System

Abstract

A system is provided.SOLUTION: A system comprising: a database for storing digital content created by creators; means for receiving requests from users; means for generating customized content using artificial intelligence based on user profile information and past behavioral history; means for generating customized content for an enterprise for a particular theme or target audience; and means for calculating and distributing rewards to creators based on how much the generated content is influenced by the original creator's work.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] Today's creators face challenges such as limited opportunities to widely publicize their excellent digital content and difficulty in generating revenue, which prevents them from concentrating on their creative activities. Meanwhile, users face difficulties finding content that suits their tastes among the vast amount of content available. Furthermore, companies lack the means to quickly generate custom content optimized for their target audiences in order to generate content as an effective marketing tool. This invention aims to solve these challenges and provide new entertainment experiences and efficient marketing methods for creators, users, and corporate advertisers. [Means for solving the problem]

[0005] The present invention provides a system that combines a database for storing digital content created by creators, a means for receiving requests from users, a means for generating customized content using artificial intelligence based on user profile information and past behavioral history, and a means for generating custom content for businesses tailored to specific themes or target audiences. The system also includes a means for calculating and distributing rewards to creators based on the degree to which the generated content was influenced by the original creator's work. The system also includes a means for learning users' browsing history and behavioral patterns and generating new content based on the learning, and a means for providing custom content and playlist sponsorships for businesses and utilizing the generated content as a marketing tool. This system allows creators to continue their creative activities with appropriate rewards, allows users to easily obtain content that suits their preferences, and enables businesses to quickly generate and utilize effective marketing content.

[0006] A "creator" is an individual or group that uses their creativity to produce digital content such as music, art, stories, recipes, and designs.

[0007] "Digital content" means copyrighted material in a form that can be stored and distributed electronically, including music, art, stories, recipes, designs, etc.

[0008] "Database" means an information system for storing, indexing, and facilitating retrieval of creator-generated digital content.

[0009] "User" means an individual or entity that requests and consumes Digital Content.

[0010] A "Request" is an action by a User requesting a particular type or category of Digital Content.

[0011] "Profile Information" is information that includes a user's personal preferences, behavioral patterns, and past selection history.

[0012] "Artificial intelligence (AI)" is a technology that uses specific algorithms to generate customized digital content based on a user's profile information and behavioral history.

[0013] "Customized Content" means digital content tailored to a user's specific needs, generated based on the user's individual profile information and requests.

[0014] "Companies" are legal entities that request custom content tailored to a specific theme or target audience, and often use this content for marketing purposes.

[0015] A "target audience" is a specific group of consumers that a company aims to target with a particular marketing effort.

[0016] "Remuneration" means consideration paid based on specific criteria for the use of a work generated by a creator.

[0017] "Market feedback" refers to evaluation information from consumers and users about the content created, and is data that creators and servers can use to improve the content and calculate rewards. [Brief explanation of the drawings]

[0018] [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

[0019] 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.

[0020] First, the terms used in the following description will be explained.

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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."

[0039] The present invention is a system for storing digital content created by creators and generating customized content for users and companies. A specific embodiment of this system will be described below.

[0040] 1. Creators' submissions and database creation

[0041] The user device provides an interface for creators to post digital content. This interface consists of a screen for uploading files such as music, art, stories, recipes, and designs. When uploading content, creators also enter metadata such as title, description, and tags.

[0042] The server receives the files and metadata uploaded by creators, stores them in a database, properly tags the content, and indexes it for easy discovery by search engines.

[0043] 2. Processing your requests and creating customized works

[0044] The user terminal provides a form for the user to request customized digital content, allowing the user to input their preferences and requirements.

[0045] When the server receives a request, it retrieves the user's profile information and past behavioral history from a database. Based on this information, it uses artificial intelligence (AI) to generate customized content. The generated content is then sent to the user's device, where the user can view or use it.

[0046] 3. Learning based on user preferences and generating new works

[0047] The server periodically collects the user's browsing history and behavioral patterns to learn their preferences. This data is used to update the user's profile. When a new request is received, the server generates more relevant content based on the updated profile information.

[0048] 4. Custom requests and playlist sponsorships for companies

[0049] The terminal provides a dedicated interface for businesses to request custom content tailored to a specific theme or target audience.

[0050] The server receives a company's request, builds a profile of the specified theme and target audience, and uses AI to generate appropriate content and provide it to the company, who can then use the generated content as a marketing tool.

[0051] 5. Calculating rewards and providing market feedback to creators

[0052] The server compares the AI-generated content with the original creator's work and analyzes the degree of influence. Based on this influence, rewards are calculated and distributed to the creator. It also collects market feedback on the generated work in real time and provides it to the creator.

[0053] Specific examples

[0054] 1. Creator submissions:

[0055] Creators upload their music tracks to the platform, and the server stores and tags the tracks and metadata in a database.

[0056] 2. User custom request:

[0057] A user requests music of a specific genre, and the server uses AI to generate a new music track based on the user's profile and past listening history, and sends it to the user's device.

[0058] 3. Custom requests from companies:

[0059] A company requests a music playlist for a Christmas campaign. The server creates a target profile based on the company's request and uses AI to generate and serve music.

[0060] 4. Creator Rewards:

[0061] The AI ​​measures the degree to which the generated track is influenced by the original creator, and the server calculates and distributes rewards to the creator based on that influence.

[0062] In this way, creators can continue their creative activities by receiving appropriate compensation, users can easily obtain content that suits their preferences, and companies can quickly generate and utilize effective marketing content.

[0063] The processing flow will be explained below.

[0064] Creators' submission of works and creation of a database

[0065] Step 1:

[0066] The user device displays an interface for creators to post digital content, who select files such as music, art, stories, recipes, and designs, and enter metadata such as titles, descriptions, and tags.

[0067] Step 2:

[0068] The user clicks the upload button, sending the selected file and the entered metadata to the server.

[0069] Step 3:

[0070] The server receives the uploaded file and metadata, inspects the content, and decides where to store it.

[0071] Step 4:

[0072] The server saves the file to storage and inserts the metadata into a database.

[0073] Step 5:

[0074] The server adds appropriate tags to the uploaded content and indexes it in a database.

[0075] Processing user requests and generating customized works

[0076] Step 1:

[0077] The user terminal displays a form for the user to request customized digital content, and the user enters their preferences and requirements into the form.

[0078] Step 2:

[0079] When a user submits a request form, the contents are sent to the server.

[0080] Step 3:

[0081] The server receives the user's request and retrieves the user's profile information and past behavior history from a database.

[0082] Step 4:

[0083] The server uses artificial intelligence (AI) to generate new customized content based on the profile information and past behavioral history obtained.

[0084] Step 5:

[0085] The server transmits the generated customized content to the user's terminal.

[0086] Learning based on user preferences and generating new works

[0087] Step 1:

[0088] The server periodically collects users' browsing history and behavioral patterns.

[0089] Step 2:

[0090] The server analyzes the user's preferences based on the collected data and updates the profile information.

[0091] Step 3:

[0092] With each new request, the server uses AI to generate more suitable content based on updated profile information.

[0093] Offering custom requests and playlist sponsorships for businesses

[0094] Step 1:

[0095] The user device displays a dedicated interface for businesses, which allows them to request custom content tailored to a specific theme or target audience.

[0096] Step 2:

[0097] When a company submits a request form, the contents are sent to the server.

[0098] Step 3:

[0099] The server receives the business's request and builds a profile of the specified theme and target audience.

[0100] Step 4:

[0101] The server uses AI to generate custom content that meets the company's requirements.

[0102] Step 5:

[0103] The server provides the generated content to the business and accepts feedback.

[0104] Calculating rewards and providing market feedback to creators

[0105] Step 1:

[0106] The server compares the AI-generated content with the original creator's work and calculates the degree of influence.

[0107] Step 2:

[0108] The server calculates the reward for the creator based on the influence.

[0109] Step 3:

[0110] The server distributes the calculated rewards to the creators.

[0111] Step 4:

[0112] The server collects and provides market feedback on the created works to the creators.

[0113] The above is a specific processing flow of the present invention. This specification creates an environment in which creators, users, and companies can easily achieve their respective goals.

[0114] Example 1

[0115] 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."

[0116] There is a need to develop a system that can centrally handle the posting and accumulation of digital content, the generation of customized content, the provision of content to users and businesses, the calculation of compensation for creators, and the provision of market feedback. This system must have the ability to efficiently manage data and provide highly accurate AI-generated content, while also establishing a mechanism for creators to receive appropriate compensation.

[0117] 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.

[0118] In this invention, the server has a database for storing digital content created by creators, and includes: means for receiving requests from users; means for receiving data from user terminals and storing it together with metadata; means for generating customized content using a generative AI model based on the user's profile information and past behavioral history and sending it to the user terminal; means for updating the user profile based on the user's browsing history and behavioral patterns; means for generating custom content for companies tailored to specific themes and target audiences, and means for creating target profiles based on company requests and generating content using AI; means for calculating rewards based on the influence of the generated content on the original creator's work and allocating them to creators; means for providing a dedicated interface for companies and receiving requests; and means for collecting market feedback in real time and providing it to creators. This enables efficient management of digital content and the provision of customized, high-quality AI-generated content.

[0119] "Creator" refers to an individual or entity that creates and submits digital content to the system.

[0120] "Digital content" refers to information assets provided in electronic form, such as music, art, stories, recipes, and designs.

[0121] "Database" means a structured data storage system for managing and storing Creator-contributed Digital Content and associated Metadata.

[0122] "User" means any individual or entity that utilizes the System to request customized digital content.

[0123] "Request" means a request by a User to the System to provide customized digital content.

[0124] "Profile information" refers to information about a user, a collection of data including the user's attributes, preferences, behavioral history, etc.

[0125] "Behavioral history" refers to records of the operations, selections, browsing information, etc. that a user performs within the system.

[0126] "Artificial intelligence (AI)" refers to machine learning and natural language processing technologies used to customize digital content based on user profile information and past behavior.

[0127] "Customized Content" refers to digital content that is generated based on a user's specific requests and preferences.

[0128] "Company" refers to a legal entity that requests the system to generate custom content tailored to a specific theme or target audience.

[0129] "Theme" means the primary subject or topic specified by a Company in a request for custom content generation.

[0130] "Target audience" refers to a specific group of viewers or buyers that a company is targeting.

[0131] "Remuneration" refers to monetary compensation paid to a creator based on the influence of the original creator's work on the generated content.

[0132] "Metadata" refers to additional information such as title, description, and tags that accompany digital content.

[0133] "Generative AI models" refer to algorithms or machine learning models that generate digital content based on user requests, based on collected data and profile information.

[0134] "Market feedback" refers to the reaction and evaluation of the generated content from the market and users.

[0135] "Private Interface" refers to a user interface provided to a business to make specific requests.

[0136] The present invention provides a system for storing digital content created by creators and generating customized content for users and businesses. The following describes in detail an embodiment of this system.

[0137] Creators' submission of works and database creation

[0138] The user device provides an interface for creators to post digital content. This interface consists of a screen for uploading files such as music, art, stories, recipes, and designs. When creators upload content, they can also enter metadata such as title, description, and tags.

[0139] The server receives uploaded files and metadata from creators. The data is stored in a database. The server then properly tags the stored content, allowing it to be indexed by search engines and making it easier for users to find.

[0140] Processing user requests and generating customized works

[0141] The user terminal provides a form for requesting digital content customized for the user, allowing the user to input their preferences and requirements.

[0142] The server receives the user's request. It analyzes the request and retrieves the user's profile information and past behavioral history from a database. Based on the retrieved information, the server uses a generative AI model to generate customized content. The generated content is sent to the user's device, where the user can view or use it.

[0143] Learning based on user preferences and generating new works

[0144] The server periodically collects your browsing history and behavioral patterns, and uses this data to learn your preferences and update your profile.

[0145] When a new request is received, the system generates more relevant content based on the user's latest profile information, leveraging generative AI models to enable highly accurate customization.

[0146] Offering custom requests and playlist sponsorships for businesses

[0147] The device provides a dedicated interface for businesses to request custom content tailored to a specific theme or target audience.

[0148] The server receives requests from businesses, builds profiles based on the specified theme and target audience, and uses generative AI models to generate customized content and provide it to businesses, who can then use the generated content as a marketing tool.

[0149] Calculating rewards and providing market feedback to creators

[0150] The server compares the AI-generated content with the original creator's work and analyzes the degree of influence. Based on this influence, it calculates and distributes rewards to the creator. It also collects market feedback on the generated work in real time and provides that feedback to the creator.

[0151] Specific examples

[0152] 1. Creators upload their own music tracks to the platform.

[0153] The server stores the tracks and metadata in a database and tags them appropriately.

[0154] 2. A user requests music of a particular genre.

[0155] The server uses a generative AI model based on the user profile and past history to generate new music tracks and send them to the user's device.

[0156] 3. A company requests a music playlist for their Christmas campaign.

[0157] The server creates a target profile based on the company's requirements and generates and delivers music using a generative AI model.

[0158] Prompt Sentence Examples

[0159] "Create a pop Christmas song."

[0160] "Generate relaxing background music with elements of classical music"

[0161] As described above, the present invention is a system that realizes efficient management and customized provision of digital content, and also distributes appropriate rewards to creators and provides marketing support to companies.

[0162] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0163] Creators' submission of works and database creation

[0164] Step 1:

[0165] The user device provides an interface for creators to upload digital content, select files such as music, art, or stories, and enter metadata such as titles, descriptions, and tags.

[0166] Input: Digital content file, title, description, tags

[0167] Output: Uploaded digital content and metadata

[0168] Step 2:

[0169] The server receives the digital content and metadata uploaded from the user terminal and stores the received data in a database.

[0170] Input: Digital content and metadata from the user's device

[0171] Output: Digital content and metadata stored in a database

[0172] Step 3:

[0173] The server properly tags the stored digital content and generates an index so that it can be easily found by search engines.

[0174] Input: Digital content and metadata stored in a database

[0175] Output: A tagged index of digital content

[0176] Processing user requests and generating customized works

[0177] Step 1:

[0178] The user terminal provides a request form for the user, and the user inputs his or her preferences and conditions.

[0179] Input: User preferences and conditions

[0180] Output: Request content

[0181] Step 2:

[0182] The server receives the user's request, retrieves the user's profile information and past behavioral history from a database, and uses this information to generate customized content using a generative AI model.

[0183] Input: User requests, profile information, and activity history

[0184] Output: Generated customized content

[0185] Step 3:

[0186] The server transmits the generated customized content to the user terminal, which receives and displays it, and the user views or uses the content.

[0187] Input: Generated customization content

[0188] Output: Content displayed on the user's device

[0189] Learning based on user preferences and generating new works

[0190] Step 1:

[0191] The server periodically collects users' browsing history and behavioral patterns and analyzes the data, thereby learning their preferences.

[0192] Input: User browsing history, behavioral patterns

[0193] Output: Parsed data, updated profile

[0194] Step 2:

[0195] When a new request is received, the server generates content based on the latest profile information and customizes it to match the user's preferences.

[0196] Input: Latest profile information, user requests

[0197] Output: Customized content

[0198] Offering custom requests and playlist sponsorships for businesses

[0199] Step 1:

[0200] The terminal provides a dedicated interface for businesses, allowing them to input requests for custom content tailored to a specific theme or target audience.

[0201] Input: Company theme, target audience criteria

[0202] Output: Request from company

[0203] Step 2:

[0204] The server receives requests from businesses, builds profiles based on specified themes and target audiences, and uses generative AI models to generate and deliver customized content to businesses.

[0205] Input: Company request, theme, target audience criteria

[0206] Output: Corporate customized content

[0207] Calculating rewards and providing market feedback to creators

[0208] Step 1:

[0209] The server compares the AI-generated content with the original creator's work, analyzes the degree of influence, and calculates rewards based on the degree of influence.

[0210] Input: Generated content, the work of the original creator

[0211] Output: Impact analysis results, calculated rewards

[0212] Step 2:

[0213] The server collects market feedback on the created works in real time and provides the feedback to the creators.

[0214] Input: Market Feedback

[0215] Output: Feedback provided to the creator

[0216] Specific examples

[0217] 1. Creators upload their music tracks to the platform, and the server stores the tracks and metadata in a database, tagging them appropriately.

[0218] 2. A user requests music of a specific genre. The server uses a generative AI model based on the user profile and past history to generate a new music track and sends it to the user's device.

[0219] 3. A company requests a music playlist for a Christmas campaign. The server creates a target profile based on the company's requirements and generates and serves music using a generative AI model.

[0220] (Application example 1)

[0221] 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."

[0222] Traditional digital content creation and distribution systems have made it difficult to provide personalized content that perfectly matches users' individual preferences and lack appropriate compensation distribution to creators. In addition, it has been difficult to quickly generate marketing content tailored to target audiences for businesses. This has hindered the improvement of user experience and the provision of flexible services to creators and businesses.

[0223] 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.

[0224] In this invention, the server includes means for providing a database for storing digital content created by creators, means for receiving requests from users, means for generating customized content using a generative artificial intelligence based on the user's profile information and past behavioral history, means for generating custom content for companies tailored to a specific theme or target audience, means for calculating and allocating rewards to creators based on the degree to which the generated content was influenced by the original creator's work, means for recommending new content using a generative artificial intelligence model based on user preferences, and means for logging content usage history. This makes it possible to provide personalized content that meets the preferences of individual users, thereby enabling appropriate reward allocation to creators and the rapid generation of targeted marketing content for companies.

[0225] "Creator" means an individual or entity that creates and provides digital content.

[0226] "Digital content" refers to data in digital form, such as music, video, images, and text.

[0227] A "database" is a system that systematically accumulates and manages digital content and related information created by creators.

[0228] "User" means any individual or entity that uses the System to request, view or use Digital Content.

[0229] A "means for receiving requests" is an interface or system for receiving requests for customized content from users.

[0230] "Profile information" refers to data such as a user's basic information, preferences, and past behavioral history.

[0231] "Past behavior history" is a record of the activities a user has performed within the system.

[0232] "Generative AI" refers to machine learning algorithms and models that generate new content based on input data.

[0233] The "means for generating customized content" is a system that uses the user's profile information and past behavioral history to create content optimized for the user.

[0234] The "means for generating custom content for businesses" is a system that generates content tailored to specific themes based on business requests and target audiences.

[0235] "Influence" is a measure of the degree to which the generated content is based on the work of the original creator.

[0236] "Means for calculating rewards and distributing them to creators" refers to a system that calculates and pays appropriate rewards to creators based on their level of influence.

[0237] "Means for recommending new content using a generative artificial intelligence model" is a system that presents optimal content as candidates based on the user's preferences.

[0238] "Logging means" refers to a system that stores a user's content usage history and uses it for later analysis and recommendations.

[0239] The present invention is a system for storing digital content created by creators and providing customized content to users and businesses. This system is realized using the following hardware and software.

[0240] System configuration

[0241] 1. Server:

[0242] A database for storing digital content

[0243] An interface that receives requests from users

[0244] Profile information and past behavior history management system

[0245] Computing infrastructure for running generative artificial intelligence (AI) models

[0246] 2. Terminal:

[0247] An interface for creators to post content

[0248] An interface for users and businesses to request customized content

[0249] An interface for recommending new content to users

[0250] Data processing and calculation

[0251] Building the database:

[0252] The server stores digital content such as music, videos, images, and text uploaded by creators in a database, along with metadata (title, description, tags, etc.).

[0253] Request Processing and Customization:

[0254] When a user requests customized content through their device, the request data is sent to a server, which uses generative artificial intelligence (AI) to generate new content based on the user's profile information and past behavioral history, and provides it to the user.

[0255] Enterprise Customization:

[0256] When a company requests content for a specific theme or target audience, the server builds a profile based on the company's requirements and uses AI to generate custom content, which is then provided to the company as a marketing tool.

[0257] Recording of content usage history:

[0258] Every time a user interacts with content, the history is recorded as a log on the server, and this historical data is later used as training data for the recommendation algorithm.

[0259] Reward Calculation:

[0260] The AI-generated content is measured to determine the degree of similarity (influence) between it and the original creator's work, and the reward is calculated based on that. The calculated reward is then distributed to the creator.

[0261] Specific examples

[0262] User scenario:

[0263] 1. The user requests "I want to listen to relaxing music" from their device.

[0264] 2. The server retrieves the user's profile information and past behavioral history, and based on this, the AI ​​generates a suitable music track.

[0265] 3. The generated music track is sent to the device where the user listens to it.

[0266] Example prompt sentence:

[0267] "I want to listen to relaxing music. Please generate new music tracks that suit my tastes."

[0268] In this way, users can easily obtain the most suitable content according to their individual preferences, and creators and businesses can also be provided with flexible services.

[0269] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0270] Step 1:

[0271] Creators upload digital content. The device provides an interface for creators to post digital content such as music, videos, images, and text. Creators enter metadata such as title, description, and tags and upload the content. The entered content and metadata are sent to the server. The server receives this data and stores it in a database.

[0272] Step 2:

[0273] The user requests customized content. The user inputs their preferences and conditions using the device's request interface. For example, they input a request such as "I want to listen to relaxing music." This request is then sent to the server.

[0274] Step 3:

[0275] The server retrieves the user's profile information and past behavior history. When the server receives the request, it retrieves the user's profile information and past behavior history from the database. These data are used as input in the next step.

[0276] Step 4:

[0277] The server uses AI to generate customized content. The server uses the acquired user profile information and past behavioral history as input data to input a prompt to the generative AI model. For example, the prompt might be, "I want to listen to relaxing music. Please generate a new music track that suits the user's preferences." The AI ​​model generates new content based on this input and outputs the results to the server.

[0278] Step 5:

[0279] The server provides the generated content to the user. The generated content (e.g., a music track) is sent from the server to the user's device. The user can then view or use the new content on their device.

[0280] Step 6:

[0281] The server logs the content usage history. The history of content that a user has viewed or used is recorded as a log on the server. This history data is used for future content generation and recommendation algorithms.

[0282] Step 7:

[0283] The server calculates the reward for the creator. It measures the influence of the original creator's work on the generated content and calculates the reward based on that influence. The result of this calculation is distributed to the creator as a reward.

[0284] Step 8:

[0285] A business requests custom content tailored to a specific theme or target audience. The business uses its device to send a request for custom content tailored to a theme or target audience to a server. The server builds a profile based on the request and generates relevant content using an AI model. The business uses the generated content as a marketing tool.

[0286] 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.

[0287] The present invention combines an emotion engine with a system for storing digital content created by creators and generating customized content for users and businesses. Specific embodiments of this system are described below.

[0288] 1. Creators' submissions and database creation

[0289] The user device displays an interface for creators to post digital content, selecting files such as music, art, stories, recipes, and designs, and entering metadata such as titles, descriptions, and tags.

[0290] The server receives the files and metadata uploaded by creators, stores them in a database, properly tags the content, and indexes it for easy discovery by search engines.

[0291] 2. Processing your requests and creating customized works

[0292] The user terminal provides a form for the user to request customized digital content, by inputting his / her preferences and requirements.

[0293] When the server receives the request, it retrieves the user's profile information and past behavioral history from a database. Based on this information, it uses artificial intelligence (AI) to generate customized content. The generated content is then sent to the user's device, where the user can view or use it.

[0294] 3. Learning based on user preferences and generating new works

[0295] The server periodically collects a user's browsing history and behavioral patterns to learn their preferences. This data is used to update the user's profile. When a new request is received, the server generates more relevant content based on the updated profile information.

[0296] 4. Custom requests and playlist sponsorships for companies

[0297] The user device displays a dedicated interface for businesses, which allows businesses to request custom content tailored to a specific theme or target audience.

[0298] The server receives a company's request, builds a profile of the specified theme and target audience, and uses AI to generate appropriate content and provide it to the company, who can then use the generated content as a marketing tool.

[0299] 5. Calculating rewards and providing market feedback to creators

[0300] The server compares the AI-generated content with the original creator's work and analyzes the degree of influence. Based on this influence, rewards are calculated and distributed to the creator. It also collects market feedback on the generated work in real time and provides it to the creator.

[0301] 6. User Emotion Recognition and Content Generation

[0302] The user device is equipped with an emotion engine that recognizes the user's emotional state. The emotion engine uses facial recognition technology to analyze the user's emotions and adds the results to the user's profile information. It also analyzes the user's input text and voice to determine the user's emotional state and generates customized content based on that information.

[0303] The server utilizes profile information, including the user's emotional state, to generate content that is more suited to the user's mood and situation. The generated content is customized to the user's real-time emotional state, providing a higher level of satisfaction.

[0304] Specific examples

[0305] 1. Creator submissions:

[0306] Creators upload their music tracks to the platform, and the server stores and tags the tracks and metadata in a database.

[0307] 2. User custom request:

[0308] A user requests music of a specific genre. The server uses AI to generate new music tracks based on the user's profile information and past listening history, and sends them to the user's device. It also takes into account the user's emotional state to provide music that matches their mood.

[0309] 3. User emotion recognition:

[0310] The user device takes a picture of the user's face with a camera and recognizes emotions from facial expressions. For example, if it determines that the user is relaxed, it generates relaxing music to match that.

[0311] 4. Corporate custom requests:

[0312] A company requests a music playlist for a Christmas campaign. The server creates a target profile based on the company's request and uses AI to generate and serve music.

[0313] 5. Creator Rewards:

[0314] The server measures the degree to which the AI-generated track is influenced by the original creator, and calculates and distributes rewards to the creator based on that influence.

[0315] In this way, specific embodiments of the present invention realize a system that allows creators to continue their creative activities with appropriate rewards, users to easily obtain content that suits their preferences and emotional state, and companies to quickly generate and utilize effective marketing content.

[0316] The processing flow will be explained below.

[0317] Creators' submission of works and creation of a database

[0318] Step 1:

[0319] The user device displays an interface for creators to post digital content, who select files such as music, art, stories, recipes, and designs, and enter metadata such as titles, descriptions, and tags.

[0320] Step 2:

[0321] When the user clicks the upload button, the selected file and the entered metadata are sent to the server.

[0322] Step 3:

[0323] The server receives the uploaded file and metadata, inspects the content, and decides where to store it.

[0324] Step 4:

[0325] The server saves the file to storage and inserts the metadata into a database.

[0326] Step 5:

[0327] The server assigns appropriate tags to the uploaded content and indexes it in a database.

[0328] Processing user requests and generating customized works

[0329] Step 1:

[0330] The user terminal provides the user with a form for requesting customized digital content, in which the user inputs their preferences and requirements.

[0331] Step 2:

[0332] When a user submits a request form, the contents are sent to the server.

[0333] Step 3:

[0334] The server receives the user's request and retrieves the user's profile information and past behavioral history from a database.

[0335] Step 4:

[0336] The server uses artificial intelligence (AI) to generate new customized content based on the profile information and past behavioral history obtained.

[0337] Step 5:

[0338] The server transmits the generated customized content to the user's terminal.

[0339] Learning based on user preferences and generating new works

[0340] Step 1:

[0341] The server periodically collects users' browsing history and behavioral patterns.

[0342] Step 2:

[0343] The server analyzes the user's preferences based on the collected data and updates the profile information.

[0344] Step 3:

[0345] With each new request, the server uses AI to generate more appropriate content based on the updated profile information.

[0346] Offering custom requests and playlist sponsorships for businesses

[0347] Step 1:

[0348] The device displays a dedicated interface for businesses, which they can use to request custom content tailored to a specific theme or target audience.

[0349] Step 2:

[0350] When a company submits a request form, the contents are sent to the server.

[0351] Step 3:

[0352] The server receives the business's request and builds a profile of the specified theme and target audience.

[0353] Step 4:

[0354] The server uses AI to generate custom content that meets the company's requirements.

[0355] Step 5:

[0356] The server provides the generated content to the business and accepts feedback.

[0357] Calculating rewards and providing market feedback to creators

[0358] Step 1:

[0359] The server compares the AI-generated content with the original creator's work and calculates the degree of influence.

[0360] Step 2:

[0361] The server calculates the reward for the creator based on the influence.

[0362] Step 3:

[0363] The server distributes the calculated rewards to the creators.

[0364] Step 4:

[0365] The server collects and provides market feedback on the created works to the creators.

[0366] User emotion recognition and content generation

[0367] Step 1:

[0368] The user terminal is equipped with an emotion engine to recognize the user's emotional state, which uses facial recognition technology to analyze the user's emotions and adds the results to the profile information.

[0369] Step 2:

[0370] The user terminal analyzes the user's input text and voice to determine their emotional state and transmits that information to the server.

[0371] Step 3:

[0372] Based on profile information, including emotional state, the server uses AI to generate content that is more suited to the user's mood and situation.

[0373] Step 4:

[0374] The server transmits the generated content to the user's terminal, where the user can use it in real time.

[0375] In this way, a system will be realized in which creators can continue their creative activities by receiving appropriate compensation, users can easily obtain content that matches their preferences and emotional state, and companies can quickly generate and utilize effective marketing content.

[0376] Example 2

[0377] 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."

[0378] Conventional digital content generation systems have difficulty generating customized content based on user profile information and behavioral history. Furthermore, they have not adequately addressed the generation of custom content as a marketing tool for businesses, the appropriate distribution of rewards to creators, or the provision of content tailored to users' emotional states. As a result, many challenges remain in improving user satisfaction, ensuring fairness in creator reward systems, and meeting the targeting accuracy required by businesses.

[0379] 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.

[0380] In this invention, the server has a database for storing digital content created by creators, and includes: means for generating customized content using a generative AI model based on user profile information and past behavioral history; means for generating custom content for companies tailored to a specific theme or target audience; means for calculating and distributing rewards to creators based on the degree to which the generated content was influenced by the original creator's work; and means for recognizing the user's emotional state and generating customized content based thereon. This makes it possible to provide content based on the user's preferences and emotions, achieve fair reward distribution to creators, and generate marketing content for companies with high target accuracy.

[0381] "Creator" refers to an individual or organization that creates digital content and provides it to this system.

[0382] "Digital content" refers to content stored and transmitted in electronic form, such as music, art, stories, recipes, and designs.

[0383] "Database" means a storage system within the system that accumulates and manages creator-provided digital content and associated metadata.

[0384] "User" means an individual or entity that requests and uses customized content through the System.

[0385] "Profile Information" refers to personal information about a user, as well as data such as preferences and behavioral history.

[0386] "Behavioral history" refers to data such as the operations a user performs within the system and their browsing history.

[0387] A "generative AI model" is an algorithm that uses artificial intelligence technology to generate customized content based on a user's profile information and requests.

[0388] "Custom Content" refers to digital content that is customized to meet the needs of a particular user or business.

[0389] "Reward" refers to monetary compensation calculated based on the influence of the generated content on the work of the original creator.

[0390] "Emotional state" is data that indicates a user's current emotions and is collected using facial recognition technology and voice analysis.

[0391] "Interface" refers to the screens and input forms that allow creators, users, and companies to interact with the system.

[0392] "Marketing Tools" refers to digital content that a business uses to advertise and promote to its target audience.

[0393] MODE FOR CARRYING OUT THE INVENTION

[0394] The present invention relates to a system for storing digital content created by creators and generating customized content for users and businesses. The system of the present invention utilizes an emotion engine to recognize the user's emotional state and customize content based on that state, thereby providing a higher level of satisfaction.

[0395] 1. Creator content submissions

[0396] A creator uses a user terminal to upload a digital content file to the system. The user terminal displays a dialog box for file selection and a form for inputting metadata (title, description, tags). When the creator enters this information and performs the upload, the server receives the relevant data and stores it in a database. The file is tagged and an index is generated for easy future search. As a concrete example, a creator uploads a music track they created to the system, and the server stores the track and metadata in a database and tags it.

[0397] 2. Accepting custom user requests

[0398] The user device provides a form for the user to request customized digital content. The user enters information into fields for their preferences and conditions, such as genre and tempo. After entering the conditions and clicking the submit button, the server retrieves the user's profile information and past behavioral history from a database and generates customized content using a generative AI model.

[0399] 3. Customized Content Generation

[0400] The server uses a generative AI model to generate customized content based on the acquired profile information. Specifically, it sends a prompt tailored to the specific user to the generative AI model. For example, it uses the prompt, "Generate the best music for when you want to relax." The generated content is then sent to the user's device, where the user can view or play it.

[0401] 4. Learning user preferences

[0402] The server periodically collects the user's browsing history and behavioral patterns, and updates the profile based on the user's preferences. This data is used to generate more accurate content for future customizations.

[0403] 5. Custom request acceptance for companies

[0404] The user device displays a dedicated interface for businesses, who then request custom content tailored to a specific theme or target audience. The server receives the business's request, builds a profile of the specified theme or target audience, and uses AI to generate appropriate content and provide it to the business.

[0405] 6. Creator Remuneration Calculation

[0406] The server analyzes the degree to which the generated content was influenced by the original creator's work. Based on the degree of influence, the server calculates and distributes rewards to the creator. For example, the server analyzes the degree to which a music track generated by a generative AI model was influenced by the original creator, and calculates monetary rewards based on the results.

[0407] 7. User Emotion Recognition

[0408] The user device uses an emotion engine to recognize the user's face and analyze their voice to determine their emotional state. The server updates the user's profile based on this information and generates content in real time that matches their emotions. Specifically, the server sends a prompt to the AI ​​model, such as "Please generate music that is best suited to when the user is sad," and then provides the generated content.

[0409] In this way, the system generates and delivers high-quality digital content that meets the needs of creators, users, and businesses.

[0410] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0411] The flow of this system's program processing

[0412] Step 1: Creator Content Submission

[0413] Specific actions

[0414] The user terminal displays an interface for creators to post digital content.

[0415] Input: Creator selects a file and enters a title, description, and tags.

[0416] Output: The input files and metadata are generated.

[0417] Data Processing

[0418] The server receives the file and metadata sent from the user terminal.

[0419] Input: Files and metadata from the user's device.

[0420] Output: Save files and metadata to a database.

[0421] What happens: The server creates a new entry in the database, storing the file path and metadata, then runs the tagging algorithm to generate the index.

[0422] Step 2: Accepting a user's custom request

[0423] Specific actions

[0424] The user terminal provides a form for the user to request customized digital content.

[0425] Input: The user inputs preferences and conditions such as genre and tempo.

[0426] Output: Generates the request data.

[0427] Data Processing

[0428] The server receives a request from the user terminal and retrieves the user's profile information and past behavior history from the database.

[0429] Input: User request data, profile information, and past behavior.

[0430] Output: The input data to a generative AI model.

[0431] What it does: The server queries the database for relevant user data and creates a prompt to pass to the generative AI model.

[0432] Step 3: Customized content generation

[0433] Specific actions

[0434] The server sends the prompt sentences to a generative AI model to generate customized content.

[0435] Input: Prompt statement (e.g., "Generate the perfect music for when you want to relax").

[0436] Output: The generated customization content.

[0437] Data Processing

[0438] The server transmits the generated content to the user terminal.

[0439] Input: The generated customization content.

[0440] Output: Data sent to the user's terminal.

[0441] Specific operation: The server receives content from the generative AI model and sends it to the user's device.

[0442] Step 4: Learning user preferences

[0443] Specific actions

[0444] The server periodically collects and learns from users' browsing history and behavioral patterns.

[0445] Input: User operation log data.

[0446] Output: The updated profile data.

[0447] Data Processing

[0448] The server updates the user's profile based on the collected data.

[0449] Input: User operation log.

[0450] Output: The updated profile information.

[0451] Specific operation: The server analyzes the operation log and updates the profile information.

[0452] Step 5: Custom Requests for Businesses

[0453] Specific actions

[0454] The user terminal displays an interface specifically for the enterprise.

[0455] Input: Specific topic and target audience information entered by the company.

[0456] Output: Generates the request data.

[0457] Data Processing

[0458] The server receives the business's request and builds a profile of the target.

[0459] Input: Company request data.

[0460] Output: Prompt statement and custom content.

[0461] How it works: The server creates prompts for the generative AI model based on the company's request and generates custom content.

[0462] Step 6: Creator Reward Calculation

[0463] Specific actions

[0464] The server compares the generated content with the original creator's work.

[0465] Input: Generated content, original creator work.

[0466] Output: Impact score.

[0467] Data Processing

[0468] The server calculates rewards based on the degree of influence and distributes them to creators.

[0469] Input: Impact score.

[0470] Output: Determination and allocation of reward amounts.

[0471] Specific operation: The server calculates the amount based on the influence score and transfers the reward to the creator's account.

[0472] Step 7: Recognizing user emotions

[0473] Specific actions

[0474] The user terminal uses an emotion engine to recognize the user's emotional state.

[0475] Input: User's facial expression data, voice data.

[0476] Output: Emotional state data.

[0477] Data Processing

[0478] The server generates customized content based on the emotional state.

[0479] Input: Emotional state data.

[0480] Output: Customized content.

[0481] Specific operation: The server sends the prompt "Please generate the best music for when the user is sad" to the generative AI model, and then sends the generated content to the user's device.

[0482] In this way, each step in the system has clear inputs and outputs, and through data processing and calculations, it is possible to provide users and businesses with highly customized digital content.

[0483] (Application example 2)

[0484] 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."

[0485] In today's digital content consumption environment, users have diverse needs based on diverse tastes and emotions. For this reason, providing static content is difficult to fully satisfy users. There is also a lack of efficient ways for companies to generate marketing content tailored to their target audiences. Furthermore, there is a need for a system that properly recognizes the extent to which creators' works have influenced users and distributes rewards fairly.

[0486] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0487] In this invention, the server has a database for storing digital content created by creators, and includes a means for receiving requests from users, a means for generating customized content using artificial intelligence based on user profile information and past behavioral history, a means for generating custom content for companies tailored to a specific theme or target audience, a means for calculating and distributing rewards to creators based on the degree to which the generated content was influenced by the original creator's work, a means for generating customized content in real time using facial recognition technology and emotion analysis technology based on the user's emotional state, a means for adapting the generated content to the user's emotional state and providing it in real time, and a means for collecting feedback from users and using it as learning data for the system. This makes it possible to provide content optimized to the preferences and emotions of each user, thereby realizing efficient generation of marketing content for companies and fair distribution of rewards to creators.

[0488] "Creator" means an individual or entity that creates digital content as their own creation and uploads it to the Platform.

[0489] "Digital content" is any creative work stored and distributed in digital form, such as music, art, stories, videos, recipes, or designs.

[0490] A "database" is a collection of information that stores digital content and related metadata created by creators and provides it in response to requests from users and companies.

[0491] "User" means an individual or legal entity that views and uses digital content, makes requests, and receives services.

[0492] "Profile Information" refers to basic data about a user (e.g., age, gender, location) and information obtained from past behavioral history.

[0493] "Artificial intelligence" is a technology that analyzes input data and generates optimal content based on user requests.

[0494] "Customized content" refers to digital content that is optimized for a specific user, generated based on the user's profile information, past behavioral history, and real-time emotional state.

[0495] "Company" refers to a legal entity that uses custom content tailored to a specific theme or target audience as a marketing tool.

[0496] "Theme" refers to the subject or motif that a company or user uses to generate specific content.

[0497] "Target audience" refers to the viewers or users that a particular piece of content is intended for.

[0498] "Facial recognition technology" is a technology for detecting and recognizing human faces using devices such as cameras.

[0499] "Emotion analysis technology" is a technology that analyzes and determines a user's emotions from recognized faces, voices, and text.

[0500] "Feedback" refers to the evaluations and opinions that users give about the content provided, and is information that is used as learning data for the system.

[0501] This invention combines an emotion engine with a system for storing digital content created by creators and generating customized content for users and businesses. Specific embodiments of this system are described below.

[0502] 1. Creators' submissions and database creation

[0503] The server provides an interface for creators to post digital content. Creators enter metadata such as title, description, and tags along with the files they select. The server receives the files and metadata uploaded by creators and stores them in a database. It also tags them appropriately and creates an index for easy discovery by search engines. The software used for this includes a database management system (e.g., MySQL or PostgreSQL) and Python scripts for metadata processing.

[0504] 2. Processing your requests and creating customized works

[0505] The server provides a form for users to request customized digital content. Users use this form to enter their preferences and requirements. When the server receives the request from the user's device, it retrieves the user's profile information and past behavioral history from a database. Based on this information, it uses artificial intelligence (AI) to generate customized content and sends it to the user's device. This is done using machine learning libraries (e.g., TensorFlow and PyTorch).

[0506] 3. Learning based on user preferences and generating new works

[0507] The server periodically collects the user's browsing history and behavioral patterns to learn their preferences. This data is used to update the user's profile. When a new request is received, the server generates content that is more appropriate for the user based on the latest profile information. Data processing is done using large-scale data processing frameworks such as BigQuery and Hadoop.

[0508] 4. Custom requests and playlist sponsorships for companies

[0509] The server provides a dedicated interface for businesses. Businesses use this interface to request custom content tailored to a specific theme or target audience. The server receives the business's request and builds a profile of the specified theme or target audience. It uses AI to generate appropriate content and provides it to the business. It uses digital marketing tools (e.g., Google Analytics or Adobe Analytics) to see how the business uses the generated content as a marketing tool.

[0510] 5. Calculating rewards and providing market feedback to creators

[0511] The server compares the AI-generated content with the original creator's work and analyzes the degree of influence. Based on this degree of influence, rewards are calculated and distributed to the creator. It also collects market feedback on the generated work in real time and provides it to the creator. This is done using a distributed processing system (e.g., Apache Kafka or Flume).

[0512] 6. User Emotion Recognition and Content Generation

[0513] The user device is equipped with an emotion engine to recognize the user's emotional state. This emotion engine uses a camera to capture the user's face in real time and analyzes their emotions. It also analyzes the user's input text and voice to determine their emotional state and generate customized content based on that information. The software used for this includes a facial recognition framework (e.g., OpenCV), an emotion analysis library (e.g., EmotionRecognizer), and a natural language processing model (e.g., BERT).

[0514] For example, if the user has a relaxed expression while playing shuffle, the system will recommend music with a relaxing effect. An example of a prompt sentence is, "If the user's emotion is determined to be relaxed, please recommend music with a relaxing effect. For example, music in the genres 'Ambient' or 'Chillout' is recommended."

[0515] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0516] Step 1:

[0517] Creator submissions

[0518] The server provides an interface for creators to post digital content. Creators enter metadata such as title, description, and tags along with the files they select. The entered data is received by the server and stored in a database. The server tags the metadata and generates an index to make it easily discoverable by search engines.

[0519] Input: Creator-submitted digital content files and metadata

[0520] Output: Digital content and metadata stored in a database

[0521] Step 2:

[0522] Receiving a user request

[0523] The user device provides a form for requesting customized digital content. The user uses this form to input their preferences and requirements. The input request data is sent to the server, which combines it with the user's profile information and past behavior. The user information is retrieved from the database and prepared for processing the request.

[0524] Input: Preferences and conditions entered by the user into the request form

[0525] Output: Request data sent to the server

[0526] Step 3:

[0527] Customized Content Generation

[0528] The server generates customized content using a generative AI model based on the request data. Specifically, it analyzes the request data, the user's profile information, and past behavioral history, and uses machine learning libraries (e.g., TensorFlow and PyTorch) to generate optimal content based on that information. The generated content is then sent to the user's device.

[0529] Input: Request data, profile information, past behavior history

[0530] Output: Customized digital content

[0531] Step 4:

[0532] User emotion recognition

[0533] The user device uses a camera to capture the user's face in real time and analyzes their emotions using an emotion analysis engine (e.g., EmotionRecognizer). The emotion data is added to the user's profile information, which is then used as input data for the AI ​​model.

[0534] Input: Camera image

[0535] Output: User emotion data

[0536] Step 5:

[0537] Real-time content generation and delivery

[0538] The server uses a generative AI model to generate customized content in real time based on the user's profile information, including emotional data. The generated content is then sent to the user's device and provided in real time, allowing the user to instantly receive content that is appropriate for their emotional state.

[0539] Input: User emotion data, profile information

[0540] Output: Real-time customized digital content

[0541] Step 6:

[0542] Gathering user feedback

[0543] The user's device collects feedback from the user regarding the provided content (e.g., like button, comments). This feedback information is sent to the server and used as learning data for the system. This improves the accuracy of the AI ​​model and allows it to generate better customized content.

[0544] Input: User feedback

[0545] Output: Feedback data sent to the server

[0546] 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.

[0547] 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.

[0548] 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.

[0549] [Second embodiment]

[0550] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0551] 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.

[0552] 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).

[0553] 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.

[0554] 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.

[0555] 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).

[0556] 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.

[0557] 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.

[0558] 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.

[0559] 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.

[0560] 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.

[0561] 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."

[0562] The present invention is a system for storing digital content created by creators and generating customized content for users and companies. A specific embodiment of this system will be described below.

[0563] 1. Creators' submissions and database creation

[0564] The user device provides an interface for creators to post digital content. This interface consists of a screen for uploading files such as music, art, stories, recipes, and designs. When uploading content, creators also enter metadata such as title, description, and tags.

[0565] The server receives the files and metadata uploaded by creators, stores them in a database, properly tags the content, and indexes it for easy discovery by search engines.

[0566] 2. Processing your requests and creating customized works

[0567] The user terminal provides a form for the user to request customized digital content, allowing the user to input their preferences and requirements.

[0568] When the server receives a request, it retrieves the user's profile information and past behavioral history from a database. Based on this information, it uses artificial intelligence (AI) to generate customized content. The generated content is then sent to the user's device, where the user can view or use it.

[0569] 3. Learning based on user preferences and generating new works

[0570] The server periodically collects the user's browsing history and behavioral patterns to learn their preferences. This data is used to update the user's profile. When a new request is received, the server generates more relevant content based on the updated profile information.

[0571] 4. Custom requests and playlist sponsorships for companies

[0572] The terminal provides a dedicated interface for businesses to request custom content tailored to a specific theme or target audience.

[0573] The server receives a company's request, builds a profile of the specified theme and target audience, and uses AI to generate appropriate content and provide it to the company, who can then use the generated content as a marketing tool.

[0574] 5. Calculating rewards and providing market feedback to creators

[0575] The server compares the AI-generated content with the original creator's work and analyzes the degree of influence. Based on this influence, rewards are calculated and distributed to the creator. It also collects market feedback on the generated work in real time and provides it to the creator.

[0576] Specific examples

[0577] 1. Creator submissions:

[0578] Creators upload their music tracks to the platform, and the server stores and tags the tracks and metadata in a database.

[0579] 2. User custom request:

[0580] A user requests music of a specific genre, and the server uses AI to generate a new music track based on the user's profile and past listening history, and sends it to the user's device.

[0581] 3. Custom requests from companies:

[0582] A company requests a music playlist for a Christmas campaign. The server creates a target profile based on the company's request and uses AI to generate and serve music.

[0583] 4. Creator Rewards:

[0584] The AI ​​measures the degree to which the generated track is influenced by the original creator, and the server calculates and distributes rewards to the creator based on that influence.

[0585] In this way, creators can continue their creative activities by receiving appropriate compensation, users can easily obtain content that suits their preferences, and companies can quickly generate and utilize effective marketing content.

[0586] The processing flow will be explained below.

[0587] Creators' submission of works and creation of a database

[0588] Step 1:

[0589] The user device displays an interface for creators to post digital content, who select files such as music, art, stories, recipes, and designs, and enter metadata such as titles, descriptions, and tags.

[0590] Step 2:

[0591] The user clicks the upload button, sending the selected file and the entered metadata to the server.

[0592] Step 3:

[0593] The server receives the uploaded file and metadata, inspects the content, and decides where to store it.

[0594] Step 4:

[0595] The server saves the file to storage and inserts the metadata into a database.

[0596] Step 5:

[0597] The server adds appropriate tags to the uploaded content and indexes it in a database.

[0598] Processing user requests and generating customized works

[0599] Step 1:

[0600] The user terminal displays a form for the user to request customized digital content, and the user enters their preferences and requirements into the form.

[0601] Step 2:

[0602] When a user submits a request form, the contents are sent to the server.

[0603] Step 3:

[0604] The server receives the user's request and retrieves the user's profile information and past behavior history from a database.

[0605] Step 4:

[0606] The server uses artificial intelligence (AI) to generate new customized content based on the profile information and past behavioral history obtained.

[0607] Step 5:

[0608] The server transmits the generated customized content to the user's terminal.

[0609] Learning based on user preferences and generating new works

[0610] Step 1:

[0611] The server periodically collects users' browsing history and behavioral patterns.

[0612] Step 2:

[0613] The server analyzes the user's preferences based on the collected data and updates the profile information.

[0614] Step 3:

[0615] With each new request, the server uses AI to generate more suitable content based on updated profile information.

[0616] Offering custom requests and playlist sponsorships for businesses

[0617] Step 1:

[0618] The user device displays a dedicated interface for businesses, which allows them to request custom content tailored to a specific theme or target audience.

[0619] Step 2:

[0620] When a company submits a request form, the contents are sent to the server.

[0621] Step 3:

[0622] The server receives the business's request and builds a profile of the specified theme and target audience.

[0623] Step 4:

[0624] The server uses AI to generate custom content that meets the company's requirements.

[0625] Step 5:

[0626] The server provides the generated content to the business and accepts feedback.

[0627] Calculating rewards and providing market feedback to creators

[0628] Step 1:

[0629] The server compares the AI-generated content with the original creator's work and calculates the degree of influence.

[0630] Step 2:

[0631] The server calculates the reward for the creator based on the influence.

[0632] Step 3:

[0633] The server distributes the calculated rewards to the creators.

[0634] Step 4:

[0635] The server collects and provides market feedback on the created works to the creators.

[0636] The above is a specific processing flow of the present invention. This specification creates an environment in which creators, users, and companies can easily achieve their respective goals.

[0637] Example 1

[0638] 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."

[0639] There is a need to develop a system that can centrally handle the posting and accumulation of digital content, the generation of customized content, the provision of content to users and businesses, the calculation of compensation for creators, and the provision of market feedback. This system must have the ability to efficiently manage data and provide highly accurate AI-generated content, while also establishing a mechanism for creators to receive appropriate compensation.

[0640] 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.

[0641] In this invention, the server has a database for storing digital content created by creators, and includes: means for receiving requests from users; means for receiving data from user terminals and storing it together with metadata; means for generating customized content using a generative AI model based on the user's profile information and past behavioral history and sending it to the user terminal; means for updating the user profile based on the user's browsing history and behavioral patterns; means for generating custom content for companies tailored to specific themes and target audiences, and means for creating target profiles based on company requests and generating content using AI; means for calculating rewards based on the influence of the generated content on the original creator's work and allocating them to creators; means for providing a dedicated interface for companies and receiving requests; and means for collecting market feedback in real time and providing it to creators. This enables efficient management of digital content and the provision of customized, high-quality AI-generated content.

[0642] "Creator" refers to an individual or entity that creates and submits digital content to the system.

[0643] "Digital content" refers to information assets provided in electronic form, such as music, art, stories, recipes, and designs.

[0644] "Database" means a structured data storage system for managing and storing Creator-contributed Digital Content and associated Metadata.

[0645] "User" means any individual or entity that utilizes the System to request customized digital content.

[0646] "Request" means a request by a User to the System to provide customized digital content.

[0647] "Profile information" refers to information about a user, a collection of data including the user's attributes, preferences, behavioral history, etc.

[0648] "Behavioral history" refers to records of the operations, selections, browsing information, etc. that a user performs within the system.

[0649] "Artificial intelligence (AI)" refers to machine learning and natural language processing technologies used to customize digital content based on user profile information and past behavior.

[0650] "Customized Content" refers to digital content that is generated based on a user's specific requests and preferences.

[0651] "Company" refers to a legal entity that requests the system to generate custom content tailored to a specific theme or target audience.

[0652] "Theme" means the primary subject or topic specified by a Company in a request for custom content generation.

[0653] "Target audience" refers to a specific group of viewers or buyers that a company is targeting.

[0654] "Remuneration" refers to monetary compensation paid to a creator based on the influence of the original creator's work on the generated content.

[0655] "Metadata" refers to additional information such as title, description, and tags that accompany digital content.

[0656] "Generative AI models" refer to algorithms or machine learning models that generate digital content based on user requests, based on collected data and profile information.

[0657] "Market feedback" refers to the reaction and evaluation of the generated content from the market and users.

[0658] "Private Interface" refers to a user interface provided to a business to make specific requests.

[0659] The present invention provides a system for storing digital content created by creators and generating customized content for users and businesses. The following describes in detail an embodiment of this system.

[0660] Creators' submission of works and database creation

[0661] The user device provides an interface for creators to post digital content. This interface consists of a screen for uploading files such as music, art, stories, recipes, and designs. When creators upload content, they can also enter metadata such as title, description, and tags.

[0662] The server receives uploaded files and metadata from creators. The data is stored in a database. The server then properly tags the stored content, allowing it to be indexed by search engines and making it easier for users to find.

[0663] Processing user requests and generating customized works

[0664] The user terminal provides a form for requesting digital content customized for the user, allowing the user to input their preferences and requirements.

[0665] The server receives the user's request. It analyzes the request and retrieves the user's profile information and past behavioral history from a database. Based on the retrieved information, the server uses a generative AI model to generate customized content. The generated content is sent to the user's device, where the user can view or use it.

[0666] Learning based on user preferences and generating new works

[0667] The server periodically collects your browsing history and behavioral patterns, and uses this data to learn your preferences and update your profile.

[0668] When a new request is received, the system generates more relevant content based on the user's latest profile information, leveraging generative AI models to enable highly accurate customization.

[0669] Offering custom requests and playlist sponsorships for businesses

[0670] The device provides a dedicated interface for businesses to request custom content tailored to a specific theme or target audience.

[0671] The server receives requests from businesses, builds profiles based on the specified theme and target audience, and uses generative AI models to generate customized content and provide it to businesses, who can then use the generated content as a marketing tool.

[0672] Calculating rewards and providing market feedback to creators

[0673] The server compares the AI-generated content with the original creator's work and analyzes the degree of influence. Based on this influence, it calculates and distributes rewards to the creator. It also collects market feedback on the generated work in real time and provides that feedback to the creator.

[0674] Specific examples

[0675] 1. Creators upload their own music tracks to the platform.

[0676] The server stores the tracks and metadata in a database and tags them appropriately.

[0677] 2. A user requests music of a particular genre.

[0678] The server uses a generative AI model based on the user profile and past history to generate new music tracks and send them to the user's device.

[0679] 3. A company requests a music playlist for their Christmas campaign.

[0680] The server creates a target profile based on the company's requirements and generates and delivers music using a generative AI model.

[0681] Prompt Sentence Examples

[0682] "Create a pop Christmas song."

[0683] "Generate relaxing background music with elements of classical music"

[0684] As described above, the present invention is a system that realizes efficient management and customized provision of digital content, and also distributes appropriate rewards to creators and provides marketing support to companies.

[0685] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0686] Creators' submission of works and database creation

[0687] Step 1:

[0688] The user device provides an interface for creators to upload digital content, select files such as music, art, or stories, and enter metadata such as titles, descriptions, and tags.

[0689] Input: Digital content file, title, description, tags

[0690] Output: Uploaded digital content and metadata

[0691] Step 2:

[0692] The server receives the digital content and metadata uploaded from the user terminal and stores the received data in a database.

[0693] Input: Digital content and metadata from the user's device

[0694] Output: Digital content and metadata stored in a database

[0695] Step 3:

[0696] The server properly tags the stored digital content and generates an index so that it can be easily found by search engines.

[0697] Input: Digital content and metadata stored in a database

[0698] Output: A tagged index of digital content

[0699] Processing user requests and generating customized works

[0700] Step 1:

[0701] The user terminal provides a request form for the user, and the user inputs his or her preferences and conditions.

[0702] Input: User preferences and conditions

[0703] Output: Request content

[0704] Step 2:

[0705] The server receives the user's request, retrieves the user's profile information and past behavioral history from a database, and uses this information to generate customized content using a generative AI model.

[0706] Input: User requests, profile information, and activity history

[0707] Output: Generated customized content

[0708] Step 3:

[0709] The server transmits the generated customized content to the user terminal, which receives and displays it, and the user views or uses the content.

[0710] Input: Generated customization content

[0711] Output: Content displayed on the user's device

[0712] Learning based on user preferences and generating new works

[0713] Step 1:

[0714] The server periodically collects users' browsing history and behavioral patterns and analyzes the data, thereby learning their preferences.

[0715] Input: User browsing history, behavioral patterns

[0716] Output: Parsed data, updated profile

[0717] Step 2:

[0718] When a new request is received, the server generates content based on the latest profile information and customizes it to match the user's preferences.

[0719] Input: Latest profile information, user requests

[0720] Output: Customized content

[0721] Offering custom requests and playlist sponsorships for businesses

[0722] Step 1:

[0723] The terminal provides a dedicated interface for businesses, allowing them to input requests for custom content tailored to a specific theme or target audience.

[0724] Input: Company theme, target audience criteria

[0725] Output: Request from company

[0726] Step 2:

[0727] The server receives requests from businesses, builds profiles based on specified themes and target audiences, and uses generative AI models to generate and deliver customized content to businesses.

[0728] Input: Company request, theme, target audience criteria

[0729] Output: Corporate customized content

[0730] Calculating rewards and providing market feedback to creators

[0731] Step 1:

[0732] The server compares the AI-generated content with the original creator's work, analyzes the degree of influence, and calculates rewards based on the degree of influence.

[0733] Input: Generated content, the work of the original creator

[0734] Output: Impact analysis results, calculated rewards

[0735] Step 2:

[0736] The server collects market feedback on the created works in real time and provides the feedback to the creators.

[0737] Input: Market Feedback

[0738] Output: Feedback provided to the creator

[0739] Specific examples

[0740] 1. Creators upload their music tracks to the platform, and the server stores the tracks and metadata in a database, tagging them appropriately.

[0741] 2. A user requests music of a specific genre. The server uses a generative AI model based on the user profile and past history to generate a new music track and sends it to the user's device.

[0742] 3. A company requests a music playlist for a Christmas campaign. The server creates a target profile based on the company's requirements and generates and serves music using a generative AI model.

[0743] (Application example 1)

[0744] 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."

[0745] Traditional digital content creation and distribution systems have made it difficult to provide personalized content that perfectly matches users' individual preferences and lack appropriate compensation distribution to creators. In addition, it has been difficult to quickly generate marketing content tailored to target audiences for businesses. This has hindered the improvement of user experience and the provision of flexible services to creators and businesses.

[0746] 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.

[0747] In this invention, the server includes means for providing a database for storing digital content created by creators, means for receiving requests from users, means for generating customized content using a generative artificial intelligence based on the user's profile information and past behavioral history, means for generating custom content for companies tailored to a specific theme or target audience, means for calculating and allocating rewards to creators based on the degree to which the generated content was influenced by the original creator's work, means for recommending new content using a generative artificial intelligence model based on user preferences, and means for logging content usage history. This makes it possible to provide personalized content that meets the preferences of individual users, thereby enabling appropriate reward allocation to creators and the rapid generation of targeted marketing content for companies.

[0748] "Creator" means an individual or entity that creates and provides digital content.

[0749] "Digital content" refers to data in digital form, such as music, video, images, and text.

[0750] A "database" is a system that systematically accumulates and manages digital content and related information created by creators.

[0751] "User" means any individual or entity that uses the System to request, view or use Digital Content.

[0752] A "means for receiving requests" is an interface or system for receiving requests for customized content from users.

[0753] "Profile information" refers to data such as a user's basic information, preferences, and past behavioral history.

[0754] "Past behavior history" is a record of the activities a user has performed within the system.

[0755] "Generative AI" refers to machine learning algorithms and models that generate new content based on input data.

[0756] The "means for generating customized content" is a system that uses the user's profile information and past behavioral history to create content optimized for the user.

[0757] The "means for generating custom content for businesses" is a system that generates content tailored to specific themes based on business requests and target audiences.

[0758] "Influence" is a measure of the degree to which the generated content is based on the work of the original creator.

[0759] "Means for calculating rewards and distributing them to creators" refers to a system that calculates and pays appropriate rewards to creators based on their level of influence.

[0760] "Means for recommending new content using a generative artificial intelligence model" is a system that presents optimal content as candidates based on the user's preferences.

[0761] "Logging means" refers to a system that stores a user's content usage history and uses it for later analysis and recommendations.

[0762] The present invention is a system for storing digital content created by creators and providing customized content to users and businesses. This system is realized using the following hardware and software.

[0763] System configuration

[0764] 1. Server:

[0765] A database for storing digital content

[0766] An interface that receives requests from users

[0767] Profile information and past behavior history management system

[0768] Computing infrastructure for running generative artificial intelligence (AI) models

[0769] 2. Terminal:

[0770] An interface for creators to post content

[0771] An interface for users and businesses to request customized content

[0772] An interface for recommending new content to users

[0773] Data processing and calculation

[0774] Building the database:

[0775] The server stores digital content such as music, videos, images, and text uploaded by creators in a database, along with metadata (title, description, tags, etc.).

[0776] Request Processing and Customization:

[0777] When a user requests customized content through their device, the request data is sent to a server, which uses generative artificial intelligence (AI) to generate new content based on the user's profile information and past behavioral history, and provides it to the user.

[0778] Enterprise Customization:

[0779] When a company requests content for a specific theme or target audience, the server builds a profile based on the company's requirements and uses AI to generate custom content, which is then provided to the company as a marketing tool.

[0780] Recording of content usage history:

[0781] Every time a user interacts with content, the history is recorded as a log on the server, and this historical data is later used as training data for the recommendation algorithm.

[0782] Reward Calculation:

[0783] The AI-generated content is measured to determine the degree of similarity (influence) between it and the original creator's work, and the reward is calculated based on that. The calculated reward is then distributed to the creator.

[0784] Specific examples

[0785] User scenario:

[0786] 1. The user requests "I want to listen to relaxing music" from their device.

[0787] 2. The server retrieves the user's profile information and past behavioral history, and based on this, the AI ​​generates a suitable music track.

[0788] 3. The generated music track is sent to the device where the user listens to it.

[0789] Example prompt sentence:

[0790] "I want to listen to relaxing music. Please generate new music tracks that suit my tastes."

[0791] In this way, users can easily obtain the most suitable content according to their individual preferences, and creators and businesses can also be provided with flexible services.

[0792] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0793] Step 1:

[0794] Creators upload digital content. The device provides an interface for creators to post digital content such as music, videos, images, and text. Creators enter metadata such as title, description, and tags and upload the content. The entered content and metadata are sent to the server. The server receives this data and stores it in a database.

[0795] Step 2:

[0796] The user requests customized content. The user inputs their preferences and conditions using the device's request interface. For example, they input a request such as "I want to listen to relaxing music." This request is then sent to the server.

[0797] Step 3:

[0798] The server retrieves the user's profile information and past behavior history. When the server receives the request, it retrieves the user's profile information and past behavior history from the database. These data are used as input in the next step.

[0799] Step 4:

[0800] The server uses AI to generate customized content. The server uses the acquired user profile information and past behavioral history as input data to input a prompt to the generative AI model. For example, the prompt might be, "I want to listen to relaxing music. Please generate a new music track that suits the user's preferences." The AI ​​model generates new content based on this input and outputs the results to the server.

[0801] Step 5:

[0802] The server provides the generated content to the user. The generated content (e.g., a music track) is sent from the server to the user's device. The user can then view or use the new content on their device.

[0803] Step 6:

[0804] The server logs the content usage history. The history of content that a user has viewed or used is recorded as a log on the server. This history data is used for future content generation and recommendation algorithms.

[0805] Step 7:

[0806] The server calculates the reward for the creator. It measures the influence of the original creator's work on the generated content and calculates the reward based on that influence. The result of this calculation is distributed to the creator as a reward.

[0807] Step 8:

[0808] A business requests custom content tailored to a specific theme or target audience. The business uses its device to send a request for custom content tailored to a theme or target audience to a server. The server builds a profile based on the request and generates relevant content using an AI model. The business uses the generated content as a marketing tool.

[0809] 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.

[0810] The present invention combines an emotion engine with a system for storing digital content created by creators and generating customized content for users and businesses. Specific embodiments of this system are described below.

[0811] 1. Creators' submissions and database creation

[0812] The user device displays an interface for creators to post digital content, selecting files such as music, art, stories, recipes, and designs, and entering metadata such as titles, descriptions, and tags.

[0813] The server receives the files and metadata uploaded by creators, stores them in a database, properly tags the content, and indexes it for easy discovery by search engines.

[0814] 2. Processing your requests and creating customized works

[0815] The user terminal provides a form for the user to request customized digital content, by inputting his / her preferences and requirements.

[0816] When the server receives the request, it retrieves the user's profile information and past behavioral history from a database. Based on this information, it uses artificial intelligence (AI) to generate customized content. The generated content is then sent to the user's device, where the user can view or use it.

[0817] 3. Learning based on user preferences and generating new works

[0818] The server periodically collects a user's browsing history and behavioral patterns to learn their preferences. This data is used to update the user's profile. When a new request is received, the server generates more relevant content based on the updated profile information.

[0819] 4. Custom requests and playlist sponsorships for companies

[0820] The user device displays a dedicated interface for businesses, which allows businesses to request custom content tailored to a specific theme or target audience.

[0821] The server receives a company's request, builds a profile of the specified theme and target audience, and uses AI to generate appropriate content and provide it to the company, who can then use the generated content as a marketing tool.

[0822] 5. Calculating rewards and providing market feedback to creators

[0823] The server compares the AI-generated content with the original creator's work and analyzes the degree of influence. Based on this influence, rewards are calculated and distributed to the creator. It also collects market feedback on the generated work in real time and provides it to the creator.

[0824] 6. User Emotion Recognition and Content Generation

[0825] The user device is equipped with an emotion engine that recognizes the user's emotional state. The emotion engine uses facial recognition technology to analyze the user's emotions and adds the results to the user's profile information. It also analyzes the user's input text and voice to determine the user's emotional state and generates customized content based on that information.

[0826] The server utilizes profile information, including the user's emotional state, to generate content that is more suited to the user's mood and situation. The generated content is customized to the user's real-time emotional state, providing a higher level of satisfaction.

[0827] Specific examples

[0828] 1. Creator submissions:

[0829] Creators upload their music tracks to the platform, and the server stores and tags the tracks and metadata in a database.

[0830] 2. User custom request:

[0831] A user requests music of a specific genre. The server uses AI to generate new music tracks based on the user's profile information and past listening history, and sends them to the user's device. It also takes into account the user's emotional state to provide music that matches their mood.

[0832] 3. User emotion recognition:

[0833] The user device takes a picture of the user's face with a camera and recognizes emotions from facial expressions. For example, if it determines that the user is relaxed, it generates relaxing music to match that.

[0834] 4. Corporate custom requests:

[0835] A company requests a music playlist for a Christmas campaign. The server creates a target profile based on the company's request and uses AI to generate and serve music.

[0836] 5. Creator Rewards:

[0837] The server measures the degree to which the AI-generated track is influenced by the original creator, and calculates and distributes rewards to the creator based on that influence.

[0838] In this way, specific embodiments of the present invention realize a system that allows creators to continue their creative activities with appropriate rewards, users to easily obtain content that suits their preferences and emotional state, and companies to quickly generate and utilize effective marketing content.

[0839] The processing flow will be explained below.

[0840] Creators' submission of works and creation of a database

[0841] Step 1:

[0842] The user device displays an interface for creators to post digital content, who select files such as music, art, stories, recipes, and designs, and enter metadata such as titles, descriptions, and tags.

[0843] Step 2:

[0844] When the user clicks the upload button, the selected file and the entered metadata are sent to the server.

[0845] Step 3:

[0846] The server receives the uploaded file and metadata, inspects the content, and decides where to store it.

[0847] Step 4:

[0848] The server saves the file to storage and inserts the metadata into a database.

[0849] Step 5:

[0850] The server assigns appropriate tags to the uploaded content and indexes it in a database.

[0851] Processing user requests and generating customized works

[0852] Step 1:

[0853] The user terminal provides the user with a form for requesting customized digital content, in which the user inputs their preferences and requirements.

[0854] Step 2:

[0855] When a user submits a request form, the contents are sent to the server.

[0856] Step 3:

[0857] The server receives the user's request and retrieves the user's profile information and past behavioral history from a database.

[0858] Step 4:

[0859] The server uses artificial intelligence (AI) to generate new customized content based on the profile information and past behavioral history obtained.

[0860] Step 5:

[0861] The server transmits the generated customized content to the user's terminal.

[0862] Learning based on user preferences and generating new works

[0863] Step 1:

[0864] The server periodically collects users' browsing history and behavioral patterns.

[0865] Step 2:

[0866] The server analyzes the user's preferences based on the collected data and updates the profile information.

[0867] Step 3:

[0868] With each new request, the server uses AI to generate more appropriate content based on the updated profile information.

[0869] Offering custom requests and playlist sponsorships for businesses

[0870] Step 1:

[0871] The device displays a dedicated interface for businesses, which they can use to request custom content tailored to a specific theme or target audience.

[0872] Step 2:

[0873] When a company submits a request form, the contents are sent to the server.

[0874] Step 3:

[0875] The server receives the business's request and builds a profile of the specified theme and target audience.

[0876] Step 4:

[0877] The server uses AI to generate custom content that meets the company's requirements.

[0878] Step 5:

[0879] The server provides the generated content to the business and accepts feedback.

[0880] Calculating rewards and providing market feedback to creators

[0881] Step 1:

[0882] The server compares the AI-generated content with the original creator's work and calculates the degree of influence.

[0883] Step 2:

[0884] The server calculates the reward for the creator based on the influence.

[0885] Step 3:

[0886] The server distributes the calculated rewards to the creators.

[0887] Step 4:

[0888] The server collects and provides market feedback on the created works to the creators.

[0889] User emotion recognition and content generation

[0890] Step 1:

[0891] The user terminal is equipped with an emotion engine to recognize the user's emotional state, which uses facial recognition technology to analyze the user's emotions and adds the results to the profile information.

[0892] Step 2:

[0893] The user terminal analyzes the user's input text and voice to determine their emotional state and transmits that information to the server.

[0894] Step 3:

[0895] Based on profile information, including emotional state, the server uses AI to generate content that is more suited to the user's mood and situation.

[0896] Step 4:

[0897] The server transmits the generated content to the user's terminal, where the user can use it in real time.

[0898] In this way, a system will be realized in which creators can continue their creative activities by receiving appropriate compensation, users can easily obtain content that matches their preferences and emotional state, and companies can quickly generate and utilize effective marketing content.

[0899] Example 2

[0900] 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."

[0901] Conventional digital content generation systems have difficulty generating customized content based on user profile information and behavioral history. Furthermore, they have not adequately addressed the generation of custom content as a marketing tool for businesses, the appropriate distribution of rewards to creators, or the provision of content tailored to users' emotional states. As a result, many challenges remain in improving user satisfaction, ensuring fairness in creator reward systems, and meeting the targeting accuracy required by businesses.

[0902] 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.

[0903] In this invention, the server has a database for storing digital content created by creators, and includes: means for generating customized content using a generative AI model based on user profile information and past behavioral history; means for generating custom content for companies tailored to a specific theme or target audience; means for calculating and distributing rewards to creators based on the degree to which the generated content was influenced by the original creator's work; and means for recognizing the user's emotional state and generating customized content based thereon. This makes it possible to provide content based on the user's preferences and emotions, achieve fair reward distribution to creators, and generate marketing content for companies with high target accuracy.

[0904] "Creator" refers to an individual or organization that creates digital content and provides it to this system.

[0905] "Digital content" refers to content stored and transmitted in electronic form, such as music, art, stories, recipes, and designs.

[0906] "Database" means a storage system within the system that accumulates and manages creator-provided digital content and associated metadata.

[0907] "User" means an individual or entity that requests and uses customized content through the System.

[0908] "Profile Information" refers to personal information about a user, as well as data such as preferences and behavioral history.

[0909] "Behavioral history" refers to data such as the operations a user performs within the system and their browsing history.

[0910] A "generative AI model" is an algorithm that uses artificial intelligence technology to generate customized content based on a user's profile information and requests.

[0911] "Custom Content" refers to digital content that is customized to meet the needs of a particular user or business.

[0912] "Reward" refers to monetary compensation calculated based on the influence of the generated content on the work of the original creator.

[0913] "Emotional state" is data that indicates a user's current emotions and is collected using facial recognition technology and voice analysis.

[0914] "Interface" refers to the screens and input forms that allow creators, users, and companies to interact with the system.

[0915] "Marketing Tools" refers to digital content that a business uses to advertise and promote to its target audience.

[0916] MODE FOR CARRYING OUT THE INVENTION

[0917] The present invention relates to a system for storing digital content created by creators and generating customized content for users and businesses. The system of the present invention utilizes an emotion engine to recognize the user's emotional state and customize content based on that state, thereby providing a higher level of satisfaction.

[0918] 1. Creator content submissions

[0919] A creator uses a user terminal to upload a digital content file to the system. The user terminal displays a dialog box for file selection and a form for inputting metadata (title, description, tags). When the creator enters this information and performs the upload, the server receives the relevant data and stores it in a database. The file is tagged and an index is generated for easy future search. As a concrete example, a creator uploads a music track they created to the system, and the server stores the track and metadata in a database and tags it.

[0920] 2. Accepting custom user requests

[0921] The user device provides a form for the user to request customized digital content. The user enters information into fields for their preferences and conditions, such as genre and tempo. After entering the conditions and clicking the submit button, the server retrieves the user's profile information and past behavioral history from a database and generates customized content using a generative AI model.

[0922] 3. Customized Content Generation

[0923] The server uses a generative AI model to generate customized content based on the acquired profile information. Specifically, it sends a prompt tailored to the specific user to the generative AI model. For example, it uses the prompt, "Generate the best music for when you want to relax." The generated content is then sent to the user's device, where the user can view or play it.

[0924] 4. Learning user preferences

[0925] The server periodically collects the user's browsing history and behavioral patterns, and updates the profile based on the user's preferences. This data is used to generate more accurate content for future customizations.

[0926] 5. Custom request acceptance for companies

[0927] The user device displays a dedicated interface for businesses, who then request custom content tailored to a specific theme or target audience. The server receives the business's request, builds a profile of the specified theme or target audience, and uses AI to generate appropriate content and provide it to the business.

[0928] 6. Creator Remuneration Calculation

[0929] The server analyzes the degree to which the generated content was influenced by the original creator's work. Based on the degree of influence, the server calculates and distributes rewards to the creator. For example, the server analyzes the degree to which a music track generated by a generative AI model was influenced by the original creator, and calculates monetary rewards based on the results.

[0930] 7. User Emotion Recognition

[0931] The user device uses an emotion engine to recognize the user's face and analyze their voice to determine their emotional state. The server updates the user's profile based on this information and generates content in real time that matches their emotions. Specifically, the server sends a prompt to the AI ​​model, such as "Please generate music that is best suited to when the user is sad," and then provides the generated content.

[0932] In this way, the system generates and delivers high-quality digital content that meets the needs of creators, users, and businesses.

[0933] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0934] The flow of this system's program processing

[0935] Step 1: Creator Content Submission

[0936] Specific actions

[0937] The user terminal displays an interface for creators to post digital content.

[0938] Input: Creator selects a file and enters a title, description, and tags.

[0939] Output: The input files and metadata are generated.

[0940] Data Processing

[0941] The server receives the file and metadata sent from the user terminal.

[0942] Input: Files and metadata from the user's device.

[0943] Output: Save files and metadata to a database.

[0944] What happens: The server creates a new entry in the database, storing the file path and metadata, then runs the tagging algorithm to generate the index.

[0945] Step 2: Accepting a user's custom request

[0946] Specific actions

[0947] The user terminal provides a form for the user to request customized digital content.

[0948] Input: The user inputs preferences and conditions such as genre and tempo.

[0949] Output: Generates the request data.

[0950] Data Processing

[0951] The server receives a request from the user terminal and retrieves the user's profile information and past behavior history from the database.

[0952] Input: User request data, profile information, and past behavior.

[0953] Output: The input data to a generative AI model.

[0954] What it does: The server queries the database for relevant user data and creates a prompt to pass to the generative AI model.

[0955] Step 3: Customized content generation

[0956] Specific actions

[0957] The server sends the prompt sentences to a generative AI model to generate customized content.

[0958] Input: Prompt statement (e.g., "Generate the perfect music for when you want to relax").

[0959] Output: The generated customization content.

[0960] Data Processing

[0961] The server transmits the generated content to the user terminal.

[0962] Input: The generated customization content.

[0963] Output: Data sent to the user's terminal.

[0964] Specific operation: The server receives content from the generative AI model and sends it to the user's device.

[0965] Step 4: Learning user preferences

[0966] Specific actions

[0967] The server periodically collects and learns from users' browsing history and behavioral patterns.

[0968] Input: User operation log data.

[0969] Output: The updated profile data.

[0970] Data Processing

[0971] The server updates the user's profile based on the collected data.

[0972] Input: User operation log.

[0973] Output: The updated profile information.

[0974] Specific operation: The server analyzes the operation log and updates the profile information.

[0975] Step 5: Custom Requests for Businesses

[0976] Specific actions

[0977] The user terminal displays an interface specifically for the enterprise.

[0978] Input: Specific topic and target audience information entered by the company.

[0979] Output: Generates the request data.

[0980] Data Processing

[0981] The server receives the business's request and builds a profile of the target.

[0982] Input: Company request data.

[0983] Output: Prompt statement and custom content.

[0984] How it works: The server creates prompts for the generative AI model based on the company's request and generates custom content.

[0985] Step 6: Creator Reward Calculation

[0986] Specific actions

[0987] The server compares the generated content with the original creator's work.

[0988] Input: Generated content, original creator work.

[0989] Output: Impact score.

[0990] Data Processing

[0991] The server calculates rewards based on the degree of influence and distributes them to creators.

[0992] Input: Impact score.

[0993] Output: Determination and allocation of reward amounts.

[0994] Specific operation: The server calculates the amount based on the influence score and transfers the reward to the creator's account.

[0995] Step 7: Recognizing user emotions

[0996] Specific actions

[0997] The user terminal uses an emotion engine to recognize the user's emotional state.

[0998] Input: User's facial expression data, voice data.

[0999] Output: Emotional state data.

[1000] Data Processing

[1001] The server generates customized content based on the emotional state.

[1002] Input: Emotional state data.

[1003] Output: Customized content.

[1004] Specific operation: The server sends the prompt "Please generate the best music for when the user is sad" to the generative AI model, and then sends the generated content to the user's device.

[1005] In this way, each step in the system has clear inputs and outputs, and through data processing and calculations, it is possible to provide users and businesses with highly customized digital content.

[1006] (Application example 2)

[1007] 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."

[1008] In today's digital content consumption environment, users have diverse needs based on diverse tastes and emotions. For this reason, providing static content is difficult to fully satisfy users. There is also a lack of efficient ways for companies to generate marketing content tailored to their target audiences. Furthermore, there is a need for a system that properly recognizes the extent to which creators' works have influenced users and distributes rewards fairly.

[1009] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1010] In this invention, the server has a database for storing digital content created by creators, and includes a means for receiving requests from users, a means for generating customized content using artificial intelligence based on user profile information and past behavioral history, a means for generating custom content for companies tailored to a specific theme or target audience, a means for calculating and distributing rewards to creators based on the degree to which the generated content was influenced by the original creator's work, a means for generating customized content in real time using facial recognition technology and emotion analysis technology based on the user's emotional state, a means for adapting the generated content to the user's emotional state and providing it in real time, and a means for collecting feedback from users and using it as learning data for the system. This makes it possible to provide content optimized to the preferences and emotions of each user, thereby realizing efficient generation of marketing content for companies and fair distribution of rewards to creators.

[1011] "Creator" means an individual or entity that creates digital content as their own creation and uploads it to the Platform.

[1012] "Digital content" is any creative work stored and distributed in digital form, such as music, art, stories, videos, recipes, or designs.

[1013] A "database" is a collection of information that stores digital content and related metadata created by creators and provides it in response to requests from users and companies.

[1014] "User" means an individual or legal entity that views and uses digital content, makes requests, and receives services.

[1015] "Profile Information" refers to basic data about a user (e.g., age, gender, location) and information obtained from past behavioral history.

[1016] "Artificial intelligence" is a technology that analyzes input data and generates optimal content based on user requests.

[1017] "Customized content" refers to digital content that is optimized for a specific user, generated based on the user's profile information, past behavioral history, and real-time emotional state.

[1018] "Company" refers to a legal entity that uses custom content tailored to a specific theme or target audience as a marketing tool.

[1019] "Theme" refers to the subject or motif that a company or user uses to generate specific content.

[1020] "Target audience" refers to the viewers or users that a particular piece of content is intended for.

[1021] "Facial recognition technology" is a technology for detecting and recognizing human faces using devices such as cameras.

[1022] "Emotion analysis technology" is a technology that analyzes and determines a user's emotions from recognized faces, voices, and text.

[1023] "Feedback" refers to the evaluations and opinions that users give about the content provided, and is information that is used as learning data for the system.

[1024] This invention combines an emotion engine with a system for storing digital content created by creators and generating customized content for users and businesses. Specific embodiments of this system are described below.

[1025] 1. Creators' submissions and database creation

[1026] The server provides an interface for creators to post digital content. Creators enter metadata such as title, description, and tags along with the files they select. The server receives the files and metadata uploaded by creators and stores them in a database. It also tags them appropriately and creates an index for easy discovery by search engines. The software used for this includes a database management system (e.g., MySQL or PostgreSQL) and Python scripts for metadata processing.

[1027] 2. Processing your requests and creating customized works

[1028] The server provides a form for users to request customized digital content. Users use this form to enter their preferences and requirements. When the server receives the request from the user's device, it retrieves the user's profile information and past behavioral history from a database. Based on this information, it uses artificial intelligence (AI) to generate customized content and sends it to the user's device. This is done using machine learning libraries (e.g., TensorFlow and PyTorch).

[1029] 3. Learning based on user preferences and generating new works

[1030] The server periodically collects the user's browsing history and behavioral patterns to learn their preferences. This data is used to update the user's profile. When a new request is received, the server generates content that is more appropriate for the user based on the latest profile information. Data processing is done using large-scale data processing frameworks such as BigQuery and Hadoop.

[1031] 4. Custom requests and playlist sponsorships for companies

[1032] The server provides a dedicated interface for businesses. Businesses use this interface to request custom content tailored to a specific theme or target audience. The server receives the business's request and builds a profile of the specified theme or target audience. It uses AI to generate appropriate content and provides it to the business. It uses digital marketing tools (e.g., Google Analytics or Adobe Analytics) to see how the business uses the generated content as a marketing tool.

[1033] 5. Calculating rewards and providing market feedback to creators

[1034] The server compares the AI-generated content with the original creator's work and analyzes the degree of influence. Based on this degree of influence, rewards are calculated and distributed to the creator. It also collects market feedback on the generated work in real time and provides it to the creator. This is done using a distributed processing system (e.g., Apache Kafka or Flume).

[1035] 6. User Emotion Recognition and Content Generation

[1036] The user device is equipped with an emotion engine to recognize the user's emotional state. This emotion engine uses a camera to capture the user's face in real time and analyzes their emotions. It also analyzes the user's input text and voice to determine their emotional state and generate customized content based on that information. The software used for this includes a facial recognition framework (e.g., OpenCV), an emotion analysis library (e.g., EmotionRecognizer), and a natural language processing model (e.g., BERT).

[1037] For example, if the user has a relaxed expression while playing shuffle, the system will recommend music with a relaxing effect. An example of a prompt sentence is, "If the user's emotion is determined to be relaxed, please recommend music with a relaxing effect. For example, music in the genres 'Ambient' or 'Chillout' is recommended."

[1038] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1039] Step 1:

[1040] Creator submissions

[1041] The server provides an interface for creators to post digital content. Creators enter metadata such as title, description, and tags along with the files they select. The entered data is received by the server and stored in a database. The server tags the metadata and generates an index to make it easily discoverable by search engines.

[1042] Input: Creator-submitted digital content files and metadata

[1043] Output: Digital content and metadata stored in a database

[1044] Step 2:

[1045] Receiving a user request

[1046] The user device provides a form for requesting customized digital content. The user uses this form to input their preferences and requirements. The input request data is sent to the server, which combines it with the user's profile information and past behavior. The user information is retrieved from the database and prepared for processing the request.

[1047] Input: Preferences and conditions entered by the user into the request form

[1048] Output: Request data sent to the server

[1049] Step 3:

[1050] Customized Content Generation

[1051] The server generates customized content using a generative AI model based on the request data. Specifically, it analyzes the request data, the user's profile information, and past behavioral history, and uses machine learning libraries (e.g., TensorFlow and PyTorch) to generate optimal content based on that information. The generated content is then sent to the user's device.

[1052] Input: Request data, profile information, past behavior history

[1053] Output: Customized digital content

[1054] Step 4:

[1055] User emotion recognition

[1056] The user device uses a camera to capture the user's face in real time and analyzes their emotions using an emotion analysis engine (e.g., EmotionRecognizer). The emotion data is added to the user's profile information, which is then used as input data for the AI ​​model.

[1057] Input: Camera image

[1058] Output: User emotion data

[1059] Step 5:

[1060] Real-time content generation and delivery

[1061] The server uses a generative AI model to generate customized content in real time based on the user's profile information, including emotional data. The generated content is then sent to the user's device and provided in real time, allowing the user to instantly receive content that is appropriate for their emotional state.

[1062] Input: User emotion data, profile information

[1063] Output: Real-time customized digital content

[1064] Step 6:

[1065] Gathering user feedback

[1066] The user's device collects feedback from the user regarding the provided content (e.g., like button, comments). This feedback information is sent to the server and used as learning data for the system. This improves the accuracy of the AI ​​model and allows it to generate better customized content.

[1067] Input: User feedback

[1068] Output: Feedback data sent to the server

[1069] 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.

[1070] 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.

[1071] 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.

[1072] [Third embodiment]

[1073] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1074] 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.

[1075] 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).

[1076] 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.

[1077] 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.

[1078] 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).

[1079] 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.

[1080] 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.

[1081] 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.

[1082] 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.

[1083] 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.

[1084] 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."

[1085] The present invention is a system for storing digital content created by creators and generating customized content for users and companies. A specific embodiment of this system will be described below.

[1086] 1. Creators' submissions and database creation

[1087] The user device provides an interface for creators to post digital content. This interface consists of a screen for uploading files such as music, art, stories, recipes, and designs. When uploading content, creators also enter metadata such as title, description, and tags.

[1088] The server receives the files and metadata uploaded by creators, stores them in a database, properly tags the content, and indexes it for easy discovery by search engines.

[1089] 2. Processing your requests and creating customized works

[1090] The user terminal provides a form for the user to request customized digital content, allowing the user to input their preferences and requirements.

[1091] When the server receives a request, it retrieves the user's profile information and past behavioral history from a database. Based on this information, it uses artificial intelligence (AI) to generate customized content. The generated content is then sent to the user's device, where the user can view or use it.

[1092] 3. Learning based on user preferences and generating new works

[1093] The server periodically collects the user's browsing history and behavioral patterns to learn their preferences. This data is used to update the user's profile. When a new request is received, the server generates more relevant content based on the updated profile information.

[1094] 4. Custom requests and playlist sponsorships for companies

[1095] The terminal provides a dedicated interface for businesses to request custom content tailored to a specific theme or target audience.

[1096] The server receives a company's request, builds a profile of the specified theme and target audience, and uses AI to generate appropriate content and provide it to the company, who can then use the generated content as a marketing tool.

[1097] 5. Calculating rewards and providing market feedback to creators

[1098] The server compares the AI-generated content with the original creator's work and analyzes the degree of influence. Based on this influence, rewards are calculated and distributed to the creator. It also collects market feedback on the generated work in real time and provides it to the creator.

[1099] Specific examples

[1100] 1. Creator submissions:

[1101] Creators upload their music tracks to the platform, and the server stores and tags the tracks and metadata in a database.

[1102] 2. User custom request:

[1103] A user requests music of a specific genre, and the server uses AI to generate a new music track based on the user's profile and past listening history, and sends it to the user's device.

[1104] 3. Custom requests from companies:

[1105] A company requests a music playlist for a Christmas campaign. The server creates a target profile based on the company's request and uses AI to generate and serve music.

[1106] 4. Creator Rewards:

[1107] The AI ​​measures the degree to which the generated track is influenced by the original creator, and the server calculates and distributes rewards to the creator based on that influence.

[1108] In this way, creators can continue their creative activities by receiving appropriate compensation, users can easily obtain content that suits their preferences, and companies can quickly generate and utilize effective marketing content.

[1109] The processing flow will be explained below.

[1110] Creators' submission of works and creation of a database

[1111] Step 1:

[1112] The user device displays an interface for creators to post digital content, who select files such as music, art, stories, recipes, and designs, and enter metadata such as titles, descriptions, and tags.

[1113] Step 2:

[1114] The user clicks the upload button, sending the selected file and the entered metadata to the server.

[1115] Step 3:

[1116] The server receives the uploaded file and metadata, inspects the content, and decides where to store it.

[1117] Step 4:

[1118] The server saves the file to storage and inserts the metadata into a database.

[1119] Step 5:

[1120] The server adds appropriate tags to the uploaded content and indexes it in a database.

[1121] Processing user requests and generating customized works

[1122] Step 1:

[1123] The user terminal displays a form for the user to request customized digital content, and the user enters their preferences and requirements into the form.

[1124] Step 2:

[1125] When a user submits a request form, the contents are sent to the server.

[1126] Step 3:

[1127] The server receives the user's request and retrieves the user's profile information and past behavior history from a database.

[1128] Step 4:

[1129] The server uses artificial intelligence (AI) to generate new customized content based on the profile information and past behavioral history obtained.

[1130] Step 5:

[1131] The server transmits the generated customized content to the user's terminal.

[1132] Learning based on user preferences and generating new works

[1133] Step 1:

[1134] The server periodically collects users' browsing history and behavioral patterns.

[1135] Step 2:

[1136] The server analyzes the user's preferences based on the collected data and updates the profile information.

[1137] Step 3:

[1138] With each new request, the server uses AI to generate more suitable content based on updated profile information.

[1139] Offering custom requests and playlist sponsorships for businesses

[1140] Step 1:

[1141] The user device displays a dedicated interface for businesses, which allows them to request custom content tailored to a specific theme or target audience.

[1142] Step 2:

[1143] When a company submits a request form, the contents are sent to the server.

[1144] Step 3:

[1145] The server receives the business's request and builds a profile of the specified theme and target audience.

[1146] Step 4:

[1147] The server uses AI to generate custom content that meets the company's requirements.

[1148] Step 5:

[1149] The server provides the generated content to the business and accepts feedback.

[1150] Calculating rewards and providing market feedback to creators

[1151] Step 1:

[1152] The server compares the AI-generated content with the original creator's work and calculates the degree of influence.

[1153] Step 2:

[1154] The server calculates the reward for the creator based on the influence.

[1155] Step 3:

[1156] The server distributes the calculated rewards to the creators.

[1157] Step 4:

[1158] The server collects and provides market feedback on the created works to the creators.

[1159] The above is a specific processing flow of the present invention. This specification creates an environment in which creators, users, and companies can easily achieve their respective goals.

[1160] Example 1

[1161] 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."

[1162] There is a need to develop a system that can centrally handle the posting and accumulation of digital content, the generation of customized content, the provision of content to users and businesses, the calculation of compensation for creators, and the provision of market feedback. This system must have the ability to efficiently manage data and provide highly accurate AI-generated content, while also establishing a mechanism for creators to receive appropriate compensation.

[1163] 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.

[1164] In this invention, the server has a database for storing digital content created by creators, and includes: means for receiving requests from users; means for receiving data from user terminals and storing it together with metadata; means for generating customized content using a generative AI model based on the user's profile information and past behavioral history and sending it to the user terminal; means for updating the user profile based on the user's browsing history and behavioral patterns; means for generating custom content for companies tailored to specific themes and target audiences, and means for creating target profiles based on company requests and generating content using AI; means for calculating rewards based on the influence of the generated content on the original creator's work and allocating them to creators; means for providing a dedicated interface for companies and receiving requests; and means for collecting market feedback in real time and providing it to creators. This enables efficient management of digital content and the provision of customized, high-quality AI-generated content.

[1165] "Creator" refers to an individual or entity that creates and submits digital content to the system.

[1166] "Digital content" refers to information assets provided in electronic form, such as music, art, stories, recipes, and designs.

[1167] "Database" means a structured data storage system for managing and storing Creator-contributed Digital Content and associated Metadata.

[1168] "User" means any individual or entity that utilizes the System to request customized digital content.

[1169] "Request" means a request by a User to the System to provide customized digital content.

[1170] "Profile information" refers to information about a user, a collection of data including the user's attributes, preferences, behavioral history, etc.

[1171] "Behavioral history" refers to records of the operations, selections, browsing information, etc. that a user performs within the system.

[1172] "Artificial intelligence (AI)" refers to machine learning and natural language processing technologies used to customize digital content based on user profile information and past behavior.

[1173] "Customized Content" refers to digital content that is generated based on a user's specific requests and preferences.

[1174] "Company" refers to a legal entity that requests the system to generate custom content tailored to a specific theme or target audience.

[1175] "Theme" means the primary subject or topic specified by a Company in a request for custom content generation.

[1176] "Target audience" refers to a specific group of viewers or buyers that a company is targeting.

[1177] "Remuneration" refers to monetary compensation paid to a creator based on the influence of the original creator's work on the generated content.

[1178] "Metadata" refers to additional information such as title, description, and tags that accompany digital content.

[1179] "Generative AI models" refer to algorithms or machine learning models that generate digital content based on user requests, based on collected data and profile information.

[1180] "Market feedback" refers to the reaction and evaluation of the generated content from the market and users.

[1181] "Private Interface" refers to a user interface provided to a business to make specific requests.

[1182] The present invention provides a system for storing digital content created by creators and generating customized content for users and businesses. The following describes in detail an embodiment of this system.

[1183] Creators' submission of works and database creation

[1184] The user device provides an interface for creators to post digital content. This interface consists of a screen for uploading files such as music, art, stories, recipes, and designs. When creators upload content, they can also enter metadata such as title, description, and tags.

[1185] The server receives uploaded files and metadata from creators. The data is stored in a database. The server then properly tags the stored content, allowing it to be indexed by search engines and making it easier for users to find.

[1186] Processing user requests and generating customized works

[1187] The user terminal provides a form for requesting digital content customized for the user, allowing the user to input their preferences and requirements.

[1188] The server receives the user's request. It analyzes the request and retrieves the user's profile information and past behavioral history from a database. Based on the retrieved information, the server uses a generative AI model to generate customized content. The generated content is sent to the user's device, where the user can view or use it.

[1189] Learning based on user preferences and generating new works

[1190] The server periodically collects your browsing history and behavioral patterns, and uses this data to learn your preferences and update your profile.

[1191] When a new request is received, the system generates more relevant content based on the user's latest profile information, leveraging generative AI models to enable highly accurate customization.

[1192] Offering custom requests and playlist sponsorships for businesses

[1193] The device provides a dedicated interface for businesses to request custom content tailored to a specific theme or target audience.

[1194] The server receives requests from businesses, builds profiles based on the specified theme and target audience, and uses generative AI models to generate customized content and provide it to businesses, who can then use the generated content as a marketing tool.

[1195] Calculating rewards and providing market feedback to creators

[1196] The server compares the AI-generated content with the original creator's work and analyzes the degree of influence. Based on this influence, it calculates and distributes rewards to the creator. It also collects market feedback on the generated work in real time and provides that feedback to the creator.

[1197] Specific examples

[1198] 1. Creators upload their own music tracks to the platform.

[1199] The server stores the tracks and metadata in a database and tags them appropriately.

[1200] 2. A user requests music of a particular genre.

[1201] The server uses a generative AI model based on the user profile and past history to generate new music tracks and send them to the user's device.

[1202] 3. A company requests a music playlist for their Christmas campaign.

[1203] The server creates a target profile based on the company's requirements and generates and delivers music using a generative AI model.

[1204] Prompt Sentence Examples

[1205] "Create a pop Christmas song."

[1206] "Generate relaxing background music with elements of classical music"

[1207] As described above, the present invention is a system that realizes efficient management and customized provision of digital content, and also distributes appropriate rewards to creators and provides marketing support to companies.

[1208] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1209] Creators' submission of works and database creation

[1210] Step 1:

[1211] The user device provides an interface for creators to upload digital content, select files such as music, art, or stories, and enter metadata such as titles, descriptions, and tags.

[1212] Input: Digital content file, title, description, tags

[1213] Output: Uploaded digital content and metadata

[1214] Step 2:

[1215] The server receives the digital content and metadata uploaded from the user terminal and stores the received data in a database.

[1216] Input: Digital content and metadata from the user's device

[1217] Output: Digital content and metadata stored in a database

[1218] Step 3:

[1219] The server properly tags the stored digital content and generates an index so that it can be easily found by search engines.

[1220] Input: Digital content and metadata stored in a database

[1221] Output: A tagged index of digital content

[1222] Processing user requests and generating customized works

[1223] Step 1:

[1224] The user terminal provides a request form for the user, and the user inputs his or her preferences and conditions.

[1225] Input: User preferences and conditions

[1226] Output: Request content

[1227] Step 2:

[1228] The server receives the user's request, retrieves the user's profile information and past behavioral history from a database, and uses this information to generate customized content using a generative AI model.

[1229] Input: User requests, profile information, and activity history

[1230] Output: Generated customized content

[1231] Step 3:

[1232] The server transmits the generated customized content to the user terminal, which receives and displays it, and the user views or uses the content.

[1233] Input: Generated customization content

[1234] Output: Content displayed on the user's device

[1235] Learning based on user preferences and generating new works

[1236] Step 1:

[1237] The server periodically collects users' browsing history and behavioral patterns and analyzes the data, thereby learning their preferences.

[1238] Input: User browsing history, behavioral patterns

[1239] Output: Parsed data, updated profile

[1240] Step 2:

[1241] When a new request is received, the server generates content based on the latest profile information and customizes it to match the user's preferences.

[1242] Input: Latest profile information, user requests

[1243] Output: Customized content

[1244] Offering custom requests and playlist sponsorships for businesses

[1245] Step 1:

[1246] The terminal provides a dedicated interface for businesses, allowing them to input requests for custom content tailored to a specific theme or target audience.

[1247] Input: Company theme, target audience criteria

[1248] Output: Request from company

[1249] Step 2:

[1250] The server receives requests from businesses, builds profiles based on specified themes and target audiences, and uses generative AI models to generate and deliver customized content to businesses.

[1251] Input: Company request, theme, target audience criteria

[1252] Output: Corporate customized content

[1253] Calculating rewards and providing market feedback to creators

[1254] Step 1:

[1255] The server compares the AI-generated content with the original creator's work, analyzes the degree of influence, and calculates rewards based on the degree of influence.

[1256] Input: Generated content, the work of the original creator

[1257] Output: Impact analysis results, calculated rewards

[1258] Step 2:

[1259] The server collects market feedback on the created works in real time and provides the feedback to the creators.

[1260] Input: Market Feedback

[1261] Output: Feedback provided to the creator

[1262] Specific examples

[1263] 1. Creators upload their music tracks to the platform, and the server stores the tracks and metadata in a database, tagging them appropriately.

[1264] 2. A user requests music of a specific genre. The server uses a generative AI model based on the user profile and past history to generate a new music track and sends it to the user's device.

[1265] 3. A company requests a music playlist for a Christmas campaign. The server creates a target profile based on the company's requirements and generates and serves music using a generative AI model.

[1266] (Application example 1)

[1267] 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."

[1268] Traditional digital content creation and distribution systems have made it difficult to provide personalized content that perfectly matches users' individual preferences and lack appropriate compensation distribution to creators. In addition, it has been difficult to quickly generate marketing content tailored to target audiences for businesses. This has hindered the improvement of user experience and the provision of flexible services to creators and businesses.

[1269] 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.

[1270] In this invention, the server includes means for providing a database for storing digital content created by creators, means for receiving requests from users, means for generating customized content using a generative artificial intelligence based on the user's profile information and past behavioral history, means for generating custom content for companies tailored to a specific theme or target audience, means for calculating and allocating rewards to creators based on the degree to which the generated content was influenced by the original creator's work, means for recommending new content using a generative artificial intelligence model based on user preferences, and means for logging content usage history. This makes it possible to provide personalized content that meets the preferences of individual users, thereby enabling appropriate reward allocation to creators and the rapid generation of targeted marketing content for companies.

[1271] "Creator" means an individual or entity that creates and provides digital content.

[1272] "Digital content" refers to data in digital form, such as music, video, images, and text.

[1273] A "database" is a system that systematically accumulates and manages digital content and related information created by creators.

[1274] "User" means any individual or entity that uses the System to request, view or use Digital Content.

[1275] A "means for receiving requests" is an interface or system for receiving requests for customized content from users.

[1276] "Profile information" refers to data such as a user's basic information, preferences, and past behavioral history.

[1277] "Past behavior history" is a record of the activities a user has performed within the system.

[1278] "Generative AI" refers to machine learning algorithms and models that generate new content based on input data.

[1279] The "means for generating customized content" is a system that uses the user's profile information and past behavioral history to create content optimized for the user.

[1280] The "means for generating custom content for businesses" is a system that generates content tailored to specific themes based on business requests and target audiences.

[1281] "Influence" is a measure of the degree to which the generated content is based on the work of the original creator.

[1282] "Means for calculating rewards and distributing them to creators" refers to a system that calculates and pays appropriate rewards to creators based on their level of influence.

[1283] "Means for recommending new content using a generative artificial intelligence model" is a system that presents optimal content as candidates based on the user's preferences.

[1284] "Logging means" refers to a system that stores a user's content usage history and uses it for later analysis and recommendations.

[1285] The present invention is a system for storing digital content created by creators and providing customized content to users and businesses. This system is realized using the following hardware and software.

[1286] System configuration

[1287] 1. Server:

[1288] A database for storing digital content

[1289] An interface that receives requests from users

[1290] Profile information and past behavior history management system

[1291] Computing infrastructure for running generative artificial intelligence (AI) models

[1292] 2. Terminal:

[1293] An interface for creators to post content

[1294] An interface for users and businesses to request customized content

[1295] An interface for recommending new content to users

[1296] Data processing and calculation

[1297] Building the database:

[1298] The server stores digital content such as music, videos, images, and text uploaded by creators in a database, along with metadata (title, description, tags, etc.).

[1299] Request Processing and Customization:

[1300] When a user requests customized content through their device, the request data is sent to a server, which uses generative artificial intelligence (AI) to generate new content based on the user's profile information and past behavioral history, and provides it to the user.

[1301] Enterprise Customization:

[1302] When a company requests content for a specific theme or target audience, the server builds a profile based on the company's requirements and uses AI to generate custom content, which is then provided to the company as a marketing tool.

[1303] Recording of content usage history:

[1304] Every time a user interacts with content, the history is recorded as a log on the server, and this historical data is later used as training data for the recommendation algorithm.

[1305] Reward Calculation:

[1306] The AI-generated content is measured to determine the degree of similarity (influence) between it and the original creator's work, and the reward is calculated based on that. The calculated reward is then distributed to the creator.

[1307] Specific examples

[1308] User scenario:

[1309] 1. The user requests "I want to listen to relaxing music" from their device.

[1310] 2. The server retrieves the user's profile information and past behavioral history, and based on this, the AI ​​generates a suitable music track.

[1311] 3. The generated music track is sent to the device where the user listens to it.

[1312] Example prompt sentence:

[1313] "I want to listen to relaxing music. Please generate new music tracks that suit my tastes."

[1314] In this way, users can easily obtain the most suitable content according to their individual preferences, and creators and businesses can also be provided with flexible services.

[1315] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1316] Step 1:

[1317] Creators upload digital content. The device provides an interface for creators to post digital content such as music, videos, images, and text. Creators enter metadata such as title, description, and tags and upload the content. The entered content and metadata are sent to the server. The server receives this data and stores it in a database.

[1318] Step 2:

[1319] The user requests customized content. The user inputs their preferences and conditions using the device's request interface. For example, they input a request such as "I want to listen to relaxing music." This request is then sent to the server.

[1320] Step 3:

[1321] The server retrieves the user's profile information and past behavior history. When the server receives the request, it retrieves the user's profile information and past behavior history from the database. These data are used as input in the next step.

[1322] Step 4:

[1323] The server uses AI to generate customized content. The server uses the acquired user profile information and past behavioral history as input data to input a prompt to the generative AI model. For example, the prompt might be, "I want to listen to relaxing music. Please generate a new music track that suits the user's preferences." The AI ​​model generates new content based on this input and outputs the results to the server.

[1324] Step 5:

[1325] The server provides the generated content to the user. The generated content (e.g., a music track) is sent from the server to the user's device. The user can then view or use the new content on their device.

[1326] Step 6:

[1327] The server logs the content usage history. The history of content that a user has viewed or used is recorded as a log on the server. This history data is used for future content generation and recommendation algorithms.

[1328] Step 7:

[1329] The server calculates the reward for the creator. It measures the influence of the original creator's work on the generated content and calculates the reward based on that influence. The result of this calculation is distributed to the creator as a reward.

[1330] Step 8:

[1331] A business requests custom content tailored to a specific theme or target audience. The business uses its device to send a request for custom content tailored to a theme or target audience to a server. The server builds a profile based on the request and generates relevant content using an AI model. The business uses the generated content as a marketing tool.

[1332] 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.

[1333] The present invention combines an emotion engine with a system for storing digital content created by creators and generating customized content for users and businesses. Specific embodiments of this system are described below.

[1334] 1. Creators' submissions and database creation

[1335] The user device displays an interface for creators to post digital content, selecting files such as music, art, stories, recipes, and designs, and entering metadata such as titles, descriptions, and tags.

[1336] The server receives the files and metadata uploaded by creators, stores them in a database, properly tags the content, and indexes it for easy discovery by search engines.

[1337] 2. Processing your requests and creating customized works

[1338] The user terminal provides a form for the user to request customized digital content, by inputting his / her preferences and requirements.

[1339] When the server receives the request, it retrieves the user's profile information and past behavioral history from a database. Based on this information, it uses artificial intelligence (AI) to generate customized content. The generated content is then sent to the user's device, where the user can view or use it.

[1340] 3. Learning based on user preferences and generating new works

[1341] The server periodically collects a user's browsing history and behavioral patterns to learn their preferences. This data is used to update the user's profile. When a new request is received, the server generates more relevant content based on the updated profile information.

[1342] 4. Custom requests and playlist sponsorships for companies

[1343] The user device displays a dedicated interface for businesses, which allows businesses to request custom content tailored to a specific theme or target audience.

[1344] The server receives a company's request, builds a profile of the specified theme and target audience, and uses AI to generate appropriate content and provide it to the company, who can then use the generated content as a marketing tool.

[1345] 5. Calculating rewards and providing market feedback to creators

[1346] The server compares the AI-generated content with the original creator's work and analyzes the degree of influence. Based on this influence, rewards are calculated and distributed to the creator. It also collects market feedback on the generated work in real time and provides it to the creator.

[1347] 6. User Emotion Recognition and Content Generation

[1348] The user device is equipped with an emotion engine that recognizes the user's emotional state. The emotion engine uses facial recognition technology to analyze the user's emotions and adds the results to the user's profile information. It also analyzes the user's input text and voice to determine the user's emotional state and generates customized content based on that information.

[1349] The server utilizes profile information, including the user's emotional state, to generate content that is more suited to the user's mood and situation. The generated content is customized to the user's real-time emotional state, providing a higher level of satisfaction.

[1350] Specific examples

[1351] 1. Creator submissions:

[1352] Creators upload their music tracks to the platform, and the server stores and tags the tracks and metadata in a database.

[1353] 2. User custom request:

[1354] A user requests music of a specific genre. The server uses AI to generate new music tracks based on the user's profile information and past listening history, and sends them to the user's device. It also takes into account the user's emotional state to provide music that matches their mood.

[1355] 3. User emotion recognition:

[1356] The user device takes a picture of the user's face with a camera and recognizes emotions from facial expressions. For example, if it determines that the user is relaxed, it generates relaxing music to match that.

[1357] 4. Corporate custom requests:

[1358] A company requests a music playlist for a Christmas campaign. The server creates a target profile based on the company's request and uses AI to generate and serve music.

[1359] 5. Creator Rewards:

[1360] The server measures the degree to which the AI-generated track is influenced by the original creator, and calculates and distributes rewards to the creator based on that influence.

[1361] In this way, specific embodiments of the present invention realize a system that allows creators to continue their creative activities with appropriate rewards, users to easily obtain content that suits their preferences and emotional state, and companies to quickly generate and utilize effective marketing content.

[1362] The processing flow will be explained below.

[1363] Creators' submission of works and creation of a database

[1364] Step 1:

[1365] The user device displays an interface for creators to post digital content, who select files such as music, art, stories, recipes, and designs, and enter metadata such as titles, descriptions, and tags.

[1366] Step 2:

[1367] When the user clicks the upload button, the selected file and the entered metadata are sent to the server.

[1368] Step 3:

[1369] The server receives the uploaded file and metadata, inspects the content, and decides where to store it.

[1370] Step 4:

[1371] The server saves the file to storage and inserts the metadata into a database.

[1372] Step 5:

[1373] The server assigns appropriate tags to the uploaded content and indexes it in a database.

[1374] Processing user requests and generating customized works

[1375] Step 1:

[1376] The user terminal provides the user with a form for requesting customized digital content, in which the user inputs their preferences and requirements.

[1377] Step 2:

[1378] When a user submits a request form, the contents are sent to the server.

[1379] Step 3:

[1380] The server receives the user's request and retrieves the user's profile information and past behavioral history from a database.

[1381] Step 4:

[1382] The server uses artificial intelligence (AI) to generate new customized content based on the profile information and past behavioral history obtained.

[1383] Step 5:

[1384] The server transmits the generated customized content to the user's terminal.

[1385] Learning based on user preferences and generating new works

[1386] Step 1:

[1387] The server periodically collects users' browsing history and behavioral patterns.

[1388] Step 2:

[1389] The server analyzes the user's preferences based on the collected data and updates the profile information.

[1390] Step 3:

[1391] With each new request, the server uses AI to generate more appropriate content based on the updated profile information.

[1392] Offering custom requests and playlist sponsorships for businesses

[1393] Step 1:

[1394] The device displays a dedicated interface for businesses, which they can use to request custom content tailored to a specific theme or target audience.

[1395] Step 2:

[1396] When a company submits a request form, the contents are sent to the server.

[1397] Step 3:

[1398] The server receives the business's request and builds a profile of the specified theme and target audience.

[1399] Step 4:

[1400] The server uses AI to generate custom content that meets the company's requirements.

[1401] Step 5:

[1402] The server provides the generated content to the business and accepts feedback.

[1403] Calculating rewards and providing market feedback to creators

[1404] Step 1:

[1405] The server compares the AI-generated content with the original creator's work and calculates the degree of influence.

[1406] Step 2:

[1407] The server calculates the reward for the creator based on the influence.

[1408] Step 3:

[1409] The server distributes the calculated rewards to the creators.

[1410] Step 4:

[1411] The server collects and provides market feedback on the created works to the creators.

[1412] User emotion recognition and content generation

[1413] Step 1:

[1414] The user terminal is equipped with an emotion engine to recognize the user's emotional state, which uses facial recognition technology to analyze the user's emotions and adds the results to the profile information.

[1415] Step 2:

[1416] The user terminal analyzes the user's input text and voice to determine their emotional state and transmits that information to the server.

[1417] Step 3:

[1418] Based on profile information, including emotional state, the server uses AI to generate content that is more suited to the user's mood and situation.

[1419] Step 4:

[1420] The server transmits the generated content to the user's terminal, where the user can use it in real time.

[1421] In this way, a system will be realized in which creators can continue their creative activities by receiving appropriate compensation, users can easily obtain content that matches their preferences and emotional state, and companies can quickly generate and utilize effective marketing content.

[1422] Example 2

[1423] 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."

[1424] Conventional digital content generation systems have difficulty generating customized content based on user profile information and behavioral history. Furthermore, they have not adequately addressed the generation of custom content as a marketing tool for businesses, the appropriate distribution of rewards to creators, or the provision of content tailored to users' emotional states. As a result, many challenges remain in improving user satisfaction, ensuring fairness in creator reward systems, and meeting the targeting accuracy required by businesses.

[1425] 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.

[1426] In this invention, the server has a database for storing digital content created by creators, and includes: means for generating customized content using a generative AI model based on user profile information and past behavioral history; means for generating custom content for companies tailored to a specific theme or target audience; means for calculating and distributing rewards to creators based on the degree to which the generated content was influenced by the original creator's work; and means for recognizing the user's emotional state and generating customized content based thereon. This makes it possible to provide content based on the user's preferences and emotions, achieve fair reward distribution to creators, and generate marketing content for companies with high target accuracy.

[1427] "Creator" refers to an individual or organization that creates digital content and provides it to this system.

[1428] "Digital content" refers to content stored and transmitted in electronic form, such as music, art, stories, recipes, and designs.

[1429] "Database" means a storage system within the system that accumulates and manages creator-provided digital content and associated metadata.

[1430] "User" means an individual or entity that requests and uses customized content through the System.

[1431] "Profile Information" refers to personal information about a user, as well as data such as preferences and behavioral history.

[1432] "Behavioral history" refers to data such as the operations a user performs within the system and their browsing history.

[1433] A "generative AI model" is an algorithm that uses artificial intelligence technology to generate customized content based on a user's profile information and requests.

[1434] "Custom Content" refers to digital content that is customized to meet the needs of a particular user or business.

[1435] "Reward" refers to monetary compensation calculated based on the influence of the generated content on the work of the original creator.

[1436] "Emotional state" is data that indicates a user's current emotions and is collected using facial recognition technology and voice analysis.

[1437] "Interface" refers to the screens and input forms that allow creators, users, and companies to interact with the system.

[1438] "Marketing Tools" refers to digital content that a business uses to advertise and promote to its target audience.

[1439] MODE FOR CARRYING OUT THE INVENTION

[1440] The present invention relates to a system for storing digital content created by creators and generating customized content for users and businesses. The system of the present invention utilizes an emotion engine to recognize the user's emotional state and customize content based on that state, thereby providing a higher level of satisfaction.

[1441] 1. Creator content submissions

[1442] A creator uses a user terminal to upload a digital content file to the system. The user terminal displays a dialog box for file selection and a form for inputting metadata (title, description, tags). When the creator enters this information and performs the upload, the server receives the relevant data and stores it in a database. The file is tagged and an index is generated for easy future search. As a concrete example, a creator uploads a music track they created to the system, and the server stores the track and metadata in a database and tags it.

[1443] 2. Accepting custom user requests

[1444] The user device provides a form for the user to request customized digital content. The user enters information into fields for their preferences and conditions, such as genre and tempo. After entering the conditions and clicking the submit button, the server retrieves the user's profile information and past behavioral history from a database and generates customized content using a generative AI model.

[1445] 3. Customized Content Generation

[1446] The server uses a generative AI model to generate customized content based on the acquired profile information. Specifically, it sends a prompt tailored to the specific user to the generative AI model. For example, it uses the prompt, "Generate the best music for when you want to relax." The generated content is then sent to the user's device, where the user can view or play it.

[1447] 4. Learning user preferences

[1448] The server periodically collects the user's browsing history and behavioral patterns, and updates the profile based on the user's preferences. This data is used to generate more accurate content for future customizations.

[1449] 5. Custom request acceptance for companies

[1450] The user device displays a dedicated interface for businesses, who then request custom content tailored to a specific theme or target audience. The server receives the business's request, builds a profile of the specified theme or target audience, and uses AI to generate appropriate content and provide it to the business.

[1451] 6. Creator Remuneration Calculation

[1452] The server analyzes the degree to which the generated content was influenced by the original creator's work. Based on the degree of influence, the server calculates and distributes rewards to the creator. For example, the server analyzes the degree to which a music track generated by a generative AI model was influenced by the original creator, and calculates monetary rewards based on the results.

[1453] 7. User Emotion Recognition

[1454] The user device uses an emotion engine to recognize the user's face and analyze their voice to determine their emotional state. The server updates the user's profile based on this information and generates content in real time that matches their emotions. Specifically, the server sends a prompt to the AI ​​model, such as "Please generate music that is best suited to when the user is sad," and then provides the generated content.

[1455] In this way, the system generates and delivers high-quality digital content that meets the needs of creators, users, and businesses.

[1456] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1457] The flow of this system's program processing

[1458] Step 1: Creator Content Submission

[1459] Specific actions

[1460] The user terminal displays an interface for creators to post digital content.

[1461] Input: Creator selects a file and enters a title, description, and tags.

[1462] Output: The input files and metadata are generated.

[1463] Data Processing

[1464] The server receives the file and metadata sent from the user terminal.

[1465] Input: Files and metadata from the user's device.

[1466] Output: Save files and metadata to a database.

[1467] What happens: The server creates a new entry in the database, storing the file path and metadata, then runs the tagging algorithm to generate the index.

[1468] Step 2: Accepting a user's custom request

[1469] Specific actions

[1470] The user terminal provides a form for the user to request customized digital content.

[1471] Input: The user inputs preferences and conditions such as genre and tempo.

[1472] Output: Generates the request data.

[1473] Data Processing

[1474] The server receives a request from the user terminal and retrieves the user's profile information and past behavior history from the database.

[1475] Input: User request data, profile information, and past behavior.

[1476] Output: The input data to a generative AI model.

[1477] What it does: The server queries the database for relevant user data and creates a prompt to pass to the generative AI model.

[1478] Step 3: Customized content generation

[1479] Specific actions

[1480] The server sends the prompt sentences to a generative AI model to generate customized content.

[1481] Input: Prompt statement (e.g., "Generate the perfect music for when you want to relax").

[1482] Output: The generated customization content.

[1483] Data Processing

[1484] The server transmits the generated content to the user terminal.

[1485] Input: The generated customization content.

[1486] Output: Data sent to the user's terminal.

[1487] Specific operation: The server receives content from the generative AI model and sends it to the user's device.

[1488] Step 4: Learning user preferences

[1489] Specific actions

[1490] The server periodically collects and learns from users' browsing history and behavioral patterns.

[1491] Input: User operation log data.

[1492] Output: The updated profile data.

[1493] Data Processing

[1494] The server updates the user's profile based on the collected data.

[1495] Input: User operation log.

[1496] Output: The updated profile information.

[1497] Specific operation: The server analyzes the operation log and updates the profile information.

[1498] Step 5: Custom Requests for Businesses

[1499] Specific actions

[1500] The user terminal displays an interface specifically for the enterprise.

[1501] Input: Specific topic and target audience information entered by the company.

[1502] Output: Generates the request data.

[1503] Data Processing

[1504] The server receives the business's request and builds a profile of the target.

[1505] Input: Company request data.

[1506] Output: Prompt statement and custom content.

[1507] How it works: The server creates prompts for the generative AI model based on the company's request and generates custom content.

[1508] Step 6: Creator Reward Calculation

[1509] Specific actions

[1510] The server compares the generated content with the original creator's work.

[1511] Input: Generated content, original creator work.

[1512] Output: Impact score.

[1513] Data Processing

[1514] The server calculates rewards based on the degree of influence and distributes them to creators.

[1515] Input: Impact score.

[1516] Output: Determination and allocation of reward amounts.

[1517] Specific operation: The server calculates the amount based on the influence score and transfers the reward to the creator's account.

[1518] Step 7: Recognizing user emotions

[1519] Specific actions

[1520] The user terminal uses an emotion engine to recognize the user's emotional state.

[1521] Input: User's facial expression data, voice data.

[1522] Output: Emotional state data.

[1523] Data Processing

[1524] The server generates customized content based on the emotional state.

[1525] Input: Emotional state data.

[1526] Output: Customized content.

[1527] Specific operation: The server sends the prompt "Please generate the best music for when the user is sad" to the generative AI model, and then sends the generated content to the user's device.

[1528] In this way, each step in the system has clear inputs and outputs, and through data processing and calculations, it is possible to provide users and businesses with highly customized digital content.

[1529] (Application example 2)

[1530] 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."

[1531] In today's digital content consumption environment, users have diverse needs based on diverse tastes and emotions. For this reason, providing static content is difficult to fully satisfy users. There is also a lack of efficient ways for companies to generate marketing content tailored to their target audiences. Furthermore, there is a need for a system that properly recognizes the extent to which creators' works have influenced users and distributes rewards fairly.

[1532] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1533] In this invention, the server has a database for storing digital content created by creators, and includes a means for receiving requests from users, a means for generating customized content using artificial intelligence based on user profile information and past behavioral history, a means for generating custom content for companies tailored to a specific theme or target audience, a means for calculating and distributing rewards to creators based on the degree to which the generated content was influenced by the original creator's work, a means for generating customized content in real time using facial recognition technology and emotion analysis technology based on the user's emotional state, a means for adapting the generated content to the user's emotional state and providing it in real time, and a means for collecting feedback from users and using it as learning data for the system. This makes it possible to provide content optimized to the preferences and emotions of each user, thereby realizing efficient generation of marketing content for companies and fair distribution of rewards to creators.

[1534] "Creator" means an individual or entity that creates digital content as their own creation and uploads it to the Platform.

[1535] "Digital content" is any creative work stored and distributed in digital form, such as music, art, stories, videos, recipes, or designs.

[1536] A "database" is a collection of information that stores digital content and related metadata created by creators and provides it in response to requests from users and companies.

[1537] "User" means an individual or legal entity that views and uses digital content, makes requests, and receives services.

[1538] "Profile Information" refers to basic data about a user (e.g., age, gender, location) and information obtained from past behavioral history.

[1539] "Artificial intelligence" is a technology that analyzes input data and generates optimal content based on user requests.

[1540] "Customized content" refers to digital content that is optimized for a specific user, generated based on the user's profile information, past behavioral history, and real-time emotional state.

[1541] "Company" refers to a legal entity that uses custom content tailored to a specific theme or target audience as a marketing tool.

[1542] "Theme" refers to the subject or motif that a company or user uses to generate specific content.

[1543] "Target audience" refers to the viewers or users that a particular piece of content is intended for.

[1544] "Facial recognition technology" is a technology for detecting and recognizing human faces using devices such as cameras.

[1545] "Emotion analysis technology" is a technology that analyzes and determines a user's emotions from recognized faces, voices, and text.

[1546] "Feedback" refers to the evaluations and opinions that users give about the content provided, and is information that is used as learning data for the system.

[1547] This invention combines an emotion engine with a system for storing digital content created by creators and generating customized content for users and businesses. Specific embodiments of this system are described below.

[1548] 1. Creators' submissions and database creation

[1549] The server provides an interface for creators to post digital content. Creators enter metadata such as title, description, and tags along with the files they select. The server receives the files and metadata uploaded by creators and stores them in a database. It also tags them appropriately and creates an index for easy discovery by search engines. The software used for this includes a database management system (e.g., MySQL or PostgreSQL) and Python scripts for metadata processing.

[1550] 2. Processing your requests and creating customized works

[1551] The server provides a form for users to request customized digital content. Users use this form to enter their preferences and requirements. When the server receives the request from the user's device, it retrieves the user's profile information and past behavioral history from a database. Based on this information, it uses artificial intelligence (AI) to generate customized content and sends it to the user's device. This is done using machine learning libraries (e.g., TensorFlow and PyTorch).

[1552] 3. Learning based on user preferences and generating new works

[1553] The server periodically collects the user's browsing history and behavioral patterns to learn their preferences. This data is used to update the user's profile. When a new request is received, the server generates content that is more appropriate for the user based on the latest profile information. Data processing is done using large-scale data processing frameworks such as BigQuery and Hadoop.

[1554] 4. Custom requests and playlist sponsorships for companies

[1555] The server provides a dedicated interface for businesses. Businesses use this interface to request custom content tailored to a specific theme or target audience. The server receives the business's request and builds a profile of the specified theme or target audience. It uses AI to generate appropriate content and provides it to the business. It uses digital marketing tools (e.g., Google Analytics or Adobe Analytics) to see how the business uses the generated content as a marketing tool.

[1556] 5. Calculating rewards and providing market feedback to creators

[1557] The server compares the AI-generated content with the original creator's work and analyzes the degree of influence. Based on this degree of influence, rewards are calculated and distributed to the creator. It also collects market feedback on the generated work in real time and provides it to the creator. This is done using a distributed processing system (e.g., Apache Kafka or Flume).

[1558] 6. User Emotion Recognition and Content Generation

[1559] The user device is equipped with an emotion engine to recognize the user's emotional state. This emotion engine uses a camera to capture the user's face in real time and analyzes their emotions. It also analyzes the user's input text and voice to determine their emotional state and generate customized content based on that information. The software used for this includes a facial recognition framework (e.g., OpenCV), an emotion analysis library (e.g., EmotionRecognizer), and a natural language processing model (e.g., BERT).

[1560] For example, if the user has a relaxed expression while playing shuffle, the system will recommend music with a relaxing effect. An example of a prompt sentence is, "If the user's emotion is determined to be relaxed, please recommend music with a relaxing effect. For example, music in the genres 'Ambient' or 'Chillout' is recommended."

[1561] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1562] Step 1:

[1563] Creator submissions

[1564] The server provides an interface for creators to post digital content. Creators enter metadata such as title, description, and tags along with the files they select. The entered data is received by the server and stored in a database. The server tags the metadata and generates an index to make it easily discoverable by search engines.

[1565] Input: Creator-submitted digital content files and metadata

[1566] Output: Digital content and metadata stored in a database

[1567] Step 2:

[1568] Receiving a user request

[1569] The user device provides a form for requesting customized digital content. The user uses this form to input their preferences and requirements. The input request data is sent to the server, which combines it with the user's profile information and past behavior. The user information is retrieved from the database and prepared for processing the request.

[1570] Input: Preferences and conditions entered by the user into the request form

[1571] Output: Request data sent to the server

[1572] Step 3:

[1573] Customized Content Generation

[1574] The server generates customized content using a generative AI model based on the request data. Specifically, it analyzes the request data, the user's profile information, and past behavioral history, and uses machine learning libraries (e.g., TensorFlow and PyTorch) to generate optimal content based on that information. The generated content is then sent to the user's device.

[1575] Input: Request data, profile information, past behavior history

[1576] Output: Customized digital content

[1577] Step 4:

[1578] User emotion recognition

[1579] The user device uses a camera to capture the user's face in real time and analyzes their emotions using an emotion analysis engine (e.g., EmotionRecognizer). The emotion data is added to the user's profile information, which is then used as input data for the AI ​​model.

[1580] Input: Camera image

[1581] Output: User emotion data

[1582] Step 5:

[1583] Real-time content generation and delivery

[1584] The server uses a generative AI model to generate customized content in real time based on the user's profile information, including emotional data. The generated content is then sent to the user's device and provided in real time, allowing the user to instantly receive content that is appropriate for their emotional state.

[1585] Input: User emotion data, profile information

[1586] Output: Real-time customized digital content

[1587] Step 6:

[1588] Gathering user feedback

[1589] The user's device collects feedback from the user regarding the provided content (e.g., like button, comments). This feedback information is sent to the server and used as learning data for the system. This improves the accuracy of the AI ​​model and allows it to generate better customized content.

[1590] Input: User feedback

[1591] Output: Feedback data sent to the server

[1592] 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.

[1593] 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.

[1594] 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.

[1595] [Fourth embodiment]

[1596] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1597] 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.

[1598] 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).

[1599] 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.

[1600] 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.

[1601] 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).

[1602] 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.

[1603] 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.

[1604] 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.

[1605] 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.

[1606] 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.

[1607] 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.

[1608] 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."

[1609] The present invention is a system for storing digital content created by creators and generating customized content for users and companies. A specific embodiment of this system will be described below.

[1610] 1. Creators' submissions and database creation

[1611] The user device provides an interface for creators to post digital content. This interface consists of a screen for uploading files such as music, art, stories, recipes, and designs. When uploading content, creators also enter metadata such as title, description, and tags.

[1612] The server receives the files and metadata uploaded by creators, stores them in a database, properly tags the content, and indexes it for easy discovery by search engines.

[1613] 2. Processing your requests and creating customized works

[1614] The user terminal provides a form for the user to request customized digital content, allowing the user to input their preferences and requirements.

[1615] When the server receives a request, it retrieves the user's profile information and past behavioral history from a database. Based on this information, it uses artificial intelligence (AI) to generate customized content. The generated content is then sent to the user's device, where the user can view or use it.

[1616] 3. Learning based on user preferences and generating new works

[1617] The server periodically collects the user's browsing history and behavioral patterns to learn their preferences. This data is used to update the user's profile. When a new request is received, the server generates more relevant content based on the updated profile information.

[1618] 4. Custom requests and playlist sponsorships for companies

[1619] The terminal provides a dedicated interface for businesses to request custom content tailored to a specific theme or target audience.

[1620] The server receives a company's request, builds a profile of the specified theme and target audience, and uses AI to generate appropriate content and provide it to the company, who can then use the generated content as a marketing tool.

[1621] 5. Calculating rewards and providing market feedback to creators

[1622] The server compares the AI-generated content with the original creator's work and analyzes the degree of influence. Based on this influence, rewards are calculated and distributed to the creator. It also collects market feedback on the generated work in real time and provides it to the creator.

[1623] Specific examples

[1624] 1. Creator submissions:

[1625] Creators upload their music tracks to the platform, and the server stores and tags the tracks and metadata in a database.

[1626] 2. User custom request:

[1627] A user requests music of a specific genre, and the server uses AI to generate a new music track based on the user's profile and past listening history, and sends it to the user's device.

[1628] 3. Custom requests from companies:

[1629] A company requests a music playlist for a Christmas campaign. The server creates a target profile based on the company's request and uses AI to generate and serve music.

[1630] 4. Creator Rewards:

[1631] The AI ​​measures the degree to which the generated track is influenced by the original creator, and the server calculates and distributes rewards to the creator based on that influence.

[1632] In this way, creators can continue their creative activities by receiving appropriate compensation, users can easily obtain content that suits their preferences, and companies can quickly generate and utilize effective marketing content.

[1633] The processing flow will be explained below.

[1634] Creators' submission of works and creation of a database

[1635] Step 1:

[1636] The user device displays an interface for creators to post digital content, who select files such as music, art, stories, recipes, and designs, and enter metadata such as titles, descriptions, and tags.

[1637] Step 2:

[1638] The user clicks the upload button, sending the selected file and the entered metadata to the server.

[1639] Step 3:

[1640] The server receives the uploaded file and metadata, inspects the content, and decides where to store it.

[1641] Step 4:

[1642] The server saves the file to storage and inserts the metadata into a database.

[1643] Step 5:

[1644] The server adds appropriate tags to the uploaded content and indexes it in a database.

[1645] Processing user requests and generating customized works

[1646] Step 1:

[1647] The user terminal displays a form for the user to request customized digital content, and the user enters their preferences and requirements into the form.

[1648] Step 2:

[1649] When a user submits a request form, the contents are sent to the server.

[1650] Step 3:

[1651] The server receives the user's request and retrieves the user's profile information and past behavior history from a database.

[1652] Step 4:

[1653] The server uses artificial intelligence (AI) to generate new customized content based on the profile information and past behavioral history obtained.

[1654] Step 5:

[1655] The server transmits the generated customized content to the user's terminal.

[1656] Learning based on user preferences and generating new works

[1657] Step 1:

[1658] The server periodically collects users' browsing history and behavioral patterns.

[1659] Step 2:

[1660] The server analyzes the user's preferences based on the collected data and updates the profile information.

[1661] Step 3:

[1662] With each new request, the server uses AI to generate more suitable content based on updated profile information.

[1663] Offering custom requests and playlist sponsorships for businesses

[1664] Step 1:

[1665] The user device displays a dedicated interface for businesses, which allows them to request custom content tailored to a specific theme or target audience.

[1666] Step 2:

[1667] When a company submits a request form, the contents are sent to the server.

[1668] Step 3:

[1669] The server receives the business's request and builds a profile of the specified theme and target audience.

[1670] Step 4:

[1671] The server uses AI to generate custom content that meets the company's requirements.

[1672] Step 5:

[1673] The server provides the generated content to the business and accepts feedback.

[1674] Calculating rewards and providing market feedback to creators

[1675] Step 1:

[1676] The server compares the AI-generated content with the original creator's work and calculates the degree of influence.

[1677] Step 2:

[1678] The server calculates the reward for the creator based on the influence.

[1679] Step 3:

[1680] The server distributes the calculated rewards to the creators.

[1681] Step 4:

[1682] The server collects and provides market feedback on the created works to the creators.

[1683] The above is a specific processing flow of the present invention. This specification creates an environment in which creators, users, and companies can easily achieve their respective goals.

[1684] Example 1

[1685] 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."

[1686] There is a need to develop a system that can centrally handle the posting and accumulation of digital content, the generation of customized content, the provision of content to users and businesses, the calculation of compensation for creators, and the provision of market feedback. This system must have the ability to efficiently manage data and provide highly accurate AI-generated content, while also establishing a mechanism for creators to receive appropriate compensation.

[1687] 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.

[1688] In this invention, the server has a database for storing digital content created by creators, and includes: means for receiving requests from users; means for receiving data from user terminals and storing it together with metadata; means for generating customized content using a generative AI model based on the user's profile information and past behavioral history and sending it to the user terminal; means for updating the user profile based on the user's browsing history and behavioral patterns; means for generating custom content for companies tailored to specific themes and target audiences, and means for creating target profiles based on company requests and generating content using AI; means for calculating rewards based on the influence of the generated content on the original creator's work and allocating them to creators; means for providing a dedicated interface for companies and receiving requests; and means for collecting market feedback in real time and providing it to creators. This enables efficient management of digital content and the provision of customized, high-quality AI-generated content.

[1689] "Creator" refers to an individual or entity that creates and submits digital content to the system.

[1690] "Digital content" refers to information assets provided in electronic form, such as music, art, stories, recipes, and designs.

[1691] "Database" means a structured data storage system for managing and storing Creator-contributed Digital Content and associated Metadata.

[1692] "User" means any individual or entity that utilizes the System to request customized digital content.

[1693] "Request" means a request by a User to the System to provide customized digital content.

[1694] "Profile information" refers to information about a user, a collection of data including the user's attributes, preferences, behavioral history, etc.

[1695] "Behavioral history" refers to records of the operations, selections, browsing information, etc. that a user performs within the system.

[1696] "Artificial intelligence (AI)" refers to machine learning and natural language processing technologies used to customize digital content based on user profile information and past behavior.

[1697] "Customized Content" refers to digital content that is generated based on a user's specific requests and preferences.

[1698] "Company" refers to a legal entity that requests the system to generate custom content tailored to a specific theme or target audience.

[1699] "Theme" means the primary subject or topic specified by a Company in a request for custom content generation.

[1700] "Target audience" refers to a specific group of viewers or buyers that a company is targeting.

[1701] "Remuneration" refers to monetary compensation paid to a creator based on the influence of the original creator's work on the generated content.

[1702] "Metadata" refers to additional information such as title, description, and tags that accompany digital content.

[1703] "Generative AI models" refer to algorithms or machine learning models that generate digital content based on user requests, based on collected data and profile information.

[1704] "Market feedback" refers to the reaction and evaluation of the generated content from the market and users.

[1705] "Private Interface" refers to a user interface provided to a business to make specific requests.

[1706] The present invention provides a system for storing digital content created by creators and generating customized content for users and businesses. The following describes in detail an embodiment of this system.

[1707] Creators' submission of works and database creation

[1708] The user device provides an interface for creators to post digital content. This interface consists of a screen for uploading files such as music, art, stories, recipes, and designs. When creators upload content, they can also enter metadata such as title, description, and tags.

[1709] The server receives uploaded files and metadata from creators. The data is stored in a database. The server then properly tags the stored content, allowing it to be indexed by search engines and making it easier for users to find.

[1710] Processing user requests and generating customized works

[1711] The user terminal provides a form for requesting digital content customized for the user, allowing the user to input their preferences and requirements.

[1712] The server receives the user's request. It analyzes the request and retrieves the user's profile information and past behavioral history from a database. Based on the retrieved information, the server uses a generative AI model to generate customized content. The generated content is sent to the user's device, where the user can view or use it.

[1713] Learning based on user preferences and generating new works

[1714] The server periodically collects your browsing history and behavioral patterns, and uses this data to learn your preferences and update your profile.

[1715] When a new request is received, the system generates more relevant content based on the user's latest profile information, leveraging generative AI models to enable highly accurate customization.

[1716] Offering custom requests and playlist sponsorships for businesses

[1717] The device provides a dedicated interface for businesses to request custom content tailored to a specific theme or target audience.

[1718] The server receives requests from businesses, builds profiles based on the specified theme and target audience, and uses generative AI models to generate customized content and provide it to businesses, who can then use the generated content as a marketing tool.

[1719] Calculating rewards and providing market feedback to creators

[1720] The server compares the AI-generated content with the original creator's work and analyzes the degree of influence. Based on this influence, it calculates and distributes rewards to the creator. It also collects market feedback on the generated work in real time and provides that feedback to the creator.

[1721] Specific examples

[1722] 1. Creators upload their own music tracks to the platform.

[1723] The server stores the tracks and metadata in a database and tags them appropriately.

[1724] 2. A user requests music of a particular genre.

[1725] The server uses a generative AI model based on the user profile and past history to generate new music tracks and send them to the user's device.

[1726] 3. A company requests a music playlist for their Christmas campaign.

[1727] The server creates a target profile based on the company's requirements and generates and delivers music using a generative AI model.

[1728] Prompt Sentence Examples

[1729] "Create a pop Christmas song."

[1730] "Generate relaxing background music with elements of classical music"

[1731] As described above, the present invention is a system that realizes efficient management and customized provision of digital content, and also distributes appropriate rewards to creators and provides marketing support to companies.

[1732] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1733] Creators' submission of works and database creation

[1734] Step 1:

[1735] The user device provides an interface for creators to upload digital content, select files such as music, art, or stories, and enter metadata such as titles, descriptions, and tags.

[1736] Input: Digital content file, title, description, tags

[1737] Output: Uploaded digital content and metadata

[1738] Step 2:

[1739] The server receives the digital content and metadata uploaded from the user terminal and stores the received data in a database.

[1740] Input: Digital content and metadata from the user's device

[1741] Output: Digital content and metadata stored in a database

[1742] Step 3:

[1743] The server properly tags the stored digital content and generates an index so that it can be easily found by search engines.

[1744] Input: Digital content and metadata stored in a database

[1745] Output: A tagged index of digital content

[1746] Processing user requests and generating customized works

[1747] Step 1:

[1748] The user terminal provides a request form for the user, and the user inputs his or her preferences and conditions.

[1749] Input: User preferences and conditions

[1750] Output: Request content

[1751] Step 2:

[1752] The server receives the user's request, retrieves the user's profile information and past behavioral history from a database, and uses this information to generate customized content using a generative AI model.

[1753] Input: User requests, profile information, and activity history

[1754] Output: Generated customized content

[1755] Step 3:

[1756] The server transmits the generated customized content to the user terminal, which receives and displays it, and the user views or uses the content.

[1757] Input: Generated customization content

[1758] Output: Content displayed on the user's device

[1759] Learning based on user preferences and generating new works

[1760] Step 1:

[1761] The server periodically collects users' browsing history and behavioral patterns and analyzes the data, thereby learning their preferences.

[1762] Input: User browsing history, behavioral patterns

[1763] Output: Parsed data, updated profile

[1764] Step 2:

[1765] When a new request is received, the server generates content based on the latest profile information and customizes it to match the user's preferences.

[1766] Input: Latest profile information, user requests

[1767] Output: Customized content

[1768] Offering custom requests and playlist sponsorships for businesses

[1769] Step 1:

[1770] The terminal provides a dedicated interface for businesses, allowing them to input requests for custom content tailored to a specific theme or target audience.

[1771] Input: Company theme, target audience criteria

[1772] Output: Request from company

[1773] Step 2:

[1774] The server receives requests from businesses, builds profiles based on specified themes and target audiences, and uses generative AI models to generate and deliver customized content to businesses.

[1775] Input: Company request, theme, target audience criteria

[1776] Output: Corporate customized content

[1777] Calculating rewards and providing market feedback to creators

[1778] Step 1:

[1779] The server compares the AI-generated content with the original creator's work, analyzes the degree of influence, and calculates rewards based on the degree of influence.

[1780] Input: Generated content, the work of the original creator

[1781] Output: Impact analysis results, calculated rewards

[1782] Step 2:

[1783] The server collects market feedback on the created works in real time and provides the feedback to the creators.

[1784] Input: Market Feedback

[1785] Output: Feedback provided to the creator

[1786] Specific examples

[1787] 1. Creators upload their music tracks to the platform, and the server stores the tracks and metadata in a database, tagging them appropriately.

[1788] 2. A user requests music of a specific genre. The server uses a generative AI model based on the user profile and past history to generate a new music track and sends it to the user's device.

[1789] 3. A company requests a music playlist for a Christmas campaign. The server creates a target profile based on the company's requirements and generates and serves music using a generative AI model.

[1790] (Application example 1)

[1791] 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."

[1792] Traditional digital content creation and distribution systems have made it difficult to provide personalized content that perfectly matches users' individual preferences and lack appropriate compensation distribution to creators. In addition, it has been difficult to quickly generate marketing content tailored to target audiences for businesses. This has hindered the improvement of user experience and the provision of flexible services to creators and businesses.

[1793] 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.

[1794] In this invention, the server includes means for providing a database for storing digital content created by creators, means for receiving requests from users, means for generating customized content using a generative artificial intelligence based on the user's profile information and past behavioral history, means for generating custom content for companies tailored to a specific theme or target audience, means for calculating and allocating rewards to creators based on the degree to which the generated content was influenced by the original creator's work, means for recommending new content using a generative artificial intelligence model based on user preferences, and means for logging content usage history. This makes it possible to provide personalized content that meets the preferences of individual users, thereby enabling appropriate reward allocation to creators and the rapid generation of targeted marketing content for companies.

[1795] "Creator" means an individual or entity that creates and provides digital content.

[1796] "Digital content" refers to data in digital form, such as music, video, images, and text.

[1797] A "database" is a system that systematically accumulates and manages digital content and related information created by creators.

[1798] "User" means any individual or entity that uses the System to request, view or use Digital Content.

[1799] A "means for receiving requests" is an interface or system for receiving requests for customized content from users.

[1800] "Profile information" refers to data such as a user's basic information, preferences, and past behavioral history.

[1801] "Past behavior history" is a record of the activities a user has performed within the system.

[1802] "Generative AI" refers to machine learning algorithms and models that generate new content based on input data.

[1803] The "means for generating customized content" is a system that uses the user's profile information and past behavioral history to create content optimized for the user.

[1804] The "means for generating custom content for businesses" is a system that generates content tailored to specific themes based on business requests and target audiences.

[1805] "Influence" is a measure of the degree to which the generated content is based on the work of the original creator.

[1806] "Means for calculating rewards and distributing them to creators" refers to a system that calculates and pays appropriate rewards to creators based on their level of influence.

[1807] "Means for recommending new content using a generative artificial intelligence model" is a system that presents optimal content as candidates based on the user's preferences.

[1808] "Logging means" refers to a system that stores a user's content usage history and uses it for later analysis and recommendations.

[1809] The present invention is a system for storing digital content created by creators and providing customized content to users and businesses. This system is realized using the following hardware and software.

[1810] System configuration

[1811] 1. Server:

[1812] A database for storing digital content

[1813] An interface that receives requests from users

[1814] Profile information and past behavior history management system

[1815] Computing infrastructure for running generative artificial intelligence (AI) models

[1816] 2. Terminal:

[1817] An interface for creators to post content

[1818] An interface for users and businesses to request customized content

[1819] An interface for recommending new content to users

[1820] Data processing and calculation

[1821] Building the database:

[1822] The server stores digital content such as music, videos, images, and text uploaded by creators in a database, along with metadata (title, description, tags, etc.).

[1823] Request Processing and Customization:

[1824] When a user requests customized content through their device, the request data is sent to a server, which uses generative artificial intelligence (AI) to generate new content based on the user's profile information and past behavioral history, and provides it to the user.

[1825] Enterprise Customization:

[1826] When a company requests content for a specific theme or target audience, the server builds a profile based on the company's requirements and uses AI to generate custom content, which is then provided to the company as a marketing tool.

[1827] Recording of content usage history:

[1828] Every time a user interacts with content, the history is recorded as a log on the server, and this historical data is later used as training data for the recommendation algorithm.

[1829] Reward Calculation:

[1830] The AI-generated content is measured to determine the degree of similarity (influence) between it and the original creator's work, and the reward is calculated based on that. The calculated reward is then distributed to the creator.

[1831] Specific examples

[1832] User scenario:

[1833] 1. The user requests "I want to listen to relaxing music" from their device.

[1834] 2. The server retrieves the user's profile information and past behavioral history, and based on this, the AI ​​generates a suitable music track.

[1835] 3. The generated music track is sent to the device where the user listens to it.

[1836] Example prompt sentence:

[1837] "I want to listen to relaxing music. Please generate new music tracks that suit my tastes."

[1838] In this way, users can easily obtain the most suitable content according to their individual preferences, and creators and businesses can also be provided with flexible services.

[1839] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1840] Step 1:

[1841] Creators upload digital content. The device provides an interface for creators to post digital content such as music, videos, images, and text. Creators enter metadata such as title, description, and tags and upload the content. The entered content and metadata are sent to the server. The server receives this data and stores it in a database.

[1842] Step 2:

[1843] The user requests customized content. The user inputs their preferences and conditions using the device's request interface. For example, they input a request such as "I want to listen to relaxing music." This request is then sent to the server.

[1844] Step 3:

[1845] The server retrieves the user's profile information and past behavior history. When the server receives the request, it retrieves the user's profile information and past behavior history from the database. These data are used as input in the next step.

[1846] Step 4:

[1847] The server uses AI to generate customized content. The server uses the acquired user profile information and past behavioral history as input data to input a prompt to the generative AI model. For example, the prompt might be, "I want to listen to relaxing music. Please generate a new music track that suits the user's preferences." The AI ​​model generates new content based on this input and outputs the results to the server.

[1848] Step 5:

[1849] The server provides the generated content to the user. The generated content (e.g., a music track) is sent from the server to the user's device. The user can then view or use the new content on their device.

[1850] Step 6:

[1851] The server logs the content usage history. The history of content that a user has viewed or used is recorded as a log on the server. This history data is used for future content generation and recommendation algorithms.

[1852] Step 7:

[1853] The server calculates the reward for the creator. It measures the influence of the original creator's work on the generated content and calculates the reward based on that influence. The result of this calculation is distributed to the creator as a reward.

[1854] Step 8:

[1855] A business requests custom content tailored to a specific theme or target audience. The business uses its device to send a request for custom content tailored to a theme or target audience to a server. The server builds a profile based on the request and generates relevant content using an AI model. The business uses the generated content as a marketing tool.

[1856] 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.

[1857] The present invention combines an emotion engine with a system for storing digital content created by creators and generating customized content for users and businesses. Specific embodiments of this system are described below.

[1858] 1. Creators' submissions and database creation

[1859] The user device displays an interface for creators to post digital content, selecting files such as music, art, stories, recipes, and designs, and entering metadata such as titles, descriptions, and tags.

[1860] The server receives the files and metadata uploaded by creators, stores them in a database, properly tags the content, and indexes it for easy discovery by search engines.

[1861] 2. Processing your requests and creating customized works

[1862] The user terminal provides a form for the user to request customized digital content, by inputting his / her preferences and requirements.

[1863] When the server receives the request, it retrieves the user's profile information and past behavioral history from a database. Based on this information, it uses artificial intelligence (AI) to generate customized content. The generated content is then sent to the user's device, where the user can view or use it.

[1864] 3. Learning based on user preferences and generating new works

[1865] The server periodically collects a user's browsing history and behavioral patterns to learn their preferences. This data is used to update the user's profile. When a new request is received, the server generates more relevant content based on the updated profile information.

[1866] 4. Custom requests and playlist sponsorships for companies

[1867] The user device displays a dedicated interface for businesses, which allows businesses to request custom content tailored to a specific theme or target audience.

[1868] The server receives a company's request, builds a profile of the specified theme and target audience, and uses AI to generate appropriate content and provide it to the company, who can then use the generated content as a marketing tool.

[1869] 5. Calculating rewards and providing market feedback to creators

[1870] The server compares the AI-generated content with the original creator's work and analyzes the degree of influence. Based on this influence, rewards are calculated and distributed to the creator. It also collects market feedback on the generated work in real time and provides it to the creator.

[1871] 6. User Emotion Recognition and Content Generation

[1872] The user device is equipped with an emotion engine that recognizes the user's emotional state. The emotion engine uses facial recognition technology to analyze the user's emotions and adds the results to the user's profile information. It also analyzes the user's input text and voice to determine the user's emotional state and generates customized content based on that information.

[1873] The server utilizes profile information, including the user's emotional state, to generate content that is more suited to the user's mood and situation. The generated content is customized to the user's real-time emotional state, providing a higher level of satisfaction.

[1874] Specific examples

[1875] 1. Creator submissions:

[1876] Creators upload their music tracks to the platform, and the server stores and tags the tracks and metadata in a database.

[1877] 2. User custom request:

[1878] A user requests music of a specific genre. The server uses AI to generate new music tracks based on the user's profile information and past listening history, and sends them to the user's device. It also takes into account the user's emotional state to provide music that matches their mood.

[1879] 3. User emotion recognition:

[1880] The user device takes a picture of the user's face with a camera and recognizes emotions from facial expressions. For example, if it determines that the user is relaxed, it generates relaxing music to match that.

[1881] 4. Corporate custom requests:

[1882] A company requests a music playlist for a Christmas campaign. The server creates a target profile based on the company's request and uses AI to generate and serve music.

[1883] 5. Creator Rewards:

[1884] The server measures the degree to which the AI-generated track is influenced by the original creator, and calculates and distributes rewards to the creator based on that influence.

[1885] In this way, specific embodiments of the present invention realize a system that allows creators to continue their creative activities with appropriate rewards, users to easily obtain content that suits their preferences and emotional state, and companies to quickly generate and utilize effective marketing content.

[1886] The processing flow will be explained below.

[1887] Creators' submission of works and creation of a database

[1888] Step 1:

[1889] The user device displays an interface for creators to post digital content, who select files such as music, art, stories, recipes, and designs, and enter metadata such as titles, descriptions, and tags.

[1890] Step 2:

[1891] When the user clicks the upload button, the selected file and the entered metadata are sent to the server.

[1892] Step 3:

[1893] The server receives the uploaded file and metadata, inspects the content, and decides where to store it.

[1894] Step 4:

[1895] The server saves the file to storage and inserts the metadata into a database.

[1896] Step 5:

[1897] The server assigns appropriate tags to the uploaded content and indexes it in a database.

[1898] Processing user requests and generating customized works

[1899] Step 1:

[1900] The user terminal provides the user with a form for requesting customized digital content, in which the user inputs their preferences and requirements.

[1901] Step 2:

[1902] When a user submits a request form, the contents are sent to the server.

[1903] Step 3:

[1904] The server receives the user's request and retrieves the user's profile information and past behavioral history from a database.

[1905] Step 4:

[1906] The server uses artificial intelligence (AI) to generate new customized content based on the profile information and past behavioral history obtained.

[1907] Step 5:

[1908] The server transmits the generated customized content to the user's terminal.

[1909] Learning based on user preferences and generating new works

[1910] Step 1:

[1911] The server periodically collects users' browsing history and behavioral patterns.

[1912] Step 2:

[1913] The server analyzes the user's preferences based on the collected data and updates the profile information.

[1914] Step 3:

[1915] With each new request, the server uses AI to generate more appropriate content based on the updated profile information.

[1916] Offering custom requests and playlist sponsorships for businesses

[1917] Step 1:

[1918] The device displays a dedicated interface for businesses, which they can use to request custom content tailored to a specific theme or target audience.

[1919] Step 2:

[1920] When a company submits a request form, the contents are sent to the server.

[1921] Step 3:

[1922] The server receives the business's request and builds a profile of the specified theme and target audience.

[1923] Step 4:

[1924] The server uses AI to generate custom content that meets the company's requirements.

[1925] Step 5:

[1926] The server provides the generated content to the business and accepts feedback.

[1927] Calculating rewards and providing market feedback to creators

[1928] Step 1:

[1929] The server compares the AI-generated content with the original creator's work and calculates the degree of influence.

[1930] Step 2:

[1931] The server calculates the reward for the creator based on the influence.

[1932] Step 3:

[1933] The server distributes the calculated rewards to the creators.

[1934] Step 4:

[1935] The server collects and provides market feedback on the created works to the creators.

[1936] User emotion recognition and content generation

[1937] Step 1:

[1938] The user terminal is equipped with an emotion engine to recognize the user's emotional state, which uses facial recognition technology to analyze the user's emotions and adds the results to the profile information.

[1939] Step 2:

[1940] The user terminal analyzes the user's input text and voice to determine their emotional state and transmits that information to the server.

[1941] Step 3:

[1942] Based on profile information, including emotional state, the server uses AI to generate content that is more suited to the user's mood and situation.

[1943] Step 4:

[1944] The server transmits the generated content to the user's terminal, where the user can use it in real time.

[1945] In this way, a system will be realized in which creators can continue their creative activities by receiving appropriate compensation, users can easily obtain content that matches their preferences and emotional state, and companies can quickly generate and utilize effective marketing content.

[1946] Example 2

[1947] 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."

[1948] Conventional digital content generation systems have difficulty generating customized content based on user profile information and behavioral history. Furthermore, they have not adequately addressed the generation of custom content as a marketing tool for businesses, the appropriate distribution of rewards to creators, or the provision of content tailored to users' emotional states. As a result, many challenges remain in improving user satisfaction, ensuring fairness in creator reward systems, and meeting the targeting accuracy required by businesses.

[1949] 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.

[1950] In this invention, the server has a database for storing digital content created by creators, and includes: means for generating customized content using a generative AI model based on user profile information and past behavioral history; means for generating custom content for companies tailored to a specific theme or target audience; means for calculating and distributing rewards to creators based on the degree to which the generated content was influenced by the original creator's work; and means for recognizing the user's emotional state and generating customized content based thereon. This makes it possible to provide content based on the user's preferences and emotions, achieve fair reward distribution to creators, and generate marketing content for companies with high target accuracy.

[1951] "Creator" refers to an individual or organization that creates digital content and provides it to this system.

[1952] "Digital content" refers to content stored and transmitted in electronic form, such as music, art, stories, recipes, and designs.

[1953] "Database" means a storage system within the system that accumulates and manages creator-provided digital content and associated metadata.

[1954] "User" means an individual or entity that requests and uses customized content through the System.

[1955] "Profile Information" refers to personal information about a user, as well as data such as preferences and behavioral history.

[1956] "Behavioral history" refers to data such as the operations a user performs within the system and their browsing history.

[1957] A "generative AI model" is an algorithm that uses artificial intelligence technology to generate customized content based on a user's profile information and requests.

[1958] "Custom Content" refers to digital content that is customized to meet the needs of a particular user or business.

[1959] "Reward" refers to monetary compensation calculated based on the influence of the generated content on the work of the original creator.

[1960] "Emotional state" is data that indicates a user's current emotions and is collected using facial recognition technology and voice analysis.

[1961] "Interface" refers to the screens and input forms that allow creators, users, and companies to interact with the system.

[1962] "Marketing Tools" refers to digital content that a business uses to advertise and promote to its target audience.

[1963] MODE FOR CARRYING OUT THE INVENTION

[1964] The present invention relates to a system for storing digital content created by creators and generating customized content for users and businesses. The system of the present invention utilizes an emotion engine to recognize the user's emotional state and customize content based on that state, thereby providing a higher level of satisfaction.

[1965] 1. Creator content submissions

[1966] A creator uses a user terminal to upload a digital content file to the system. The user terminal displays a dialog box for file selection and a form for inputting metadata (title, description, tags). When the creator enters this information and performs the upload, the server receives the relevant data and stores it in a database. The file is tagged and an index is generated for easy future search. As a concrete example, a creator uploads a music track they created to the system, and the server stores the track and metadata in a database and tags it.

[1967] 2. Accepting custom user requests

[1968] The user device provides a form for the user to request customized digital content. The user enters information into fields for their preferences and conditions, such as genre and tempo. After entering the conditions and clicking the submit button, the server retrieves the user's profile information and past behavioral history from a database and generates customized content using a generative AI model.

[1969] 3. Customized Content Generation

[1970] The server uses a generative AI model to generate customized content based on the acquired profile information. Specifically, it sends a prompt tailored to the specific user to the generative AI model. For example, it uses the prompt, "Generate the best music for when you want to relax." The generated content is then sent to the user's device, where the user can view or play it.

[1971] 4. Learning user preferences

[1972] The server periodically collects the user's browsing history and behavioral patterns, and updates the profile based on the user's preferences. This data is used to generate more accurate content for future customizations.

[1973] 5. Custom request acceptance for companies

[1974] The user device displays a dedicated interface for businesses, who then request custom content tailored to a specific theme or target audience. The server receives the business's request, builds a profile of the specified theme or target audience, and uses AI to generate appropriate content and provide it to the business.

[1975] 6. Creator Remuneration Calculation

[1976] The server analyzes the degree to which the generated content was influenced by the original creator's work. Based on the degree of influence, the server calculates and distributes rewards to the creator. For example, the server analyzes the degree to which a music track generated by a generative AI model was influenced by the original creator, and calculates monetary rewards based on the results.

[1977] 7. User Emotion Recognition

[1978] The user device uses an emotion engine to recognize the user's face and analyze their voice to determine their emotional state. The server updates the user's profile based on this information and generates content in real time that matches their emotions. Specifically, the server sends a prompt to the AI ​​model, such as "Please generate music that is best suited to when the user is sad," and then provides the generated content.

[1979] In this way, the system generates and delivers high-quality digital content that meets the needs of creators, users, and businesses.

[1980] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1981] The flow of this system's program processing

[1982] Step 1: Creator Content Submission

[1983] Specific actions

[1984] The user terminal displays an interface for creators to post digital content.

[1985] Input: Creator selects a file and enters a title, description, and tags.

[1986] Output: The input files and metadata are generated.

[1987] Data Processing

[1988] The server receives the file and metadata sent from the user terminal.

[1989] Input: Files and metadata from the user's device.

[1990] Output: Save files and metadata to a database.

[1991] What happens: The server creates a new entry in the database, storing the file path and metadata, then runs the tagging algorithm to generate the index.

[1992] Step 2: Accepting a user's custom request

[1993] Specific actions

[1994] The user terminal provides a form for the user to request customized digital content.

[1995] Input: The user inputs preferences and conditions such as genre and tempo.

[1996] Output: Generates the request data.

[1997] Data Processing

[1998] The server receives a request from the user terminal and retrieves the user's profile information and past behavior history from the database.

[1999] Input: User request data, profile information, and past behavior.

[2000] Output: The input data to a generative AI model.

[2001] What it does: The server queries the database for relevant user data and creates a prompt to pass to the generative AI model.

[2002] Step 3: Customized content generation

[2003] Specific actions

[2004] The server sends the prompt sentences to a generative AI model to generate customized content.

[2005] Input: Prompt statement (e.g., "Generate the perfect music for when you want to relax").

[2006] Output: The generated customization content.

[2007] Data Processing

[2008] The server transmits the generated content to the user terminal.

[2009] Input: The generated customization content.

[2010] Output: Data sent to the user's terminal.

[2011] Specific operation: The server receives content from the generative AI model and sends it to the user's device.

[2012] Step 4: Learning user preferences

[2013] Specific actions

[2014] The server periodically collects and learns from users' browsing history and behavioral patterns.

[2015] Input: User operation log data.

[2016] Output: The updated profile data.

[2017] Data Processing

[2018] The server updates the user's profile based on the collected data.

[2019] Input: User operation log.

[2020] Output: The updated profile information.

[2021] Specific operation: The server analyzes the operation log and updates the profile information.

[2022] Step 5: Custom Requests for Businesses

[2023] Specific actions

[2024] The user terminal displays an interface specifically for the enterprise.

[2025] Input: Specific topic and target audience information entered by the company.

[2026] Output: Generates the request data.

[2027] Data Processing

[2028] The server receives the business's request and builds a profile of the target.

[2029] Input: Company request data.

[2030] Output: Prompt statement and custom content.

[2031] How it works: The server creates prompts for the generative AI model based on the company's request and generates custom content.

[2032] Step 6: Creator Reward Calculation

[2033] Specific actions

[2034] The server compares the generated content with the original creator's work.

[2035] Input: Generated content, original creator work.

[2036] Output: Impact score.

[2037] Data Processing

[2038] The server calculates rewards based on the degree of influence and distributes them to creators.

[2039] Input: Impact score.

[2040] Output: Determination and allocation of reward amounts.

[2041] Specific operation: The server calculates the amount based on the influence score and transfers the reward to the creator's account.

[2042] Step 7: Recognizing user emotions

[2043] Specific actions

[2044] The user terminal uses an emotion engine to recognize the user's emotional state.

[2045] Input: User's facial expression data, voice data.

[2046] Output: Emotional state data.

[2047] Data Processing

[2048] The server generates customized content based on the emotional state.

[2049] Input: Emotional state data.

[2050] Output: Customized content.

[2051] Specific operation: The server sends the prompt "Please generate the best music for when the user is sad" to the generative AI model, and then sends the generated content to the user's device.

[2052] In this way, each step in the system has clear inputs and outputs, and through data processing and calculations, it is possible to provide users and businesses with highly customized digital content.

[2053] (Application example 2)

[2054] 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."

[2055] In today's digital content consumption environment, users have diverse needs based on diverse tastes and emotions. For this reason, providing static content is difficult to fully satisfy users. There is also a lack of efficient ways for companies to generate marketing content tailored to their target audiences. Furthermore, there is a need for a system that properly recognizes the extent to which creators' works have influenced users and distributes rewards fairly.

[2056] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2057] In this invention, the server has a database for storing digital content created by creators, and includes a means for receiving requests from users, a means for generating customized content using artificial intelligence based on user profile information and past behavioral history, a means for generating custom content for companies tailored to a specific theme or target audience, a means for calculating and distributing rewards to creators based on the degree to which the generated content was influenced by the original creator's work, a means for generating customized content in real time using facial recognition technology and emotion analysis technology based on the user's emotional state, a means for adapting the generated content to the user's emotional state and providing it in real time, and a means for collecting feedback from users and using it as learning data for the system. This makes it possible to provide content optimized to the preferences and emotions of each user, thereby realizing efficient generation of marketing content for companies and fair distribution of rewards to creators.

[2058] "Creator" means an individual or entity that creates digital content as their own creation and uploads it to the Platform.

[2059] "Digital content" is any creative work stored and distributed in digital form, such as music, art, stories, videos, recipes, or designs.

[2060] A "database" is a collection of information that stores digital content and related metadata created by creators and provides it in response to requests from users and companies.

[2061] "User" means an individual or legal entity that views and uses digital content, makes requests, and receives services.

[2062] "Profile Information" refers to basic data about a user (e.g., age, gender, location) and information obtained from past behavioral history.

[2063] "Artificial intelligence" is a technology that analyzes input data and generates optimal content based on user requests.

[2064] "Customized content" refers to digital content that is optimized for a specific user, generated based on the user's profile information, past behavioral history, and real-time emotional state.

[2065] "Company" refers to a legal entity that uses custom content tailored to a specific theme or target audience as a marketing tool.

[2066] "Theme" refers to the subject or motif that a company or user uses to generate specific content.

[2067] "Target audience" refers to the viewers or users that a particular piece of content is intended for.

[2068] "Facial recognition technology" is a technology for detecting and recognizing human faces using devices such as cameras.

[2069] "Emotion analysis technology" is a technology that analyzes and determines a user's emotions from recognized faces, voices, and text.

[2070] "Feedback" refers to the evaluations and opinions that users give about the content provided, and is information that is used as learning data for the system.

[2071] This invention combines an emotion engine with a system for storing digital content created by creators and generating customized content for users and businesses. Specific embodiments of this system are described below.

[2072] 1. Creators' submissions and database creation

[2073] The server provides an interface for creators to post digital content. Creators enter metadata such as title, description, and tags along with the files they select. The server receives the files and metadata uploaded by creators and stores them in a database. It also tags them appropriately and creates an index for easy discovery by search engines. The software used for this includes a database management system (e.g., MySQL or PostgreSQL) and Python scripts for metadata processing.

[2074] 2. Processing your requests and creating customized works

[2075] The server provides a form for users to request customized digital content. Users use this form to enter their preferences and requirements. When the server receives the request from the user's device, it retrieves the user's profile information and past behavioral history from a database. Based on this information, it uses artificial intelligence (AI) to generate customized content and sends it to the user's device. This is done using machine learning libraries (e.g., TensorFlow and PyTorch).

[2076] 3. Learning based on user preferences and generating new works

[2077] The server periodically collects the user's browsing history and behavioral patterns to learn their preferences. This data is used to update the user's profile. When a new request is received, the server generates content that is more appropriate for the user based on the latest profile information. Data processing is done using large-scale data processing frameworks such as BigQuery and Hadoop.

[2078] 4. Custom requests and playlist sponsorships for companies

[2079] The server provides a dedicated interface for businesses. Businesses use this interface to request custom content tailored to a specific theme or target audience. The server receives the business's request and builds a profile of the specified theme or target audience. It uses AI to generate appropriate content and provides it to the business. It uses digital marketing tools (e.g., Google Analytics or Adobe Analytics) to see how the business uses the generated content as a marketing tool.

[2080] 5. Calculating rewards and providing market feedback to creators

[2081] The server compares the AI-generated content with the original creator's work and analyzes the degree of influence. Based on this degree of influence, rewards are calculated and distributed to the creator. It also collects market feedback on the generated work in real time and provides it to the creator. This is done using a distributed processing system (e.g., Apache Kafka or Flume).

[2082] 6. User Emotion Recognition and Content Generation

[2083] The user device is equipped with an emotion engine to recognize the user's emotional state. This emotion engine uses a camera to capture the user's face in real time and analyzes their emotions. It also analyzes the user's input text and voice to determine their emotional state and generate customized content based on that information. The software used for this includes a facial recognition framework (e.g., OpenCV), an emotion analysis library (e.g., EmotionRecognizer), and a natural language processing model (e.g., BERT).

[2084] For example, if the user has a relaxed expression while playing shuffle, the system will recommend music with a relaxing effect. An example of a prompt sentence is, "If the user's emotion is determined to be relaxed, please recommend music with a relaxing effect. For example, music in the genres 'Ambient' or 'Chillout' is recommended."

[2085] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2086] Step 1:

[2087] Creator submissions

[2088] The server provides an interface for creators to post digital content. Creators enter metadata such as title, description, and tags along with the files they select. The entered data is received by the server and stored in a database. The server tags the metadata and generates an index to make it easily discoverable by search engines.

[2089] Input: Creator-submitted digital content files and metadata

[2090] Output: Digital content and metadata stored in a database

[2091] Step 2:

[2092] Receiving a user request

[2093] The user device provides a form for requesting customized digital content. The user uses this form to input their preferences and requirements. The input request data is sent to the server, which combines it with the user's profile information and past behavior. The user information is retrieved from the database and prepared for processing the request.

[2094] Input: Preferences and conditions entered by the user into the request form

[2095] Output: Request data sent to the server

[2096] Step 3:

[2097] Customized Content Generation

[2098] The server generates customized content using a generative AI model based on the request data. Specifically, it analyzes the request data, the user's profile information, and past behavioral history, and uses machine learning libraries (e.g., TensorFlow and PyTorch) to generate optimal content based on that information. The generated content is then sent to the user's device.

[2099] Input: Request data, profile information, past behavior history

[2100] Output: Customized digital content

[2101] Step 4:

[2102] User emotion recognition

[2103] The user device uses a camera to capture the user's face in real time and analyzes their emotions using an emotion analysis engine (e.g., EmotionRecognizer). The emotion data is added to the user's profile information, which is then used as input data for the AI ​​model.

[2104] Input: Camera image

[2105] Output: User emotion data

[2106] Step 5:

[2107] Real-time content generation and delivery

[2108] The server uses a generative AI model to generate customized content in real time based on the user's profile information, including emotional data. The generated content is then sent to the user's device and provided in real time, allowing the user to instantly receive content that is appropriate for their emotional state.

[2109] Input: User emotion data, profile information

[2110] Output: Real-time customized digital content

[2111] Step 6:

[2112] Gathering user feedback

[2113] The user's device collects feedback from the user regarding the provided content (e.g., like button, comments). This feedback information is sent to the server and used as learning data for the system. This improves the accuracy of the AI ​​model and allows it to generate better customized content.

[2114] Input: User feedback

[2115] Output: Feedback data sent to the server

[2116] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2117] 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.

[2118] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2119] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2120] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2121] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2122] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2123] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2124] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2125] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2126] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2127] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2128] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2129] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2130] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2131] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2132] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2133] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2134] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2135] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2136] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2137] The following is further disclosed regarding the above embodiment.

[2138] (Claim 1)

[2139] We will establish a database to store digital content created by creators,

[2140] a means for receiving requests from users;

[2141] A means for generating customized content using artificial intelligence based on a user's profile information and past behavioral history;

[2142] A way to generate custom content for businesses tailored to specific themes and target audiences,

[2143] The system includes a means for calculating and allocating rewards to creators based on the degree of influence that the generated content received from the original creator's work.

[2144] (Claim 2)

[2145] 2. The system according to claim 1, further comprising means for learning a user's browsing history and behavioral patterns and generating new content based thereon.

[2146] (Claim 3)

[2147] 10. The system of claim 1, further comprising means for providing custom content and playlist sponsorship for businesses, utilizing the generated content as a marketing tool.

[2148] "Example 1"

[2149] (Claim 1)

[2150] We will establish a database to store digital content created by creators,

[2151] a means for receiving requests from users;

[2152] A means for generating customized content using artificial intelligence based on a user's profile information and past behavioral history;

[2153] A way to generate custom content for businesses tailored to specific themes and target audiences,

[2154] A means for calculating and allocat...

Claims

1. We will establish a database to store digital content created by creators, a means for receiving requests from users; A means for generating customized content using artificial intelligence based on a user's profile information and past behavioral history; A way to generate custom content for businesses tailored to specific themes and target audiences, The system includes a means for calculating and allocating rewards to creators based on the degree of influence that the generated content received from the original creator's work.

2. 2. The system according to claim 1, further comprising means for learning a user's browsing history and behavioral patterns and generating new content based thereon.

3. 10. The system of claim 1, further comprising means for providing custom content and playlist sponsorship for businesses, utilizing the generated content as a marketing tool.

Images