the emotional state of purchasers in real time and using an emotion recognition engine to recommend generated content based on that, and means for paying a reward to the seller according to the number of matches. This enables optimal content recommendations based on the user's emotions, thereby improving user satisfaction.

[1584] "Generated content" means information or data created by a user or creator and stored in digital form.

[1585] The "Internet" is a huge communications network that connects computers and networks around the world to each other and allows the exchange of information.

[1586] "Uploading" refers to the act of transferring data stored on a local computer or device to a remote server or online platform.

[1587] "Feature extraction" is the process of extracting specific information or attributes from content, and is often done automatically using artificial intelligence.

[1588] "Artificial intelligence" refers to computer systems and software that can mimic human intellectual activity and perform tasks such as problem solving, learning, and reasoning.

[1589] "Purchaser needs information" is information about the desired product or service entered by a user who wishes to make a purchase.

[1590] "Matching" refers to the act of matching the buyer's wants and needs with the products and services offered.

[1591] "Virtual currency" is a currency that is traded digitally and is often managed using blockchain technology.

[1592] "Settlement" refers to the process of paying for a transaction.

[1593] An "emotion recognition engine" is a system that recognizes a user's emotional state in real time by analyzing their camera footage and audio data.

[1594] "Emotional state" refers to the psychological and sensory state expressed by the user, including joy, sadness, surprise, etc.

[1595] "Recommendation" refers to the act of suggesting suitable products or services to a user.

[1596] "Paying compensation" refers to the act of paying compensation, such as money or virtual currency, for goods or services provided.

[1597] This invention is a system for smoothly trading generated digital content over the Internet, and in particular, by combining it with an emotion recognition engine, it realizes optimal content recommendations based on the user's emotional state.

[1598] The server is implemented as a system including the following means:

[1599] 1. A means of uploading generated content to the Internet

[1600] 2. Means for implementing artificial intelligence to extract features of the generated content.

[1601] 3. Means of receiving information on buyer needs

[1602] 4. A means for executing artificial intelligence to match the generated content with a purchaser based on the needs information.

[1603] 5. Means of making payments with virtual currency

[1604] 6. Using an emotion recognition engine to detect the buyer's emotional state in real time and recommend generated content based on that.

[1605] 7. A means for paying a reward to the seller according to the number of matches

[1606] Specifically, the system operates as follows.

[1607] Seller-initiated content uploads

[1608] Sellers log in to the platform using their own devices and upload their digital content. The uploaded content is then analyzed by an artificial intelligence module on the server, and the information is stored in a database for later use in matching and recommendations.

[1609] Inputting buyer needs and matching

[1610] The purchaser inputs and sends information about the content they need from their own device. The server receives this information, compares it with content in the database using an artificial intelligence module, and generates the best matching results.

[1611] Buyer Emotion Recognition

[1612] The system uses an emotion recognition engine to detect the buyer's emotional state in real time, analyzing the user's emotional state based on information obtained from the camera and microphone, and adjusting the content recommendations accordingly.

[1613] For example, if a purchaser is "smiling after watching a fantasy movie," similar fantasy works will be preferentially recommended based on that emotional state. In this way, providing content that matches the user's emotions can increase user satisfaction.

[1614] Specific examples

[1615] For example, if seller A uploads a digital art piece of "fantastic landscape painting," the generative AI module extracts and tags features such as "fantastic" and "landscape." If buyer B searches for "I want digital art of fantasy landscapes," the generative AI module will recommend seller A's digital art piece as the most suitable product, and if the emotion engine detects buyer B's happy emotions, it will prioritize products that are likely to further increase engagement based on those emotions. When buyer B selects a product and pays with virtual currency, seller A will receive a reward. During this process, seller A's reward may increase as the emotion engine improves the recommendation accuracy.

[1616] Prompt Sentence Examples

[1617] "We recommend the best content to users who smile after watching a fantasy movie, and process their purchases with virtual currency."

[1618] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1619] Step 1:

[1620] The seller logs in to the platform using their own device. Authentication is performed by entering the required information in the login form and clicking the "Login" button. The input at this stage is the user's authentication information, and the output is the result of authentication success or failure.

[1621] Step 2:

[1622] When a seller logs in to their account, they go to their My Page and click the "New Listing" button. This will display the digital content upload screen. The input data is the digital content file to be listed and its description information, and the output is a notification that the upload was successful.

[1623] Step 3:

[1624] The server stores the received content data in storage. It then invokes a generative AI module to automatically extract and tag the features of the uploaded content. The input is the uploaded digital content, and the output is its feature information and tags.

[1625] Step 4:

[1626] Purchasers access the service from their own devices and enter information about the digital content they are looking for on the search page. The input data includes search keywords and desired conditions, and the output is a click event on the search button to display matching results.

[1627] Step 5:

[1628] The server receives the needs information sent by the purchaser and passes it to the generation AI module. The generation AI module matches the needs information with registered content in the database and generates an optimal recommended content list. The input is the purchaser's needs information, and the output is a list of matched content.

[1629] Step 6:

[1630] The buyer's device is equipped with a camera and microphone, and an emotion recognition engine analyzes this data in real time. The input is camera footage and audio data, and the output is recognized emotional data. Based on this emotional data, the server displays a recommendation list of content that best suits the buyer's emotional state from the matching results.

[1631] Step 7:

[1632] The buyer selects the desired content from the recommended content and clicks the "Purchase" button. The input is the ID of the selected content, and the output is a transition to the payment page.

[1633] Step 8:

[1634] The buyer enters the cryptocurrency wallet information on the payment page and clicks the "Pay" button. The server then receives the payment information and passes it to the payment module. The input is the wallet information, and the output is the payment result.

[1635] Step 9:

[1636] The payment module processes and completes the payment in virtual currency. A notification of successful payment is sent back to the server, and the server notifies the buyer that the transaction has been completed. At this stage, a success notification from the payment module is input, and a transaction success notification is output.

[1637] Step 10:

[1638] The server calculates the reward to the seller based on the successful transaction information and pays the reward in virtual currency using the payment module. The input is the transaction information and the output is the payment of the reward to the seller's wallet.

[1639] Step 11:

[1640] The server updates the transaction history and reward information to the seller's dashboard and notifies the seller that the reward payment has been completed. The input is reward payment information, and the output is a notification and dashboard update.

[1641] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1642] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1643] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1644] [Fourth embodiment]

[1645] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1646] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1647] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1648] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1649] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1650] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1651] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1652] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1653] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1654] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1655] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1656] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1657] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1658] The present invention relates to a system for efficiently trading generated content over the Internet, and provides a means for smoothly trading digital content between sellers and buyers.

[1659] System Configuration

[1660] The system of this invention mainly consists of a server, a seller's terminal, and a buyer's terminal. The server is a central control device that communicates with and processes multiple terminals via the Internet. The terminals are devices through which users input or output data via an interface.

[1661] Seller-initiated content uploads

[1662] Device: The seller uses their device to access the platform interface. They select the "New Listing" button and fill out the form to upload their digital content (e.g., image files, 3D models, software).

[1663] Terminal: When the seller selects a file and clicks the upload button, the file and the entered information are sent to the server.

[1664] Server: The server receives this data and stores it in storage. A generative AI module is then invoked to extract features from the uploaded file and tag it appropriately.

[1665] Server: The extracted feature information and tags are stored in a database for later use in searching and matching.

[1666] Inputting buyer needs and matching

[1667] Device: Buyers access the platform using their own device and enter their requirements and needs for the desired product in the search bar, for example, "I want digital art of fantasy landscapes."

[1668] Terminal: When the buyer clicks the search button, their needs information is sent to the server.

[1669] Server: The server passes the received needs information to the generation AI module, which performs optimal matching. The generation AI module compares the needs information with the listing information in the database and lists the best-matching listing data.

[1670] Server: The matching results are sent to the buyer's device and displayed on the buyer's screen.

[1671] Checkout and payment

[1672] Terminal: The buyer selects the desired product from the displayed matching results and clicks the "Purchase" button, which will display the payment page.

[1673] Terminal: The buyer enters their cryptocurrency wallet information on the payment page and clicks the "Pay" button.

[1674] Server: The server receives the payment information and passes it to the payment module, which debits the specified cryptocurrency from the buyer's wallet and completes the transaction.

[1675] Payment module: verifies the success of the transaction and sends the result back to the server.

[1676] Payment of rewards to sellers

[1677] Server: Based on the information on successful transactions, the server calculates the seller's reward. The reward is determined based on the number of matches and the transaction amount.

[1678] Payment module: Pays the calculated reward to the seller's wallet in virtual currency.

[1679] Server: Updates the seller's dashboard with transaction history and reward information, and notifies the seller that the reward has been paid.

[1680] Specific examples

[1681] For example, Seller A uploads digital art of a "fantasy landscape," and the generative AI module extracts and tags features such as "fantasy" and "landscape." If Buyer B inputs, "I want digital art of a fantasy landscape," the generative AI module recommends Seller A's digital art as the most suitable product and displays it on Buyer B's screen. When Buyer B selects the product and pays with virtual currency, Seller A receives a reward.

[1682] The processing flow will be explained below.

[1683] Electronic data upload by seller

[1684] Step 1:

[1685] Sellers log in to the platform using their own devices, enter their login information and click the "Login" button.

[1686] Step 2:

[1687] The seller clicks the "New Listing" button on their My Page, which displays the upload form.

[1688] Step 3:

[1689] Sellers enter the category and product description on the form and upload electronic data files by dragging and dropping or selecting them from the file selection dialog.

[1690] Step 4:

[1691] When the seller clicks the "Upload" button, the entered information and file are sent to the server.

[1692] Step 5:

[1693] The server stores the received information and files in storage, then invokes the generative AI module to extract and tag the file features.

[1694] Step 6:

[1695] The server stores the characteristic information and tags in a database and registers them as listing information.

[1696] Inputting buyer needs and matching

[1697] Step 1:

[1698] Buyers access the platform using their own devices, go to the search page and enter their needs and desired products in the search bar.

[1699] Step 2:

[1700] When the purchaser clicks the "Search" button, the needs information is sent to the server.

[1701] Step 3:

[1702] The server passes the received needs information to the generation AI module, which searches the database for optimal listing information based on the needs information.

[1703] Step 4:

[1704] The generation AI module returns the matching results to the server, which then sends the matching results to the buyer's terminal and displays them.

[1705] Checkout and payment

[1706] Step 1:

[1707] The buyer selects the desired product from the displayed matching results and clicks the "Purchase" button.

[1708] Step 2:

[1709] The server receives the purchaser's selection and sends data to display the checkout page.

[1710] Step 3:

[1711] The buyer enters their cryptocurrency wallet information on the payment page and clicks the "Pay" button.

[1712] Step 4:

[1713] The server receives the payment information and forwards it to the payment module, which debits the specified cryptocurrency from the buyer's wallet to complete the transaction.

[1714] Step 5:

[1715] The payment module verifies the success of the transaction and sends the result back to the server, which notifies the buyer that the purchase has been completed.

[1716] Payment of rewards to sellers

[1717] Step 1:

[1718] The server calculates the seller's reward based on the information of successful transactions. The reward is determined according to the number of successful matches and the transaction amount.

[1719] Step 2:

[1720] The settlement module pays the calculated reward in virtual currency to the seller's wallet.

[1721] Step 3:

[1722] The server updates the transaction history and reward information on the seller's dashboard and notifies the seller that the reward payment has been completed.

[1723] Example 1

[1724] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1725] Conventional digital content trading systems struggled to efficiently handle the entire process of uploading content, extracting its features, matching it with buyer needs, settlement, and paying commissions to sellers. Furthermore, they lacked the ability to accurately interpret buyer needs and recommend appropriate products. Furthermore, there was no guarantee that payments in virtual currency or subsequent commission payments to sellers would be carried out smoothly. This hindered the smooth flow of transactions, preventing satisfaction for both sellers and buyers.

[1726] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1727] In this invention, the server includes means for uploading the generated content to the Internet, means for executing artificial intelligence to extract features of the generated content, means for receiving needs information of buyers, means for executing artificial intelligence to match the generated content with buyers based on the needs information, means for making payments in virtual currency, means for paying a reward to the seller according to the number of matches, means for extracting and tagging features of the generated content, and means for presenting optimal matching results based on the buyer's needs. This enables transactions between sellers and buyers to be carried out efficiently and smoothly, thereby improving the satisfaction of both parties and the success rate of transactions.

[1728] "Generated Content" means media in digital form that is created by Users and uploaded to the Platform.

[1729] "Means for uploading onto the Internet" refers to the software and hardware mechanisms for transmitting the generated content from the user's terminal to a server and publishing it on the Internet.

[1730] "Artificial intelligence for feature extraction" refers to algorithms and technologies that automatically identify the characteristics and attributes of uploaded content and obtain relevant information.

[1731] "Needs information" is information that indicates the conditions and requests that a purchaser has for a particular digital content.

[1732] "Artificial intelligence for matching" refers to algorithms and technologies that compare buyer needs information with generated content to find the best match.

[1733] A "virtual currency payment instrument" is a software and hardware mechanism that allows a transaction to be paid for and a purchase to be completed using virtual currency.

[1734] "Payment mechanism" means the software and hardware mechanism for paying a commission to a seller after a transaction is completed.

[1735] "Tagging" is the process of adding keywords or labels to content based on its characteristics to facilitate searching and categorization.

[1736] "Means for presenting optimal matching results based on needs" refers to the algorithms and technologies for searching for optimal content based on the needs information entered by the purchaser and presenting the results to the purchaser.

[1737] The present invention is a system for efficiently trading generated digital content, which is composed of a server, a seller's terminal, and a buyer's terminal. The server is a central device that communicates with multiple terminals via the Internet and controls the overall process. The terminals are devices through which users input or output data via an interface.

[1738] Seller-initiated content uploads

[1739] 1. Device: The seller accesses the platform interface using their device. The seller selects the "New Listing" button and fills in the required information in the form to upload digital content (e.g., image files, 3D models, software).

[1740] Example: Seller A logs into the platform from his / her computer and uploads a digital artwork of a "fantastic landscape."

[1741] Example prompt: Press the "New Listing" button and enter content information.

[1742] 2. Terminal: When the seller selects a file and clicks the upload button, the file and the entered information are sent to the server.

[1743] Content feature extraction and tagging

[1744] 3. Server: The server receives the files and meta information sent by the seller and stores them in a temporary storage area.

[1745] 4. Server: The server calls the generative AI module to analyze the uploaded content file. The generative AI module uses image processing algorithms to extract features such as color, shape, and theme, and then tag them appropriately.

[1746] Specific operation: The generation AI module generates tags such as "fantastic" and "landscape."

[1747] Example prompt: Extract file characteristics and generate appropriate tags.

[1748] 4. Server: Stores the extracted feature information and tags in a database so that they can be used for searching and matching.

[1749] Inputting buyer needs and matching

[1750] 1. Device: Buyers access the platform using their own device and enter their desired product requirements and needs in the search bar.

[1751] Example: Buyer B types into his computer, "I want digital art of a fantasy landscape."

[1752] Example prompt: Enter your needs in the product search bar.

[1753] 2. Terminal: When the buyer clicks the search button, their needs information is sent to the server.

[1754] 3. Server: The server passes the received needs information to the generation AI module, which performs optimal matching processing. The generation AI module compares the needs information with the listing information in the database and lists the most suitable listing data.

[1755] 4. Server: The matching results are sent to the buyer's device and displayed on the buyer's screen.

[1756] Example: The server recommends seller A's "fantastic landscape painting" to buyer B's needs.

[1757] Example prompt: List the products that best meet your needs.

[1758] Checkout and payment

[1759] 1. Terminal: The buyer selects the desired product from the displayed matching results and clicks the "Purchase" button, which displays the payment page.

[1760] Example: Buyer B selects a "fantastic landscape painting" and completes the payment procedure using virtual currency.

[1761] Example prompt: Please select a product and proceed with your purchase.

[1762] 2. Terminal: The buyer enters their cryptocurrency wallet information on the payment page and clicks the "Pay" button.

[1763] 3. Server: The server receives the payment information and passes it to the payment module, which debits the cryptocurrency from the buyer's wallet and completes the transaction.

[1764] 4. Payment module: Checks the success of the transaction and sends the result back to the server.

[1765] 5. Server: The server notifies the buyer's terminal that the transaction is complete.

[1766] Payment of rewards to sellers

[1767] 1. Server: Based on the successful transaction information, the server calculates the reward for the seller. The reward is determined based on the number of matches and the transaction amount.

[1768] 2. Payment module: Pays the calculated reward to the seller's wallet in cryptocurrency.

[1769] 3. Server: Updates the seller's dashboard with transaction history and reward information, and notifies the seller that the reward has been paid.

[1770] The above process flow ensures that digital content uploaded by sellers is delivered to buyers efficiently, ensuring smooth transactions. Furthermore, the generative AI module extracts features and tags them to ensure proper matching.

[1771] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1772] Step 1:

[1773] Seller Login

[1774] Input: The username and password entered on the seller's device.

[1775] How it works: The server validates the login information through the authentication module, searching the user database to see if a matching username and password combination exists.

[1776] Output: If authentication is successful, the seller will be shown the dashboard screen. If authentication is unsuccessful, a login error message will be displayed.

[1777] Step 2:

[1778] Uploading content

[1779] Input: Digital content (image files, 3D models, software) and meta information (title, description, price, etc.) uploaded from the seller's device.

[1780] How it works: The server receives the uploaded file and meta information and stores it in a temporary storage area.

[1781] Output: Success message and URL to save the file temporarily on the server.

[1782] Step 3:

[1783] Feature Extraction and Tagging

[1784] Input: Uploaded digital content files and their meta information.

[1785] How it works: The server calls the generative AI module to analyze the file, extracting features such as color, shape, and theme, and automatically generating appropriate tags.

[1786] Output: Feature information and generated tags. For example, tags such as "fantastic" and "landscape."

[1787] Step 4:

[1788] Database storage

[1789] Input: Feature information and tags.

[1790] How it works: The server stores the generated features and tags in a database, making them available for later searching and matching.

[1791] Output: Data stored in a database.

[1792] Step 5:

[1793] Buyer Login

[1794] Input: The username and password entered on the buyer's device.

[1795] How it works: The server validates the login information through the authentication module, searching the user database to see if a matching username and password combination exists.

[1796] Output: If authentication is successful, the buyer will be redirected to the dashboard screen. If authentication is unsuccessful, a login error message will be displayed.

[1797] Step 6:

[1798] Needs input

[1799] Input: The requirements and needs of the desired product entered by the buyer on their device. For example, "I want digital art of a fantasy landscape."

[1800] Behavior: The server temporarily stores the received needs information and prepares it for the next matching process.

[1801] Output: Temporarily saved needs information.

[1802] Step 7:

[1803] Matching process

[1804] Input: Temporarily saved needs information and listing information in the database.

[1805] How it works: The server calls the generation AI module, compares the needs information with the listing data in the database, and makes the best match to list the listing data that best suits the buyer.

[1806] Output: Listed listing data as a result of matching.

[1807] Step 8:

[1808] Matching results displayed

[1809] Input: The result of the match.

[1810] Operation: The server sends the matching results to the buyer's device and displays them on the buyer's screen.

[1811] Output: Matching results displayed on the buyer's device.

[1812] Step 9:

[1813] Product selection and purchase

[1814] Input: Product data and payment information (cryptocurrency wallet information) selected from the buyer's device.

[1815] How it works: After the buyer clicks the "Purchase" button, the server displays the payment page and receives payment information.

[1816] Output: Transaction data and payment information.

[1817] Step 10:

[1818] Payment Processing

[1819] Input: Cryptocurrency wallet information and transaction data provided by the buyer.

[1820] Action: The server uses the payment module to perform a virtual currency debit. If successful, the transaction is completed.

[1821] Output: Confirmation of payment completion and notification of transaction completion.

[1822] Step 11:

[1823] Remuneration calculation

[1824] Input: Successful transaction data.

[1825] How it works: The server calculates the seller's reward based on the transaction data. The reward is determined based on the number of matches and the transaction amount.

[1826] Output: The calculated reward amount.

[1827] Step 12:

[1828] Reward payment

[1829] Input: Calculated reward amount and seller wallet information.

[1830] How it works: The server uses the payment module to pay the reward in cryptocurrency to the seller's wallet. It then verifies that the payment was successful.

[1831] Output: Confirmation of payment completion.

[1832] Step 13:

[1833] Remuneration notification

[1834] Input: Completion information for reward payment.

[1835] What it does: The server updates the seller's dashboard with transaction history and reward information, and notifies them that the reward has been paid.

[1836] Output: Compensation information and transaction history displayed on the seller's dashboard.

[1837] (Application example 1)

[1838] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1839] In digital content trading, there is a demand for technology that allows for efficient and smooth transactions between sellers and buyers. In particular, there are challenges in quickly and accurately providing buyers with content that meets their needs from a vast amount of digital content, and in smoothly paying sellers. There is also a need for a method that allows for easy uploading via smartphone and automatic tag generation.

[1840] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1841] In this invention, the server includes means for uploading generated content to the Internet, means for executing artificial intelligence to extract features of the generated content, means for receiving needs information of buyers, means for executing artificial intelligence to match the generated content with buyers based on the needs information, means for making payments in virtual currency, means for paying a reward to the seller according to the number of matches, means for uploading digital content using a smartphone app, means for executing artificial intelligence to extract features from the uploaded digital content and automatically generate tags, and means for storing the generated tags and feature information in a database. This enables efficient transactions of digital content and improves usability for sellers and buyers.

[1842] "Generated content" is information or data created in digital form.

[1843] The "Internet" is a global communications medium for sending and receiving information over networks.

[1844] "Artificial intelligence for feature extraction" refers to techniques for identifying relevant characteristics from digital content and analyzing that information.

[1845] "Purchaser" means an individual or entity seeking to purchase digital content.

[1846] "Needs Information" refers to the requirements and conditions regarding the specific digital content that a purchaser desires.

[1847] "Artificial intelligence for matching" is a technology that optimally matches buyer needs information with the digital content being offered.

[1848] "Virtual currency" is a currency that is traded in digital form and is used as a means of payment online.

[1849] "Remuneration" refers to the consideration or profit that a seller receives from a transaction.

[1850] A "smartphone app" is a software program that runs on a smartphone.

[1851] A "tag" is a keyword or label added to digital content to make it easier to identify it.

[1852] A "database" is a system for efficiently storing, managing, and making searchable information.

[1853] This invention relates to a system for efficiently trading generated content over the Internet. Specifically, it is a platform where sellers upload digital content using a smartphone app, the features of that content are extracted and tagged using artificial intelligence (generative AI model), and buyers can search for and purchase content based on their needs.

[1854] System configuration and operation overview:

[1855] The system mainly consists of the following components:

[1856] 1. Server: A central device that stores data, processes data, performs artificial intelligence, and handles cryptocurrency payments.

[1857] 2. Seller's device (smartphone): Upload digital content.

[1858] 3. Buyer's device (smartphone, PC, etc.): Enter your needs information and search for and purchase content.

[1859] Seller Content Upload Instructions:

[1860] 1. Seller's device: Sellers use the smartphone app interface to upload digital content (e.g., image files, 3D models, music). To upload, they use the "New Listing" button and enter the required information.

[1861] 2. Server: Receives uploaded files and input information, stores them in storage, and then runs a generative AI model to extract features from the generated content.

[1862] 3. Server: Analyzes the content features using a generative AI model and adds appropriate tags. These features and tags are stored in a database.

[1863] Buyer needs input and matching procedure:

[1864] 1. Buyer's device: Buyers access the platform through a smartphone app or web interface and enter their desired content needs, such as a specific request for "digital art of fantasy landscapes."

[1865] 2. Server: Receives needs information and uses the generative AI model to match it with content in the database.

[1866] 3. Server: The optimal matching results are sent to the buyer's device, and the buyer can select the desired content from the displayed list.

[1867] Checkout and payment:

[1868] 1. Buyer's device: The buyer selects the content they want and clicks the "Purchase" button, which displays the payment page.

[1869] 2. Server: Receives information when a buyer makes a payment using a cryptocurrency wallet, completes the transaction using the payment module, verifies the success of the transaction, and notifies the buyer and seller of the result.

[1870] Seller Payment:

[1871] 1. Server: If the transaction is successful, calculate the seller's reward and pay it in virtual currency using the payment module.

[1872] 2. Server: Updates the transaction history and reward information on the seller's dashboard and notifies the seller that the reward has been paid.

[1873] Hardware and software used:

[1874] Hardware: Servers (e.g., AWS EC2), smartphones (iOS / Android)

[1875] Software: Python and Flask (web framework), TensorFlow / Keras (generative AI model) on the server side, Swift (iOS) or Java / Kotlin (Android) on the smartphone app side

[1876] Examples:

[1877] Seller A uploads a digital piece of art of a "fantastic landscape" using a smartphone app, and the generative AI model automatically generates tags such as "fantastic" and "landscape."

[1878] When Buyer B enters "I want digital art of fantasy landscapes," the AI ​​model recommends content from Seller A and displays it on Buyer B's screen.

[1879] When Buyer B selects a product and pays with virtual currency, Seller A is paid a reward in virtual currency.

[1880] Example prompt sentence:

[1881] "Analyze the visual features of an input digital image and generate appropriate tags based on those features."

[1882] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1883] Step 1:

[1884] Seller's device:

[1885] Sellers select the "New Listing" button on the smartphone app and upload digital content (e.g., image files, 3D models, music), while also entering the required information (title, description, price, etc.).

[1886] Step 2:

[1887] Seller's device:

[1888] When the seller clicks the upload button, the selected file and the entered information are sent to the server. The file information and metadata are packaged and sent as an HTTP request.

[1889] Step 3:

[1890] server:

[1891] The server receives the uploaded file and metadata and stores them in the specified storage. Once the storage is complete, it calls the generative AI model to extract the features of the uploaded file. Specifically, the saved file path is passed as input to the generative AI model, and the resulting feature data is output.

[1892] Step 4:

[1893] server:

[1894] The generative AI model analyzes the visual characteristics of the input file and generates appropriate tags. Specifically, it uses an image processing algorithm to extract features and then generates tags based on those features. In this process, the file path is given as input data and a tag list is obtained as output data.

[1895] Step 5:

[1896] server:

[1897] The extracted feature data and generated tags are stored in a database, which stores file paths, generated tags, file metadata, etc. The stored data is used for later searches and matching.

[1898] Step 6:

[1899] Buyer's device:

[1900] Buyers access the platform through a smartphone app or web interface and enter their desired digital content needs information. The needs information is entered in text format, and when the buyer clicks the search button, the information is sent to the server.

[1901] Step 7:

[1902] server:

[1903] The server receives the buyer's needs information and uses a generative AI model to match it with content in the database. The needs information is passed as input data to the generative AI model, and the optimal matching result is obtained as output data. Specifically, the needs information is analyzed using natural language processing technology and related content in the database is searched for.

[1904] Step 8:

[1905] server:

[1906] The matching results obtained from the generative AI model are sent to the buyer's device and displayed to the buyer. A list of matching results is generated as output data and displayed on the buyer's screen.

[1907] Step 9:

[1908] Buyer's device:

[1909] The buyer selects the desired content from the matching results and clicks the "Purchase" button. This action displays the payment page. The buyer enters their cryptocurrency wallet information and clicks the "Pay" button.

[1910] Step 10:

[1911] server:

[1912] The server receives the buyer's payment information and completes the transaction using the payment module. Specifically, it withdraws the specified cryptocurrency from the buyer's wallet, checks whether the transaction is successful, and then notifies the buyer and seller of the transaction result.

[1913] Step 11:

[1914] server:

[1915] If the transaction is successful, the seller's reward is calculated and paid in virtual currency using the payment module, which is then transferred to the seller's wallet.

[1916] Step 12:

[1917] server:

[1918] The transaction history and reward information will be updated on the seller's dashboard, and a notification will be sent to notify the seller that the reward payment has been completed. Sellers can check their transaction history and reward details by checking their dashboard.

[1919] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1920] The present invention relates to a system for efficiently trading generated content over the Internet, and realizes optimal recommendations through emotion recognition by combining an emotion engine to facilitate smooth trading of digital content between sellers and buyers.

[1921] System Configuration

[1922] The system of the present invention is composed of a server, a seller's terminal, a buyer's terminal, and an emotion engine. The server is a central control device that communicates with multiple terminals via the Internet and performs various processes. The terminals are devices through which users input and output data, and the emotion engine is a system for recognizing and analyzing user emotions in real time.

[1923] Seller-initiated content uploads

[1924] Device: Sellers log in to the platform using their own devices. Enter the required information in the login form and click the "Login" button.

[1925] Device: Sellers click the "New Listing" button on their My Page to go to the screen where they can upload their digital content. Here, they can enter the category and product description and select the digital data file.

[1926] Terminal: When the seller clicks the "Upload" button, the entered information and electronic data file are sent to the server.

[1927] Server: The server stores the received information and electronic data files in storage, then invokes the generative AI module to extract and tag the file features.

[1928] Server: The extracted feature information and tags are saved in a database and registered as listing information.

[1929] Inputting buyer needs and matching

[1930] Device: The buyer visits the platform's search page and enters their needs and desired digital content into the search bar.

[1931] Terminal: When the buyer clicks the "Search" button, the needs information is sent to the server.

[1932] Server: The server passes the received needs information to the generation AI module to search for the best listing information. The generation AI module compares this needs information with the listing information in the database and lists the best-matching listing data.

[1933] Server: The matching results are sent to the buyer's device and displayed on the buyer's screen.

[1934] Checkout and payment

[1935] Terminal: The buyer selects the desired product from the displayed matching results and clicks the "Purchase" button.

[1936] Server: The server receives the buyer's selection and sends the data to display the checkout page.

[1937] Terminal: The buyer enters their cryptocurrency wallet information on the payment page and clicks the "Pay" button.

[1938] Server: The server receives the payment information and passes it to the payment module, which debits the cryptocurrency from the buyer's wallet and completes the transaction.

[1939] Payment module: verifies the success of the transaction and sends the result back to the server, which then notifies the buyer that the purchase is complete.

[1940] Payment of rewards to sellers

[1941] Server: Based on the information of successful transactions, calculates the reward for the seller and determines the reward according to the number of successful matches and the transaction amount.

[1942] Payment module: Pays the calculated reward to the seller's wallet in virtual currency.

[1943] Server: Updates the seller's dashboard with transaction history and reward information, and notifies the seller that the reward has been paid.

[1944] Emotion engine integration

[1945] Emotion engine: Analyzes camera footage and audio data acquired from the user's device in real time to recognize the user's emotional state, such as happiness, sadness, surprise, etc.

[1946] Server: Based on the emotion data received from the emotion engine, the server adjusts the matching algorithm of the generative AI module to make recommendations that are optimal for the user's emotional state.

[1947] On your device: Shows matching listings based on your sentiment.

[1948] Specific examples

[1949] For example, if seller A uploads a digital art piece of "fantastic landscape painting," the generative AI module extracts and tags features such as "fantastic" and "landscape." If buyer B searches for "I want digital art of fantasy landscapes," the generative AI module will recommend seller A's digital art piece as the most suitable product, and if the emotion engine detects buyer B's happy emotions, it will prioritize products that are likely to further increase engagement based on those emotions. When buyer B selects a product and pays with virtual currency, seller A will receive a reward. During this process, seller A's reward may increase as the emotion engine improves the recommendation accuracy.

[1950] The processing flow will be explained below.

[1951] Electronic data upload by seller

[1952] Step 1:

[1953] Sellers log in to the platform using their own devices, enter their login information and click the "Login" button.

[1954] Step 2:

[1955] The seller clicks the "New Listing" button on their My Page, which displays the upload form.

[1956] Step 3:

[1957] Sellers enter the category and product description on the form and upload electronic data files by dragging and dropping or selecting them from the file selection dialog.

[1958] Step 4:

[1959] When the seller clicks the "Upload" button, the entered information and file are sent to the server.

[1960] Step 5:

[1961] The server stores the received information and files in storage, then invokes the generative AI module to extract and tag the file features.

[1962] Step 6:

[1963] The server stores the characteristic information and tags in a database and registers them as listing information.

[1964] Inputting buyer needs and matching

[1965] Step 1:

[1966] Buyers access the platform using their own devices, go to the search page and enter their needs and desired products in the search bar.

[1967] Step 2:

[1968] When the purchaser clicks the "Search" button, the needs information is sent to the server.

[1969] Step 3:

[1970] The server passes the received needs information to the generation AI module, which searches the database for optimal listing information based on the needs information.

[1971] Step 4:

[1972] The generation AI module returns the matching results to the server, which then sends the matching results to the buyer's terminal and displays them.

[1973] Checkout and payment

[1974] Step 1:

[1975] The buyer selects the desired product from the displayed matching results and clicks the "Purchase" button.

[1976] Step 2:

[1977] The server receives the purchaser's selection and sends data to display the checkout page.

[1978] Step 3:

[1979] The buyer enters their cryptocurrency wallet information on the payment page and clicks the "Pay" button.

[1980] Step 4:

[1981] The server receives the payment information and forwards it to the payment module, which debits the specified cryptocurrency from the buyer's wallet to complete the transaction.

[1982] Step 5:

[1983] The payment module verifies the success of the transaction and sends the result back to the server, which notifies the buyer that the purchase has been completed.

[1984] Payment of rewards to sellers

[1985] Step 1:

[1986] The server calculates the seller's reward based on the information of successful transactions. The reward is determined according to the number of successful matches and the transaction amount.

[1987] Step 2:

[1988] The settlement module pays the calculated reward in virtual currency to the seller's wallet.

[1989] Step 3:

[1990] The server updates the transaction history and reward information on the seller's dashboard and notifies the seller that the reward payment has been completed.

[1991] Emotion engine integration

[1992] Step 1:

[1993] The emotion engine analyzes camera footage and audio data acquired from the user's device in real time to recognize the user's emotional state.

[1994] Step 2:

[1995] The emotion engine transmits the recognized emotion data to the server.

[1996] Step 3:

[1997] The server adjusts the matching algorithm of the generation AI module based on the emotional data and makes recommendations that are optimal for the user's emotional state.

[1998] Step 4:

[1999] The server transmits the recommendation results based on the emotional state to the user's terminal and displays them.

[2000] Specific examples

[2001] Step 1:

[2002] Seller A uploads a digital piece of art of a "fantastic landscape painting," and the generative AI module extracts and tags features such as "fantastic" and "landscape."

[2003] Step 2:

[2004] When Buyer B searches for "I want digital art of fantasy landscapes," the generative AI module recommends Seller A's digital art as the most suitable product.

[2005] Step 3:

[2006] The emotion engine detects Buyer B's happy emotions and prioritizes displaying products that are likely to increase engagement based on those emotions.

[2007] Step 4:

[2008] When Buyer B selects a product and pays with virtual currency, Seller A receives a reward.

[2009] Step 5:

[2010] The server utilizes data from the emotion engine to learn and improve the accuracy of the recommendation algorithm.

[2011] Example 2

[2012] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2013] Current digital content trading systems face challenges such as low matching accuracy between sellers and buyers and a lack of personalized user experience. Furthermore, payment methods are limited, making smooth payments using virtual currencies difficult. Therefore, there is a demand for improved matching accuracy that takes user emotions into account, as well as dynamic payment functions using virtual currencies.

[2014] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2015] In this invention, the server includes a means for uploading the generated content to the Internet, a means for executing artificial intelligence to extract features of the generated content, and a means for receiving buyer needs information. This allows the server to recognize the user's emotional state in real time and adjust the matching algorithm, a means for making payments in virtual currency, and a means for paying rewards to sellers according to the number of matches. This improves the accuracy of matching, facilitates transactions between sellers and buyers, and enables smooth payments using virtual currency.

[2016] "Generated content" refers to data or works in digital form that are created using artificial intelligence or other digital technologies.

[2017] "Artificial intelligence" refers to technology that enables computer systems to imitate human intelligence, process and analyze data, and achieve more advanced decision-making and automation through self-learning.

[2018] "Purchaser needs information" refers to information that a user inputs explicitly or implicitly regarding the conditions and requirements for the product or service that the user desires.

[2019] An "emotion engine" refers to algorithms and technologies that recognize and analyze a user's emotional state in real time and adjust the system's behavior based on the results.

[2020] "Virtual currency" refers to a currency that uses cryptography to ensure the security of transactions and allows value to be exchanged digitally without the involvement of a central authority.

[2021] "Matching algorithm" refers to the calculation procedures and logic used to compare the buyer's needs information with the characteristics of the content generated by the seller and find the optimal combination.

[2022] "Reward" refers to the consideration or profit that an exhibitor receives when the content provided by the exhibitor is purchased.

[2023] "Receiving needs information" refers to the system taking in and processing information about the buyer's wishes and requirements.

[2024] The present invention relates to a system for efficiently trading generated content over the Internet. The system of the present invention comprises a server, a seller's terminal, a buyer's terminal, and an emotion engine. The server is a central control device that communicates with multiple terminals via the Internet and performs various processes. The terminals are devices through which users input and output, and the emotion engine is a system for recognizing and analyzing user emotions in real time.

[2025] First, the seller accesses the platform using their own device, enters the required information in the login form, and clicks the "Login" button. The server receives this login information, verifies the user information using the authentication module, and if authentication is successful, the seller is redirected to their personal page.

[2026] Next, when the seller clicks the "New Listing" button on their My Page, they are taken to the listing screen. Here, they enter the category and product description and select the electronic data file to be listed. When the seller clicks the "Upload" button, the entered information and the selected electronic data file are sent to the server. The server saves the received information and electronic data file in storage.

[2027] The server passes the saved electronic data file to a generation AI module, which extracts the file's characteristics. For example, a specific painting's data may be tagged with "fantastic" or "landscape." The extracted characteristic information and tags are stored in a database and registered as listing information. Once registration is complete, a notification of upload completion is displayed on the seller's device.

[2028] Meanwhile, buyers access the platform using their devices and enter keywords for the digital content they desire in the search bar. When the buyer clicks the "Search" button, the entered needs information is sent to the server. The server passes the received needs information to the generation AI module, which searches for the most suitable listing information. The generation AI module compares this information with the listing information in the database and lists the most suitable listing data. The matching results are sent to the buyer's device and displayed on the screen.

[2029] When a buyer selects the desired product and clicks the "Purchase" button, the selection information is sent to the server. The server receives the selected product information and sends data to display the payment page to the buyer. The buyer enters their virtual currency wallet information on the payment page and clicks the "Pay" button. The server receives the payment information and passes it to the payment module. The payment module deducts the virtual currency from the buyer's wallet and completes the transaction. Once the success of the transaction is confirmed, the result is sent back to the server, and the buyer is notified that the purchase procedure has been completed.

[2030] Based on the successful transaction information, the server calculates the reward for the seller and pays the reward in virtual currency to the seller's wallet through the payment module. The server then updates the transaction history and reward information on the seller's dashboard and notifies the seller that the reward payment has been completed.

[2031] The emotion engine analyzes camera footage and audio data acquired from the user's device in real time to recognize the user's emotional state. For example, it identifies the user's emotions such as joy, sadness, and surprise. The server adjusts the matching algorithm of the generation AI module based on the emotion data received from the emotion engine, and makes recommendations that are optimal for the user's emotional state. The adjusted matching results are displayed on the device, allowing the user to receive appropriate recommendations based on their emotions.

[2032] Specific examples

[2033] For example, if seller A uploads a digital art piece of "fantastic landscape painting," the generative AI module extracts and tags features such as "fantastic" and "landscape." If buyer B searches for "I want digital art of fantasy landscapes," the generative AI module will recommend seller A's digital art piece as the most suitable product. If the emotion engine detects buyer B's happy emotions, it will prioritize products that are likely to further increase engagement based on those emotions. When buyer B selects a product and pays with virtual currency, seller A will receive a reward. During this process, seller A's reward may increase as the emotion engine improves the recommendation accuracy.

[2034] Prompt Sentence Examples

[2035] Please explain, step by step, how the digital content of the fantastical landscape painting uploaded by Seller A matches the needs of Buyer B, and how the emotion engine uses Buyer B's emotions to make the optimal recommendation.

[2036] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2037] Step 1: Seller Login

[2038] Input: Username and password provided by the seller's device.

[2039] Server: Receives the submitted login information and passes it to the authentication module to verify the user information.

[2040] Output: If authentication is successful, the seller is redirected to their My Page and the display data of their My Page is sent to the terminal.

[2041] Specific operation: The seller enters the required information into the login form and clicks the "Login" button. The server receives this and verifies it with the user information in the database. Once verification is complete, the seller's personal page is generated and the data is sent to the terminal.

[2042] Step 2: New listing

[2043] Input: Category, product description, and electronic data file provided by the seller's terminal.

[2044] Terminal: When the seller clicks the "New Listing" button, the new listing screen will be displayed.

[2045] Specific operation: The seller enters the category and product description on the new listing screen and selects the electronic data file. When the seller clicks the "Upload" button, this information is sent to the server.

[2046] Step 3: Upload content

[2047] Input: Category, product description, and electronic data file sent from the seller's terminal.

[2048] Server: Stores received information and electronic data files in storage.

[2049] Output: The listing information is saved to storage.

[2050] Specific operation: The server writes and saves the received information and data file in the database storage. Once the saving is complete, it sends a notification to the seller that the upload is complete.

[2051] Step 4: Feature extraction and tagging

[2052] Input: Electronic data files stored in storage.

[2053] Server: Passes stored electronic data files to the generation AI module, which extracts file features.

[2054] Output: The extracted features and tags are stored in a database.

[2055] How it works: The generative AI module analyzes the data file and, for example, if it is a landscape painting, assigns tags such as "fantastic" or "landscape." These feature information and tags are then registered in a database.

[2056] Step 5: Enter your buyer's needs

[2057] Input: Search keywords provided by the buyer's device.

[2058] User (Buyer): The buyer enters the keywords for the desired content in the search bar and clicks the "Search" button.

[2059] Output: The input needs information is sent to the server.

[2060] Specific operation: The purchaser's device sends the entered keywords to the server, which prepares to pass them to the generation AI module.

[2061] Step 6: Submit your needs information

[2062] Input: The search term entered by the buyer.

[2063] Server: Passes the received needs information to the generation AI module.

[2064] Output: Matches that are compared with listings in the database.

[2065] Specific operation: The server provides the buyer's needs information to the generation AI module, which compares it with the listing information in the database and lists the most matching listing data.

[2066] Step 7: Viewing the matching results

[2067] Input: Matching results output from the generative AI module.

[2068] Server: Sends the matching results to the buyer's device.

[2069] Output: Matching results displayed on the buyer's device.

[2070] Specific operation: The buyer's device displays the matching results received from the server, and the buyer can review the results and select the desired product.

[2071] Step 8: Product Selection

[2072] Input: Information about the product selected by the buyer.

[2073] User (Buyer): The buyer selects the product they want and clicks the "Purchase" button.

[2074] Output: Product selection information is sent to the server.

[2075] Specific operation: The purchaser's device sends information about the selected product to the server.

[2076] Step 9: Enter your payment information

[2077] Input: Payment page data provided by the server, cryptocurrency wallet information entered by the buyer.

[2078] Server: Receives the selected product information and sends the payment page data to the buyer.

[2079] Output: The payment page is displayed on the buyer's device.

[2080] Specific operation: The payment page is displayed on the buyer's device, and the buyer enters their wallet information and clicks the "Pay" button, which is then sent to the server.

[2081] Step 10: Payment Processing

[2082] Input: Buyer's payment information.

[2083] Server: Receives payment information and passes it to the payment module.

[2084] Output: The payment is completed and a transaction success message is sent back to the server.

[2085] Specific operation: The payment module debits the virtual currency from the buyer's wallet, confirms whether the transaction is successful, and returns the transaction success information to the server. The server then notifies the buyer that the purchase procedure has been completed.

[2086] Step 11: Compensation calculation and determination

[2087] Input: Information about successful transactions.

[2088] Server: Based on the information of successful transactions, calculates and determines the remuneration to the seller.

[2089] Output: Calculated reward information.

[2090] Specific operation: The server analyzes the transaction information and calculates the seller's reward. The calculated reward information is sent to the payment module in the next step.

[2091] Step 12: Payment

[2092] Input: Calculated reward information.

[2093] Payment module: Pays the calculated reward in cryptocurrency to the seller's wallet.

[2094] Output: Information that the reward payment has been completed is sent back to the server.

[2095] Specific operation: The payment module transfers the reward to the seller's cryptocurrency wallet. This information is sent back to the server, which then notifies the completion of the reward payment.

[2096] Step 13: Update your trading history and rewards

[2097] Input: Information regarding payment completion.

[2098] Server: Updates the seller's dashboard with transaction history and reward information.

[2099] Output: Latest transaction history and reward information displayed on the seller dashboard.

[2100] Specific behavior: The server updates the seller's dashboard data to show the new transaction history and reward information.

[2101] Step 14: Obtaining Emotion Data

[2102] Input: Camera footage and audio data obtained from the buyer's device.

[2103] Emotion engine: Analyzes the user's emotional state in real time from camera footage and audio data.

[2104] Output: Recognized emotion data.

[2105] How it works: The emotion engine analyzes video and audio to identify emotions such as joy, sadness, and surprise, which are then sent to the server in real time.

[2106] Step 15: Analyze the emotion data

[2107] Input: Emotion data sent from the emotion engine.

[2108] Server: Receives emotion data and passes it to the generation AI module.

[2109] Output: A matching algorithm tuned based on emotion data.

[2110] How it works: The server analyzes the emotion data and passes it to the generative AI module, which then recommends products that reflect the user's emotional state.

[2111] Step 16: Adjusting the recommendation algorithm

[2112] Input: Emotion data and user needs information.

[2113] Generative AI module: Adjusts the matching algorithm based on emotion data.

[2114] Output: The adjusted recommendation results.

[2115] What it does: If users are happy, the algorithm adjusts to prioritize products that increase engagement. Adjusted matching results are generated.

[2116] Step 17: Displaying matching results (reflecting emotions)

[2117] Input: Adjusted recommendation results.

[2118] Server: Sends the adjusted matching results to the device.

[2119] Output: The best recommendation results displayed on the buyer's device.

[2120] How it works: The server sends the matching results prioritized based on emotions to the buyer's device, allowing the buyer to select products based on this.

[2121] (Application example 2)

[2122] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2123] Conventional digital content trading systems recommend content without considering the user's emotional state, resulting in low user satisfaction and inefficient trading. Furthermore, it is difficult to recommend appropriate content, making it difficult to provide optimal content that meets the buyer's needs.

[2124] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for uploading generated content to the Internet, means for executing artificial intelligence to extract features of the generated content, means for receiving needs information of purchasers, means for executing artificial intelligence to match the generated content with purchasers based on the needs information, means for making payments in virtual currency, means for detecting the emotional state of purchasers in real time and using an emotion recognition engine to recommend generated content based on that, and means for paying a reward to the seller according to the number of matches. This enables optimal content recommendations based on the user's emotions, thereby improving user satisfaction.

[2125] "Generated content" means information or data created by a user or creator and stored in digital form.

[2126] The "Internet" is a huge communications network that connects computers and networks around the world to each other and allows the exchange of information.

[2127] "Uploading" refers to the act of transferring data stored on a local computer or device to a remote server or online platform.

[2128] "Feature extraction" is the process of extracting specific information or attributes from content, and is often done automatically using artificial intelligence.

[2129] "Artificial intelligence" refers to computer systems and software that can mimic human intellectual activity and perform tasks such as problem solving, learning, and reasoning.

[2130] "Purchaser needs information" is information about the desired product or service entered by a user who wishes to make a purchase.

[2131] "Matching" refers to the act of matching the buyer's wants and needs with the products and services offered.

[2132] "Virtual currency" is a currency that is traded digitally and is often managed using blockchain technology.

[2133] "Settlement" refers to the process of paying for a transaction.

[2134] An "emotion recognition engine" is a system that recognizes a user's emotional state in real time by analyzing their camera footage and audio data.

[2135] "Emotional state" refers to the psychological and sensory state expressed by the user, including joy, sadness, surprise, etc.

[2136] "Recommendation" refers to the act of suggesting suitable products or services to a user.

[2137] "Paying compensation" refers to the act of paying compensation, such as money or virtual currency, for goods or services provided.

[2138] This invention is a system for smoothly trading generated digital content over the Internet, and in particular, by combining it with an emotion recognition engine, it realizes optimal content recommendations based on the user's emotional state.

[2139] The server is implemented as a system including the following means:

[2140] 1. A means of uploading generated content to the Internet

[2141] 2. Means for implementing artificial intelligence to extract features of the generated content.

[2142] 3. Means of receiving information on buyer needs

[2143] 4. A means for executing artificial intelligence to match the generated content with a purchaser based on the needs information.

[2144] 5. Means of making payments with virtual currency

[2145] 6. Using an emotion recognition engine to detect the buyer's emotional state in real time and recommend generated content based on that.

[2146] 7. A means for paying a reward to the seller according to the number of matches

[2147] Specifically, the system operates as follows.

[2148] Seller-initiated content uploads

[2149] Sellers log in to the platform using their own devices and upload their digital content. The uploaded content is then analyzed by an artificial intelligence module on the server, and the information is stored in a database for later use in matching and recommendations.

[2150] Inputting buyer needs and matching

[2151] The purchaser inputs and sends information about the content they need from their own device. The server receives this information, compares it with content in the database using an artificial intelligence module, and generates the best matching results.

[2152] Buyer Emotion Recognition

[2153] The system uses an emotion recognition engine to detect the buyer's emotional state in real time, analyzing the user's emotional state based on information obtained from the camera and microphone, and adjusting the content recommendations accordingly.

[2154] For example, if a purchaser is "smiling after watching a fantasy movie," similar fantasy works will be preferentially recommended based on that emotional state. In this way, providing content that matches the user's emotions can increase user satisfaction.

[2155] Specific examples

[2156] For example, if seller A uploads a digital art piece of "fantastic landscape painting," the generative AI module extracts and tags features such as "fantastic" and "landscape." If buyer B searches for "I want digital art of fantasy landscapes," the generative AI module will recommend sell...

Claims

1. means for uploading the generated content onto the Internet; means for performing artificial intelligence to extract features of the generated content; a means for receiving purchaser needs information; means for executing artificial intelligence to match the generated content with buyers based on the needs information; A means of making payments with virtual currency, The system includes a means for paying a reward to the seller according to the number of matches.

2. 10. The system of claim 1, wherein natural language processing techniques are used to interpret the needs information entered by the purchaser and improve matching accuracy.

3. 10. The system of claim 1, further comprising means for adjusting the generated content to be displayed in a manner adapted to the culture and language of a particular region in a commercial transaction environment.

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