system

Abstract

We provide the system. [Solution] A method for analyzing the characteristics of a work using a generative model and proposing the optimal promotion strategy, A means of facilitating communication with fans using natural language processing technology, A means of analyzing market data and proposing sales strategies for works, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Modern artists and creators are facing the problem that effective promotion and stable financing are difficult. Especially in the midst of the generalization of marketing using SNS and digital media, specialized knowledge for appropriately conveying the charm of works is required. Also, in the fluctuating art market, the limited information regarding the price setting and sales strategy of works is also a factor threatening the sustainability of artists' activities.

Means for Solving the Problems

[0005] To solve the above problems, this invention provides a means for analyzing an artist's work using a generative model and proposing an optimal promotion strategy. Furthermore, it utilizes natural language processing to streamline two-way communication with fans and strengthen relationships. In addition, it promotes the artist's financial independence by supporting pricing and sales channel selection based on market data analysis. By providing a system that comprehensively incorporates these means, the invention supports artists in developing their activities more effectively.

[0006] A "generative model" is a machine learning algorithm used to analyze an artist's work, extract its features, and utilize them.

[0007] "Natural language processing technology" is a technology that allows computers to understand and analyze human language, and is used to support smooth communication with fans.

[0008] "Market data" refers to information about trends and demand in the art market, and is used for pricing and sales strategies of artworks through analysis.

[0009] A "promotion strategy" refers to the set of advertising and marketing activities planned to effectively communicate the appeal of a work and to increase sales and awareness of the artwork.

[0010] "Communication tools" refer to functions and processes that support dialogue between users and fans, and are used with the aim of strengthening relationships.

[0011] "Artwork data" refers to digital information about an artwork provided by an artist, including images, titles, descriptions, and other details.

[0012] "Analysis results" refer to the results of analysis obtained using generative models and natural language processing technologies, and are information used to propose promotional and sales strategies. [Brief explanation of the drawing]

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

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

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

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

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

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

[0019] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

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

[0021] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0034] This invention provides a system for artists and creators to effectively promote their work. The system consists of three components: a server, a terminal, and a user, each playing a specific role.

[0035] The server first receives artwork data sent from the user. This artwork data includes images, titles, descriptions, etc. The server analyzes this data using a generative model to extract the characteristics of the artwork. This analysis identifies the style, theme, and target audience of the artwork. For example, by analyzing the colors and themes of a digital artwork, the server may determine that the artwork belongs to a category such as "contemporary art" or "minimalism."

[0036] Next, the server automatically generates an optimal promotion strategy based on the analysis results. This promotion strategy includes how to post on social media, suggestions for appropriate hashtags, and the timing of advertising campaigns. For example, if the work has a style that is likely to be popular with younger generations, it will recommend campaigns on Instagram and TikTok.

[0037] Furthermore, the server utilizes natural language processing technology to support communication with fans. It receives comments and messages from users, analyzes them, and generates necessary responses. This allows users to quickly deepen their interactions with fans. For example, it can provide automated responses to fan questions, creating connections with more followers.

[0038] Market data is also analyzed on the server, and appropriate sales strategies are proposed to the user. Based on current market trends, the server suggests appropriate pricing and sales opportunities for the artwork, and helps the user implement a strategy based on that. For example, if a particular style of art is selling well in a specific region, the server will suggest adjusting the pricing in that market.

[0039] The terminal displays information sent from the server to the user and provides an interface that allows the user to respond interactively. The terminal is equipped with communication means for sending user input to the server, enabling smooth information exchange between the two.

[0040] This system enables artists to maximize the effectiveness of their promotions, strengthen their relationships with fans, and enhance their competitiveness in the market. The various technical means to achieve this work effectively in conjunction with the server, terminal, and user, thus fulfilling the objectives of the invention.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The user inputs their artwork data (e.g., image, title, description, etc.) into the device and sends it to the server. The device converts the input data into the appropriate format and sends a request to the server's API endpoint.

[0044] Step 2:

[0045] The server sends the received artwork data to a generative model for analysis. The generative model analyzes the artwork's characteristics (e.g., style, color, theme) and identifies the target audience and category. Based on this information, it generates an optimal promotional strategy.

[0046] Step 3:

[0047] The server sends the generated promotional strategy to the user's device. The device displays this information in the user interface. The user reviews the proposed promotional strategy and decides on marketing activities based on it.

[0048] Step 4:

[0049] The server receives comments and inquiries from fans and analyzes them using natural language processing technology. The server automatically generates an appropriate response and sends the result to the user's terminal to notify them.

[0050] Step 5:

[0051] The terminal displays a suggested response from the server to the user. The user reviews the suggestion and can either add their own comments or send the provided response as is.

[0052] Step 6:

[0053] The server periodically collects and analyzes market data. It suggests pricing and sales channels for works based on market trends and demand, and sends this information to the user's terminal. The user then adjusts their sales strategy for their works based on this information.

[0054] (Example 1)

[0055] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0056] Currently, there is insufficient support for artists and creators to effectively promote their work, particularly in the digital realm, where optimized advertising strategies and rapid, effective communication with customers are difficult. Furthermore, developing sales strategies based on market trends is complex, highlighting the need for systems that can efficiently handle these tasks.

[0057] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0058] In this invention, the server includes means for analyzing the characteristics of content using a generation algorithm and proposing an optimal advertising strategy, means for facilitating information exchange with customers using natural language processing, and means for analyzing sales data and proposing a content promotion strategy. This enables users to efficiently conduct promotional activities, strengthen relationships with customers, and execute sales strategies based on the latest market trends.

[0059] A "generative algorithm" is a computational method for analyzing the characteristics of content and extracting its features.

[0060] "Content characteristics" refer to the style, theme, color, shape, and other features of creative works such as images and text.

[0061] "Advertising strategy" refers to a promotional plan designed to effectively deliver content to a specific target audience.

[0062] "Natural language processing" is a technology that enables computers to understand, generate, and manipulate human language.

[0063] "Information exchange with customers" refers to communication between users, buyers, and fans, including question-and-answer sessions and message exchanges.

[0064] "Sales data" refers to a dataset containing information about sales and market trends.

[0065] A "sales promotion strategy" refers to an implementation plan designed to increase sales of a specific product or service.

[0066] "Communication means" refers to technical means, including devices and protocols, for sending and receiving information.

[0067] This invention is a system designed to enable artists and creators to efficiently promote their work, strengthen relationships with customers, and enhance their competitiveness in the market. The system primarily consists of three components: a server, terminals, and users, each with its own specific role.

[0068] The server receives artwork data submitted by users and analyzes the characteristics of the artwork using a generative AI model. The software used here includes image analysis algorithms and natural language processing libraries. Based on the analyzed data, the system automatically generates an optimal advertising strategy. Specifically, this could include promotional strategies such as "suggesting SNS campaigns targeted at the target audience" and "selecting effective hashtags." As an example, by inputting a prompt such as "How should I promote digital illustrations targeting young people?" into the generative AI model, an optimal promotional strategy can be obtained.

[0069] Furthermore, the server utilizes natural language processing technology to support customer communication on behalf of the user. It provides the ability to analyze user comments and messages in real time and generate appropriate responses. This enables users to respond to customers quickly and strengthen relationships with their followers.

[0070] Furthermore, the server analyzes sales data and understands market trends and consumption patterns to propose appropriate promotional strategies for content. For example, based on information such as the popularity of a particular style of art in a certain region, it becomes possible to adjust sales prices and campaign timings.

[0071] The terminal displays information sent from the server to the user, providing an interface for the user to conduct promotional activities and communicate with customers based on this information. Users can interactively manage the process by inputting information and interacting with the server via the terminal.

[0072] Users upload their work and information to this system and act according to the analytics and promotional strategies provided by the server. This allows them to more effectively increase their market exposure and expand their customer base.

[0073] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0074] Step 1:

[0075] Users input data about the works they want to promote via their devices. Specifically, they use an interface to upload image files, titles, and descriptions of their works. The input data contains information for analysis, which forms the basis for the next steps.

[0076] Step 2:

[0077] The server receives artwork data sent from the terminal. The received data becomes input for subsequent analysis. The server feeds the artwork data into a generating AI model and extracts its characteristics. Specifically, it identifies colors, shapes, and themes through image analysis, and analyzes the style and target audience of the artwork through text analysis. This process outputs the style, theme, and target user group of the artwork.

[0078] Step 3:

[0079] The server automatically generates the optimal advertising strategy based on the analysis results. The generation algorithm takes the extracted characteristics information of the works as input and performs tasks such as selecting effective social media platforms and suggesting appropriate hashtags. The output is provided to the user as a concrete promotional strategy.

[0080] Step 4:

[0081] The server utilizes natural language processing technology to support communication with customers. Comments and messages received by users through their devices are sent to the server and analyzed using natural language processing. Based on the analysis data obtained, an appropriate response is generated and provided to the user as output.

[0082] Step 5:

[0083] The server analyzes sales data to understand market trends and proposes appropriate promotional strategies to users. This process takes market information obtained from external data sources as input and suggests the optimal selling price and promotional timing for the user's work. The output is specific market strategy information.

[0084] Step 6:

[0085] The terminal displays information sent from the server to the user. Based on this information, the user can conduct specific promotional activities and interact with customers. The terminal also provides a means of communication for sending user feedback to the server, enabling two-way information exchange.

[0086] This series of processes allows users to maximize the effectiveness of their promotions, strengthen customer relationships, and maintain a competitive edge in the market.

[0087] (Application Example 1)

[0088] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0089] Artists and creators require significant time and effort in promoting and marketing their work, as well as analyzing market information and actively communicating with fans. Therefore, they seek technologies that maximize the effectiveness of their promotional strategies and foster smooth relationships with their fans.

[0090] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0091] In this invention, the server includes means for analyzing the characteristics of a work using a generative model and proposing an optimal promotional strategy, means for facilitating communication with supporters using natural language processing technology, means for analyzing market information and proposing a sales strategy for the work, and means for acquiring work data, performing work analysis using visual devices, and providing suggestions in real time. This enables artists to automate the formulation of promotional strategies and effective communication with fans, thereby enhancing the market competitiveness of their works.

[0092] A "generative model" is an algorithm that automatically learns significant features from data and has the ability to analyze those features on new data.

[0093] "Advertising strategy" refers to a plan and methods for effectively promoting a product or work, using appropriate messages and media for the right target audience.

[0094] "Natural language processing technology" is a technology that enables computers to understand, generate, and manipulate the language that humans use in everyday life, and it can be used for semantic analysis of texts and dialogue generation, among other things.

[0095] "Communication with supporters" refers to the exchange of information and opinions between artists and creators and their fans, conducted to deepen understanding of and support for their work.

[0096] "Market information" refers to data such as market trends, consumer demand, and competitive landscape related to a specific product or service, and is an important element in formulating marketing strategies.

[0097] A "sales strategy for a work" refers to the methods and plans for effectively selling a work in the market, and includes pricing, sales channel selection, and promotional activities.

[0098] "Artwork data" refers to information about an artist's or creator's work, and consists of elements such as images, titles, and descriptions.

[0099] "Visual devices" are electronic devices used to acquire, analyze, and display images and video data, and include cameras and displays.

[0100] "Providing real-time suggestions" means instantly analyzing data and providing advice and strategies based on the results.

[0101] The system for realizing this invention operates through the coordinated efforts of a server, a terminal, and a user. The server receives artwork data sent from artists and creators and analyzes it using a generative model. This analysis extracts the characteristics of the artwork, and an optimal promotional strategy is formulated. The server also has the function of analyzing comments and messages from fans using natural language processing technology and generating corresponding responses.

[0102] The server provides users with proposed promotional strategies in real time and performs detailed analysis of the artwork using visual devices. This allows users to effectively promote their artwork and adjust their sales strategies based on the information. Specifically, it operates generative models using software such as TENSORFLOW® and performs natural language processing using OpenAI® technology.

[0103] The terminal has the functionality to visually present suggestions received from the server to the user and allow the user to interact with them. This allows the artist to get an overview of the strategy and make adjustments as needed.

[0104] For example, when a young artist uploads a new abstract painting, the server analyzes its colors and composition and makes suggestions such as, "This piece is perfect for contemporary art. It would be effective to post it on Instagram between 7 PM and 9 PM on weekdays."

[0105] An example of a prompt could be, "What target audience is this work best suited for?" This prompt allows the system to suggest the customer base that would be most receptive to the created work.

[0106] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0107] Step 1:

[0108] The server receives artwork data from the user. The input includes images, titles, and descriptions. This data is saved and prepared for analysis. The output is the saved artwork data.

[0109] Step 2:

[0110] The server inputs the stored artwork data into a generating AI model and performs feature extraction. The generating AI model analyzes the colors and themes of the images to identify the style and target audience. The output is characteristic information of the analyzed artwork.

[0111] Step 3:

[0112] The server uses a generative AI model to formulate the optimal promotional strategy based on characteristic information. Inputs include the style of the work and the target audience, while output is a specific promotional plan (e.g., timing and content of social media posts).

[0113] Step 4:

[0114] The server uses natural language processing technology to receive and analyze comments and messages from users. It takes text data as input, analyzes it using an AI model, and generates appropriate response sentences as output.

[0115] Step 5:

[0116] The terminal displays promotional strategies received from the server and the results of communication with fans to the user. Through the terminal, the user can interactively view a real-time overview of the strategy and the responses.

[0117] Step 6:

[0118] The user adjusts strategies and responses as needed via the terminal interface and executes the final promotional activities. The input is the suggestions from the server, and the output is the user's promotional implementation plan.

[0119] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0120] This invention provides a more personalized service by combining a system that supports the promotion and sales of artists' and creators' works with an emotion engine that recognizes user emotions. The system consists of three components: a server, a terminal, and a user.

[0121] The server first receives artwork data (images, titles, descriptions, etc.) submitted by the user. This data is analyzed by a generative model to generate the optimal promotional strategy based on the characteristics of the artwork. In addition, an emotion engine analyzes the user's emotional state and reflects it in the promotional strategy. For example, if the user is excited, an aggressive promotional campaign can be suggested.

[0122] The server also uses an emotion engine to analyze comments and messages from fans and determine their emotional tone. Using this information, it automatically generates recommended responses to help users communicate more effectively with their fans. For example, if a fan leaves a comment expressing joy, the server will recommend a positive response acknowledging their praise.

[0123] Furthermore, the server collects and analyzes market data and proposes market strategies that take into account the user's emotional state. For example, when a user is calm, it can recommend a strategy that prioritizes long-term profits. In this way, by utilizing the emotion engine, it becomes possible to provide services that nuancely reflect the user's emotions and achieve higher results.

[0124] The device displays information sent from the server to the user, allowing them to review promotional strategies and fan communication. Users can also send feedback to the server via the device to update the sentiment engine's analysis.

[0125] This system, by incorporating an emotion engine, provides a highly personalized user experience that cannot be obtained through conventional promotional activities. Therefore, this invention aims to maximize the effectiveness of artists' promotional activities and build stronger relationships with fans.

[0126] The following describes the processing flow.

[0127] Step 1:

[0128] The user inputs their artwork data (e.g., image, title, description) into their device and sends it to the server. The device then formats the data into the appropriate format and communicates it to the server's API.

[0129] Step 2:

[0130] The server analyzes the received artwork data using a generative model to extract the artwork's characteristics. This model recognizes the artwork's style and theme, and generates data to identify the target audience.

[0131] Step 3:

[0132] The server uses an emotion engine to analyze the user's emotions. Based on user input and past interaction data, it evaluates the user's current emotional state and reflects this in the promotional strategy. For example, if it determines that the user is in a challenging mood, it will suggest an aggressive campaign approach.

[0133] Step 4:

[0134] The server sends optimized information—the generated promotional strategy and the user's emotional state—to the terminal. The terminal displays this information in its user interface, allowing the user to confirm the strategy.

[0135] Step 5:

[0136] Users can review the promotional strategy through their devices and make adjustments as needed. They can also send their feedback from their devices to the server for future analysis.

[0137] Step 6:

[0138] The server receives comments from fans and analyzes them using an emotion engine. It determines the emotional tone of the comments and automatically generates appropriate replies. This information is sent to the user's device, where the user can review it and add their own response.

[0139] Step 7:

[0140] The server collects market data and uses an emotion engine to develop sales strategies tailored to the user's emotional state. This strategic information is sent to the terminal, where the user reviews it and uses it to implement the sales strategy.

[0141] This process allows the system to support promotional and sales activities that take user emotions into account, resulting in more effective marketing.

[0142] (Example 2)

[0143] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0144] In today's digital content market, it is crucial for artists and creators to effectively promote their work and communicate smoothly with consumers. However, traditional advertising strategies and sales plans have struggled to adequately reflect the characteristics of individual works and the emotional state of creators, and also have difficulty efficiently tailoring responses in communication with fans. This invention aims to solve these problems and provide more personalized promotional activities and communication methods.

[0145] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0146] This invention includes a server that analyzes the characteristics of digital content using a generation algorithm and creates an optimal advertising strategy based on that analysis; a server that uses natural language processing technology to streamline communication with enthusiasts; and a server that analyzes statistical information and constructs a sales plan for digital content. This enables highly personalized promotional activities based on the characteristics of individual works and the emotional state of the creators.

[0147] A "generation algorithm" is a set of calculation procedures that analyze the characteristics of digital content and automatically generate the optimal advertising strategy accordingly.

[0148] "Natural language processing technology" is a technology that allows computers to understand and analyze human language, and it is a means of efficiently communicating information with enthusiasts.

[0149] "Statistical information" refers to market data, specifically numerical data used to develop sales plans for digital content.

[0150] An "emotion analysis device" is a technology that analyzes a user's emotional state in real time and applies that analysis to advertising strategies.

[0151] "Response generation means" refers to technology that enables personalized information transmission tailored to the user's emotional state.

[0152] The embodiment of this invention utilizes advanced generative algorithms and natural language processing technologies to streamline the promotion of digital content and related communications. This system mainly consists of a server, terminals, and users, with each entity performing a specific function.

[0153] The server analyzes the features of received digital content using generative AI models. Specifically, machine learning frameworks such as TensorFlow and PyTorch are used, and the optimal advertising strategy is created based on the results. Furthermore, to act as an emotion analyzer, natural language processing techniques are used to evaluate the user's emotional state in detail. For natural language processing, models such as BERT and GPT are utilized to analyze text data and feedback from the user and generate emotion-based responses.

[0154] The terminal presents information obtained from the server to the user, allowing the user to view and confirm promotional strategies and responses. Furthermore, it functions as an interface for sending user feedback to the server. This makes it possible to improve the user experience through the terminal.

[0155] Users directly interact with promotional strategies provided by the server using their devices, communicating with their fans. User feedback is analyzed by the server and used to improve the next update of the generation algorithm.

[0156] A concrete example would be an artist selling artwork online using this system. When the artist uploads a new, colorful painting to the server, the generative AI model analyzes its features and recommends advertising messages that emphasize bright colors. If sentiment analysis reveals the artist is currently relaxed, it can then suggest a long-term strategy.

[0157] Examples of prompt messages include the following:

[0158] "Please generate a promotional message for the next piece I will upload. The data is 'Abstract painting with bright colors.' My current mood is relaxed."

[0159] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0160] Step 1:

[0161] The server receives digital content data (images, titles, descriptions, etc.) from the user. The input is the user's artwork data, and upon receiving it, the server checks the data's integrity. If the reception is successful, the server notifies the user that the data has been received. This process confirms that the data is ready for use in the next analysis step.

[0162] Step 2:

[0163] The server inputs the received artwork data into a generating AI model and analyzes its features. The input is the data received in step 1. The server uses a machine learning framework (e.g., TensorFlow, PyTorch) to extract features such as the artwork's colors and composition. As a result of the analysis, it outputs basic data for an optimal promotion strategy. This analysis concretizes the characteristics of the artwork, allowing the process to proceed to the next step.

[0164] Step 3:

[0165] The server analyzes the user's emotional state using an emotion analysis device. The input consists of user-provided feedback and text data. The server uses a natural language processing model (e.g., BERT, GPT) to extract emotional data from this input. The output is the user's emotional state, which is then reflected in the promotional strategy. This step enables adaptation based on the user's emotions.

[0166] Step 4:

[0167] The server generates an optimal promotional strategy based on the characteristics of the work and the user's emotional state. The input is the output from steps 2 and 3. The server combines this data to create advertising messages optimized for each individual work. The output is a specific promotional message, which is then delivered to the user. This process enables the implementation of personalized strategies.

[0168] Step 5:

[0169] The terminal displays the promotional strategy provided by the server to the user. The input is the output from step 4. The terminal displays this on the screen, and the user can refer to it and confirm its contents. This step achieves the visualization and use of the promotional strategy by the user.

[0170] Step 6:

[0171] Users send feedback and additional data to the server via their devices. The input consists of user feedback and new instructions. The server receives this feedback and adjusts and updates its analysis results and promotional strategies. This cycle allows the system to continuously improve, enabling more effective promotions.

[0172] (Application Example 2)

[0173] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0174] In today's world, the works of artists and creators are incredibly diverse, requiring appropriate promotional strategies. However, conventional promotional methods often lack personalized approaches that respond to user emotions. As a result, advertising effectiveness is diminished, leading to decreased user engagement.

[0175] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0176] In this invention, the server includes means for analyzing the characteristics of a work using a generative model and proposing an optimal promotion strategy, means for facilitating communication with fans using natural language processing technology, means for analyzing market data and proposing a sales strategy for the work, means for recognizing user emotions and personalizing advertisements, and means for analyzing emotions in real time and dynamically adjusting advertisement content. This makes it possible to optimize advertising and promotion strategies to suit user emotions.

[0177] A "generative model" is an algorithm that learns the characteristics of given data and automatically generates new data and strategies.

[0178] A "promotion strategy" is a method of planning how to approach a target market with the aim of promoting the sale of a product or service.

[0179] "Natural language processing technology" is a technology that uses computers to process human language and understand intentions and emotions.

[0180] "Market data" refers to information and statistics about a specific market, and is used to understand the competitive situation and trends within that market.

[0181] "Recognizing user emotions" is the process of analyzing a user's psychological state and identifying their current emotions.

[0182] "Personalizing ads" refers to customizing ad content to deliver the most relevant and effective ad content to specific users.

[0183] "Real-time emotion analysis" means instantly analyzing the user's emotional data to understand their current emotional state.

[0184] "Dynamically adjusting ad content" refers to the process of instantly changing the message and visuals of the ads presented to users according to their current psychological state and preferences.

[0185] To implement this invention, a system is constructed using specific hardware and software. The server receives artwork data and analyzes it using a generative AI model. In this process, the characteristics of the artwork are captured, and an optimal promotional strategy is formulated. This generative AI model receives visual and textual information of the artwork as input and extracts patterns useful for marketing.

[0186] Furthermore, the server uses natural language processing techniques to analyze comments and messages from fans. This allows it to provide advice and automated responses to help users communicate smoothly with their fans. This natural language processing technique utilizes libraries such as TensorFlow.

[0187] The server also collects market data and uses this data to analyze and optimize sales strategies for the products. Simultaneously, it leverages an emotion engine to understand the emotional states of users and fans, and personalize promotional and advertising content. OpenCV and other emotion analysis tools are used for this emotion recognition.

[0188] The terminal displays information sent from the server, allowing users to review promotional strategies and communication content. Users can also send feedback from the terminal to the server, which can be used to update the system's overall sentiment analysis. This feedback feature enhances the system's adaptability.

[0189] Specific examples of this system include suggesting promotional campaigns that emphasize a fun atmosphere when the user is expressing joy, and adopting a strategy that prioritizes providing detailed information when the user is calm.

[0190] An example of a prompt message is, "If the user's emotion is 'joyful,' please present ads that are related to an overall positive message."

[0191] In this way, the system aims to provide personalized and effective promotion and advertising strategies by utilizing emotion recognition and generative AI models.

[0192] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0193] Step 1:

[0194] The server receives artwork data sent by the user. This artwork data includes images, titles, and descriptions, and is received as input.

[0195] Step 2:

[0196] The server inputs the received artwork data into a generating AI model, which analyzes the characteristics of the artwork. The AI ​​model recognizes patterns and features in the data and extracts elements suitable for promotion. The results of this analysis are then output.

[0197] Step 3:

[0198] The server develops the optimal promotional strategy based on the promotional elements output from the generated AI model. This involves determining how to approach the target audience.

[0199] Step 4:

[0200] The server uses natural language processing technology to analyze comments and messages from fans. It receives text data as input and identifies the emotions expressed. This processing then outputs a response and communication strategy.

[0201] Step 5:

[0202] The server uses an emotion engine to analyze the user's emotional state. It uses real-time data obtained from the camera and microphone as input to identify the user's emotions. This allows for the determination of emotion-based actions.

[0203] Step 6:

[0204] The server dynamically adjusts and personalizes the ad content based on the sentiment analysis results. This ensures that ads best suited to the user's current psychological state are displayed.

[0205] Step 7:

[0206] The device displays promotional strategies and advertisements received from the server to the user. Based on this information, the user checks the progress of the promotion and sends feedback to the server as needed.

[0207] Step 8:

[0208] User feedback is received by the server, and data analysis is performed again to update promotion and advertising strategies. This ensures that the system is always operating in an optimized state.

[0209] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0210] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0211] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0212] [Second Embodiment]

[0213] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0214] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0215] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0216] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0217] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0218] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0219] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0220] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0221] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0222] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0223] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0224] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0225] This invention provides a system for artists and creators to effectively promote their work. The system consists of three components: a server, a terminal, and a user, each playing a specific role.

[0226] The server first receives artwork data sent from the user. This artwork data includes images, titles, descriptions, etc. The server analyzes this data using a generative model to extract the characteristics of the artwork. This analysis identifies the style, theme, and target audience of the artwork. For example, by analyzing the colors and themes of a digital artwork, the server may determine that the artwork belongs to a category such as "contemporary art" or "minimalism."

[0227] Next, the server automatically generates an optimal promotion strategy based on the analysis results. This promotion strategy includes how to post on social media, suggestions for appropriate hashtags, and the timing of advertising campaigns. For example, if the work has a style that is likely to be popular with younger generations, it will recommend campaigns on Instagram and TikTok.

[0228] Furthermore, the server utilizes natural language processing technology to support communication with fans. It receives comments and messages from users, analyzes them, and generates necessary responses. This allows users to quickly deepen their interactions with fans. For example, it can provide automated responses to fan questions, creating connections with more followers.

[0229] Market data is also analyzed on the server, and appropriate sales strategies are proposed to the user. Based on current market trends, the server suggests appropriate pricing and sales opportunities for the artwork, and helps the user implement a strategy based on that. For example, if a particular style of art is selling well in a specific region, the server will suggest adjusting the pricing in that market.

[0230] The terminal displays information sent from the server to the user and provides an interface that allows the user to respond interactively. The terminal is equipped with communication means for sending user input to the server, enabling smooth information exchange between the two.

[0231] This system enables artists to maximize the effectiveness of their promotions, strengthen their relationships with fans, and enhance their competitiveness in the market. The various technical means to achieve this work effectively in conjunction with the server, terminal, and user, thus fulfilling the objectives of the invention.

[0232] The following describes the processing flow.

[0233] Step 1:

[0234] The user inputs their artwork data (e.g., image, title, description, etc.) into the device and sends it to the server. The device converts the input data into the appropriate format and sends a request to the server's API endpoint.

[0235] Step 2:

[0236] The server sends the received artwork data to a generative model for analysis. The generative model analyzes the artwork's characteristics (e.g., style, color, theme) and identifies the target audience and category. Based on this information, it generates an optimal promotional strategy.

[0237] Step 3:

[0238] The server sends the generated promotional strategy to the user's device. The device displays this information in the user interface. The user reviews the proposed promotional strategy and decides on marketing activities based on it.

[0239] Step 4:

[0240] The server receives comments and inquiries from fans and analyzes them using natural language processing technology. The server automatically generates an appropriate response and sends the result to the user's terminal to notify them.

[0241] Step 5:

[0242] The terminal displays a suggested response from the server to the user. The user reviews the suggestion and can either add their own comments or send the provided response as is.

[0243] Step 6:

[0244] The server periodically collects and analyzes market data. It suggests pricing and sales channels for works based on market trends and demand, and sends this information to the user's terminal. The user then adjusts their sales strategy for their works based on this information.

[0245] (Example 1)

[0246] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0247] Currently, there is insufficient support for artists and creators to effectively promote their work, particularly in the digital realm, where optimized advertising strategies and rapid, effective communication with customers are difficult. Furthermore, developing sales strategies based on market trends is complex, highlighting the need for systems that can efficiently handle these tasks.

[0248] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0249] In this invention, the server includes means for analyzing the characteristics of content using a generation algorithm and proposing an optimal advertising strategy, means for facilitating information exchange with customers using natural language processing, and means for analyzing sales data and proposing a content promotion strategy. This enables users to efficiently conduct promotional activities, strengthen relationships with customers, and execute sales strategies based on the latest market trends.

[0250] A "generative algorithm" is a computational method for analyzing the characteristics of content and extracting its features.

[0251] "Content characteristics" refer to the style, theme, color, shape, and other features of creative works such as images and text.

[0252] "Advertising strategy" refers to a promotional plan designed to effectively deliver content to a specific target audience.

[0253] "Natural language processing" is a technology that enables computers to understand, generate, and manipulate human language.

[0254] "Information exchange with customers" refers to communication between users, buyers, and fans, including question-and-answer sessions and message exchanges.

[0255] "Sales data" refers to a dataset containing information about sales and market trends.

[0256] A "sales promotion strategy" refers to an implementation plan designed to increase sales of a specific product or service.

[0257] "Communication means" refers to technical means, including devices and protocols, for sending and receiving information.

[0258] This invention is a system designed to enable artists and creators to efficiently promote their work, strengthen relationships with customers, and enhance their competitiveness in the market. The system primarily consists of three components: a server, terminals, and users, each with its own specific role.

[0259] The server receives artwork data submitted by users and analyzes the characteristics of the artwork using a generative AI model. The software used here includes image analysis algorithms and natural language processing libraries. Based on the analyzed data, the system automatically generates an optimal advertising strategy. Specifically, this could include promotional strategies such as "suggesting SNS campaigns targeted at the target audience" and "selecting effective hashtags." As an example, by inputting a prompt such as "How should I promote digital illustrations targeting young people?" into the generative AI model, an optimal promotional strategy can be obtained.

[0260] Furthermore, the server utilizes natural language processing technology to support customer communication on behalf of the user. It provides the ability to analyze user comments and messages in real time and generate appropriate responses. This enables users to respond to customers quickly and strengthen relationships with their followers.

[0261] Furthermore, the server analyzes sales data and understands market trends and consumption patterns to propose appropriate promotional strategies for content. For example, based on information such as the popularity of a particular style of art in a certain region, it becomes possible to adjust sales prices and campaign timings.

[0262] The terminal displays information sent from the server to the user, providing an interface for the user to conduct promotional activities and communicate with customers based on this information. Users can interactively manage the process by inputting information and interacting with the server via the terminal.

[0263] Users upload their work and information to this system and act according to the analytics and promotional strategies provided by the server. This allows them to more effectively increase their market exposure and expand their customer base.

[0264] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0265] Step 1:

[0266] Users input data about the works they want to promote via their devices. Specifically, they use an interface to upload image files, titles, and descriptions of their works. The input data contains information for analysis, which forms the basis for the next steps.

[0267] Step 2:

[0268] The server receives artwork data sent from the terminal. The received data becomes input for subsequent analysis. The server feeds the artwork data into a generating AI model and extracts its characteristics. Specifically, it identifies colors, shapes, and themes through image analysis, and analyzes the style and target audience of the artwork through text analysis. This process outputs the style, theme, and target user group of the artwork.

[0269] Step 3:

[0270] The server automatically generates the optimal advertising strategy based on the analysis results. The generation algorithm takes the extracted characteristics information of the works as input and performs tasks such as selecting effective social media platforms and suggesting appropriate hashtags. The output is provided to the user as a concrete promotional strategy.

[0271] Step 4:

[0272] The server utilizes natural language processing technology to support communication with customers. Comments and messages received by users through their devices are sent to the server and analyzed using natural language processing. Based on the analysis data obtained, an appropriate response is generated and provided to the user as output.

[0273] Step 5:

[0274] The server analyzes sales data to understand market trends and proposes appropriate promotional strategies to users. This process takes market information obtained from external data sources as input and suggests the optimal selling price and promotional timing for the user's work. The output is specific market strategy information.

[0275] Step 6:

[0276] The terminal displays information sent from the server to the user. Based on this information, the user can conduct specific promotional activities and interact with customers. The terminal also provides a means of communication for sending user feedback to the server, enabling two-way information exchange.

[0277] This series of processes allows users to maximize the effectiveness of their promotions, strengthen customer relationships, and maintain a competitive edge in the market.

[0278] (Application Example 1)

[0279] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0280] Artists and creators require significant time and effort in promoting and marketing their work, as well as analyzing market information and actively communicating with fans. Therefore, they seek technologies that maximize the effectiveness of their promotional strategies and foster smooth relationships with their fans.

[0281] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0282] In this invention, the server includes means for analyzing the characteristics of a work using a generative model and proposing an optimal promotion strategy, means for facilitating communication with supporters using natural language processing technology, means for analyzing market information and proposing a sales strategy for the work, and means for acquiring work data, performing work analysis using visual devices, and providing proposals in real time. As a result, the artist can automate the formulation of promotion strategies and effective communication with fans, thereby enhancing the market competitiveness of the work.

[0283] A "generative model" is an algorithm that automatically learns significant features from data and has the ability to analyze those features for new data.

[0284] A "promotion strategy" is a plan or method for effectively promoting a product or work, which uses appropriate messages and media suitable for the target audience.

[0285] "Natural language processing technology" is a technology that enables a computer to understand, generate, and manipulate the language that humans use in daily life, and is capable of semantic analysis of sentences, dialogue generation, etc.

[0286] "Communication with supporters" refers to the exchange of information and opinions between artists or creators and the fans of their works, which is carried out to deepen the understanding and support of the works.

[0287] "Market information" is data such as market trends, consumer needs, and competitive situations related to specific products or services, and is an important element for formulating marketing strategies.

[0288] A "sales strategy for the work" is a method or plan for effectively selling a work in the market, which includes price setting, selection of sales channels, promotion activities, etc.

[0289] "Work data" is information related to the works of artists or creators, and is composed of elements such as images, titles, and descriptions.

[0290] "Visual devices" are electronic devices used to acquire, analyze, and display images and video data, and include cameras and displays.

[0291] "Providing real-time suggestions" means instantly analyzing data and providing advice and strategies based on the results.

[0292] The system for realizing this invention operates through the coordinated efforts of a server, a terminal, and a user. The server receives artwork data sent from artists and creators and analyzes it using a generative model. This analysis extracts the characteristics of the artwork, and an optimal promotional strategy is formulated. The server also has the function of analyzing comments and messages from fans using natural language processing technology and generating corresponding responses.

[0293] The server provides users with proposed promotional strategies in real time and performs detailed analysis of the artwork using visual devices. This allows users to effectively promote their artwork and adjust their sales strategies based on the information. Specifically, it operates generative models using software such as TensorFlow and performs natural language processing using OpenAI technology.

[0294] The terminal has the functionality to visually present suggestions received from the server to the user and allow the user to interact with them. This allows the artist to get an overview of the strategy and make adjustments as needed.

[0295] For example, when a young artist uploads a new abstract painting, the server analyzes its colors and composition and makes suggestions such as, "This piece is perfect for contemporary art. It would be effective to post it on Instagram between 7 PM and 9 PM on weekdays."

[0296] An example of a prompt could be, "What target audience is this work best suited for?" This prompt allows the system to suggest the customer base that would be most receptive to the created work.

[0297] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0298] Step 1:

[0299] The server receives artwork data from the user. The input includes images, titles, and descriptions. This data is saved and prepared for analysis. The output is the saved artwork data.

[0300] Step 2:

[0301] The server inputs the stored artwork data into a generating AI model and performs feature extraction. The generating AI model analyzes the colors and themes of the images to identify the style and target audience. The output is characteristic information of the analyzed artwork.

[0302] Step 3:

[0303] The server uses a generative AI model to formulate the optimal promotional strategy based on characteristic information. Inputs include the style of the work and the target audience, while output is a specific promotional plan (e.g., timing and content of social media posts).

[0304] Step 4:

[0305] The server uses natural language processing technology to receive and analyze comments and messages from users. It takes text data as input, analyzes it using an AI model, and generates appropriate response sentences as output.

[0306] Step 5:

[0307] The terminal displays to the user the promotion strategy received from the server and the communication results with fans. Through the terminal, the user can interactively confirm a real-time overview of the strategy and responses.

[0308] Step 6:

[0309] The user adjusts the strategy and replies as needed via the terminal interface and executes the final promotion activities. The input is the proposed content from the server, and the output is the user's promotion implementation plan.

[0310] Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion recognition model 59 and perform specific processing using the user's emotions.

[0311] This invention provides a more personalized service by combining an emotion engine that recognizes the user's emotions with a system for promoting and selling the works of artists and creators. The system consists of three entities: a server, a terminal, and a user.

[0312] The server first receives the work data (such as images, titles, descriptions, etc.) sent by the user. This data is analyzed by a generation model to generate an optimal promotion strategy based on the characteristics of the work. In addition, the emotion engine analyzes the user's emotional state and reflects it in the promotion strategy. For example, when the user is excited, a positive promotional campaign can be proposed.

[0313] The server also analyzes the comments and messages from fans using the emotion engine to determine the emotional tone. Using this result, it automatically generates recommended responses so that the user can communicate more effectively with fans. As a specific example, when a fan leaves a comment showing a happy emotion, the server recommends a positive reply to respond with praise.

[0314] Furthermore, the server collects and analyzes market data and proposes market strategies that take into account the user's emotional state. For example, when a user is calm, it can recommend a strategy that prioritizes long-term profits. In this way, by utilizing the emotion engine, it becomes possible to provide services that nuancely reflect the user's emotions and achieve higher results.

[0315] The device displays information sent from the server to the user, allowing them to review promotional strategies and fan communication. Users can also send feedback to the server via the device to update the sentiment engine's analysis.

[0316] This system, by incorporating an emotion engine, provides a highly personalized user experience that cannot be obtained through conventional promotional activities. Therefore, this invention aims to maximize the effectiveness of artists' promotional activities and build stronger relationships with fans.

[0317] The following describes the processing flow.

[0318] Step 1:

[0319] The user inputs their artwork data (e.g., image, title, description) into their device and sends it to the server. The device then formats the data into the appropriate format and communicates it to the server's API.

[0320] Step 2:

[0321] The server analyzes the received artwork data using a generative model to extract the artwork's characteristics. This model recognizes the artwork's style and theme, and generates data to identify the target audience.

[0322] Step 3:

[0323] The server uses an emotion engine to analyze the user's emotions. Based on user input and past interaction data, it evaluates the user's current emotional state and reflects this in the promotional strategy. For example, if it determines that the user is in a challenging mood, it will suggest an aggressive campaign approach.

[0324] Step 4:

[0325] The server sends optimized information—the generated promotional strategy and the user's emotional state—to the terminal. The terminal displays this information in its user interface, allowing the user to confirm the strategy.

[0326] Step 5:

[0327] Users can review the promotional strategy through their devices and make adjustments as needed. They can also send their feedback from their devices to the server for future analysis.

[0328] Step 6:

[0329] The server receives comments from fans and analyzes them using an emotion engine. It determines the emotional tone of the comments and automatically generates appropriate replies. This information is sent to the user's device, where the user can review it and add their own response.

[0330] Step 7:

[0331] The server collects market data and uses an emotion engine to develop sales strategies tailored to the user's emotional state. This strategic information is sent to the terminal, where the user reviews it and uses it to implement the sales strategy.

[0332] This process allows the system to support promotional and sales activities that take user emotions into account, resulting in more effective marketing.

[0333] (Example 2)

[0334] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0335] In today's digital content market, it is crucial for artists and creators to effectively promote their work and communicate smoothly with consumers. However, traditional advertising strategies and sales plans have struggled to adequately reflect the characteristics of individual works and the emotional state of creators, and also have difficulty efficiently tailoring responses in communication with fans. This invention aims to solve these problems and provide more personalized promotional activities and communication methods.

[0336] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0337] This invention includes a server that analyzes the characteristics of digital content using a generation algorithm and creates an optimal advertising strategy based on that analysis; a server that uses natural language processing technology to streamline communication with enthusiasts; and a server that analyzes statistical information and constructs a sales plan for digital content. This enables highly personalized promotional activities based on the characteristics of individual works and the emotional state of the creators.

[0338] A "generation algorithm" is a set of calculation procedures that analyze the characteristics of digital content and automatically generate the optimal advertising strategy accordingly.

[0339] "Natural language processing technology" is a technology that allows computers to understand and analyze human language, and it is a means of efficiently communicating information with enthusiasts.

[0340] "Statistical information" refers to market data, specifically numerical data used to develop sales plans for digital content.

[0341] An "emotion analysis device" is a technology that analyzes a user's emotional state in real time and applies that analysis to advertising strategies.

[0342] "Response generation means" refers to technology that enables personalized information transmission tailored to the user's emotional state.

[0343] The embodiment of this invention utilizes advanced generative algorithms and natural language processing technologies to streamline the promotion of digital content and related communications. This system mainly consists of a server, terminals, and users, with each entity performing a specific function.

[0344] The server analyzes the features of received digital content using generative AI models. Specifically, machine learning frameworks such as TensorFlow and PyTorch are used, and the optimal advertising strategy is created based on the results. Furthermore, to act as an emotion analyzer, natural language processing techniques are used to evaluate the user's emotional state in detail. For natural language processing, models such as BERT and GPT are utilized to analyze text data and feedback from the user and generate emotion-based responses.

[0345] The terminal presents information obtained from the server to the user, allowing the user to view and confirm promotional strategies and responses. Furthermore, it functions as an interface for sending user feedback to the server. This makes it possible to improve the user experience through the terminal.

[0346] Users directly interact with promotional strategies provided by the server using their devices, communicating with their fans. User feedback is analyzed by the server and used to improve the next update of the generation algorithm.

[0347] A concrete example would be an artist selling artwork online using this system. When the artist uploads a new, colorful painting to the server, the generative AI model analyzes its features and recommends advertising messages that emphasize bright colors. If sentiment analysis reveals the artist is currently relaxed, it can then suggest a long-term strategy.

[0348] Examples of prompt messages include the following:

[0349] "Please generate a promotional message for the next piece I will upload. The data is 'Abstract painting with bright colors.' My current mood is relaxed."

[0350] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0351] Step 1:

[0352] The server receives digital content data (images, titles, descriptions, etc.) from the user. The input is the user's artwork data, and upon receiving it, the server checks the data's integrity. If the reception is successful, the server notifies the user that the data has been received. This process confirms that the data is ready for use in the next analysis step.

[0353] Step 2:

[0354] The server inputs the received artwork data into a generating AI model and analyzes its features. The input is the data received in step 1. The server uses a machine learning framework (e.g., TensorFlow, PyTorch) to extract features such as the artwork's colors and composition. As a result of the analysis, it outputs basic data for an optimal promotion strategy. This analysis concretizes the characteristics of the artwork, allowing the process to proceed to the next step.

[0355] Step 3:

[0356] The server analyzes the user's emotional state using an emotion analysis device. The input consists of user-provided feedback and text data. The server uses a natural language processing model (e.g., BERT, GPT) to extract emotional data from this input. The output is the user's emotional state, which is then reflected in the promotional strategy. This step enables adaptation based on the user's emotions.

[0357] Step 4:

[0358] The server generates an optimal promotional strategy based on the characteristics of the work and the user's emotional state. The input is the output from steps 2 and 3. The server combines this data to create advertising messages optimized for each individual work. The output is a specific promotional message, which is then delivered to the user. This process enables the implementation of personalized strategies.

[0359] Step 5:

[0360] The terminal displays the promotional strategy provided by the server to the user. The input is the output from step 4. The terminal displays this on the screen, and the user can refer to it and confirm its contents. This step achieves the visualization and use of the promotional strategy by the user.

[0361] Step 6:

[0362] Users send feedback and additional data to the server via their devices. The input consists of user feedback and new instructions. The server receives this feedback and adjusts and updates its analysis results and promotional strategies. This cycle allows the system to continuously improve, enabling more effective promotions.

[0363] (Application Example 2)

[0364] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0365] In today's world, the works of artists and creators are incredibly diverse, requiring appropriate promotional strategies. However, conventional promotional methods often lack personalized approaches that respond to user emotions. As a result, advertising effectiveness is diminished, leading to decreased user engagement.

[0366] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0367] In this invention, the server includes means for analyzing the characteristics of a work using a generative model and proposing an optimal promotion strategy, means for facilitating communication with fans using natural language processing technology, means for analyzing market data and proposing a sales strategy for the work, means for recognizing user emotions and personalizing advertisements, and means for analyzing emotions in real time and dynamically adjusting advertisement content. This makes it possible to optimize advertising and promotion strategies to suit user emotions.

[0368] A "generative model" is an algorithm that learns the characteristics of given data and automatically generates new data and strategies.

[0369] A "promotion strategy" is a method of planning how to approach a target market with the aim of promoting the sale of a product or service.

[0370] "Natural language processing technology" is a technology that uses computers to process human language and understand intentions and emotions.

[0371] "Market data" refers to information and statistics about a specific market, and is used to understand the competitive situation and trends within that market.

[0372] "Recognizing user emotions" is the process of analyzing a user's psychological state and identifying their current emotions.

[0373] "Personalizing ads" refers to customizing ad content to deliver the most relevant and effective ad content to specific users.

[0374] "Real-time emotion analysis" means instantly analyzing the user's emotional data to understand their current emotional state.

[0375] "Dynamically adjusting ad content" refers to the process of instantly changing the message and visuals of the ads presented to users according to their current psychological state and preferences.

[0376] To implement this invention, a system is constructed using specific hardware and software. The server receives artwork data and analyzes it using a generative AI model. In this process, the characteristics of the artwork are captured, and an optimal promotional strategy is formulated. This generative AI model receives visual and textual information of the artwork as input and extracts patterns useful for marketing.

[0377] Furthermore, the server uses natural language processing techniques to analyze comments and messages from fans. This allows it to provide advice and automated responses to help users communicate smoothly with their fans. This natural language processing technique utilizes libraries such as TensorFlow.

[0378] The server also collects market data and uses this data to analyze and optimize sales strategies for the products. Simultaneously, it leverages an emotion engine to understand the emotional states of users and fans, and personalize promotional and advertising content. OpenCV and other emotion analysis tools are used for this emotion recognition.

[0379] The terminal displays information sent from the server, allowing users to review promotional strategies and communication content. Users can also send feedback from the terminal to the server, which can be used to update the system's overall sentiment analysis. This feedback feature enhances the system's adaptability.

[0380] Specific examples of this system include suggesting promotional campaigns that emphasize a fun atmosphere when the user is expressing joy, and adopting a strategy that prioritizes providing detailed information when the user is calm.

[0381] An example of a prompt message is, "If the user's emotion is 'joyful,' please present ads that are related to an overall positive message."

[0382] In this way, the system aims to provide personalized and effective promotion and advertising strategies by utilizing emotion recognition and generative AI models.

[0383] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0384] Step 1:

[0385] The server receives artwork data sent by the user. This artwork data includes images, titles, and descriptions, and is received as input.

[0386] Step 2:

[0387] The server inputs the received artwork data into a generating AI model, which analyzes the characteristics of the artwork. The AI ​​model recognizes patterns and features in the data and extracts elements suitable for promotion. The results of this analysis are then output.

[0388] Step 3:

[0389] The server develops the optimal promotional strategy based on the promotional elements output from the generated AI model. This involves determining how to approach the target audience.

[0390] Step 4:

[0391] The server uses natural language processing technology to analyze comments and messages from fans. It receives text data as input and identifies the emotions expressed. This processing then outputs a response and communication strategy.

[0392] Step 5:

[0393] The server uses an emotion engine to analyze the user's emotional state. It uses real-time data obtained from the camera and microphone as input to identify the user's emotions. This allows for the determination of emotion-based actions.

[0394] Step 6:

[0395] The server dynamically adjusts and personalizes the ad content based on the sentiment analysis results. This ensures that ads best suited to the user's current psychological state are displayed.

[0396] Step 7:

[0397] The device displays promotional strategies and advertisements received from the server to the user. Based on this information, the user checks the progress of the promotion and sends feedback to the server as needed.

[0398] Step 8:

[0399] User feedback is received by the server, and data analysis is performed again to update promotion and advertising strategies. This ensures that the system is always operating in an optimized state.

[0400] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0401] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0402] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0403] [Third Embodiment]

[0404] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0405] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0406] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0407] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0408] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0409] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0410] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0411] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0412] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0413] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0414] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0415] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0416] This invention provides a system for artists and creators to effectively promote their work. The system consists of three components: a server, a terminal, and a user, each playing a specific role.

[0417] The server first receives artwork data sent from the user. This artwork data includes images, titles, descriptions, etc. The server analyzes this data using a generative model to extract the characteristics of the artwork. This analysis identifies the style, theme, and target audience of the artwork. For example, by analyzing the colors and themes of a digital artwork, the server may determine that the artwork belongs to a category such as "contemporary art" or "minimalism."

[0418] Next, the server automatically generates an optimal promotion strategy based on the analysis results. This promotion strategy includes how to post on social media, suggestions for appropriate hashtags, and the timing of advertising campaigns. For example, if the work has a style that is likely to be popular with younger generations, it will recommend campaigns on Instagram and TikTok.

[0419] Furthermore, the server utilizes natural language processing technology to support communication with fans. It receives comments and messages from users, analyzes them, and generates necessary responses. This allows users to quickly deepen their interactions with fans. For example, it can provide automated responses to fan questions, creating connections with more followers.

[0420] Market data is also analyzed on the server, and appropriate sales strategies are proposed to the user. Based on current market trends, the server suggests appropriate pricing and sales opportunities for the artwork, and helps the user implement a strategy based on that. For example, if a particular style of art is selling well in a specific region, the server will suggest adjusting the pricing in that market.

[0421] The terminal displays information sent from the server to the user and provides an interface that allows the user to respond interactively. The terminal is equipped with communication means for sending user input to the server, enabling smooth information exchange between the two.

[0422] This system enables artists to maximize the effectiveness of their promotions, strengthen their relationships with fans, and enhance their competitiveness in the market. The various technical means to achieve this work effectively in conjunction with the server, terminal, and user, thus fulfilling the objectives of the invention.

[0423] The following describes the processing flow.

[0424] Step 1:

[0425] The user inputs their artwork data (e.g., image, title, description, etc.) into the device and sends it to the server. The device converts the input data into the appropriate format and sends a request to the server's API endpoint.

[0426] Step 2:

[0427] The server sends the received artwork data to a generative model for analysis. The generative model analyzes the artwork's characteristics (e.g., style, color, theme) and identifies the target audience and category. Based on this information, it generates an optimal promotional strategy.

[0428] Step 3:

[0429] The server sends the generated promotional strategy to the user's device. The device displays this information in the user interface. The user reviews the proposed promotional strategy and decides on marketing activities based on it.

[0430] Step 4:

[0431] The server receives comments and inquiries from fans and analyzes them using natural language processing technology. The server automatically generates an appropriate response and sends the result to the user's terminal to notify them.

[0432] Step 5:

[0433] The terminal displays a suggested response from the server to the user. The user reviews the suggestion and can either add their own comments or send the provided response as is.

[0434] Step 6:

[0435] The server periodically collects and analyzes market data. It suggests pricing and sales channels for works based on market trends and demand, and sends this information to the user's terminal. The user then adjusts their sales strategy for their works based on this information.

[0436] (Example 1)

[0437] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0438] Currently, there is insufficient support for artists and creators to effectively promote their work, particularly in the digital realm, where optimized advertising strategies and rapid, effective communication with customers are difficult. Furthermore, developing sales strategies based on market trends is complex, highlighting the need for systems that can efficiently handle these tasks.

[0439] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0440] In this invention, the server includes means for analyzing the characteristics of content using a generation algorithm and proposing an optimal advertising strategy, means for facilitating information exchange with customers using natural language processing, and means for analyzing sales data and proposing a content promotion strategy. This enables users to efficiently conduct promotional activities, strengthen relationships with customers, and execute sales strategies based on the latest market trends.

[0441] A "generative algorithm" is a computational method for analyzing the characteristics of content and extracting its features.

[0442] "Content characteristics" refer to the style, theme, color, shape, and other features of creative works such as images and text.

[0443] "Advertising strategy" refers to a promotional plan designed to effectively deliver content to a specific target audience.

[0444] "Natural language processing" is a technology that enables computers to understand, generate, and manipulate human language.

[0445] "Information exchange with customers" refers to communication between users, buyers, and fans, including question-and-answer sessions and message exchanges.

[0446] "Sales data" refers to a dataset containing information about sales and market trends.

[0447] A "sales promotion strategy" refers to an implementation plan designed to increase sales of a specific product or service.

[0448] "Communication means" refers to technical means, including devices and protocols, for sending and receiving information.

[0449] This invention is a system designed to enable artists and creators to efficiently promote their work, strengthen relationships with customers, and enhance their competitiveness in the market. The system primarily consists of three components: a server, terminals, and users, each with its own specific role.

[0450] The server receives artwork data submitted by users and analyzes the characteristics of the artwork using a generative AI model. The software used here includes image analysis algorithms and natural language processing libraries. Based on the analyzed data, the system automatically generates an optimal advertising strategy. Specifically, this could include promotional strategies such as "suggesting SNS campaigns targeted at the target audience" and "selecting effective hashtags." As an example, by inputting a prompt such as "How should I promote digital illustrations targeting young people?" into the generative AI model, an optimal promotional strategy can be obtained.

[0451] Furthermore, the server utilizes natural language processing technology to support customer communication on behalf of the user. It provides the ability to analyze user comments and messages in real time and generate appropriate responses. This enables users to respond to customers quickly and strengthen relationships with their followers.

[0452] Furthermore, the server analyzes sales data and understands market trends and consumption patterns to propose appropriate promotional strategies for content. For example, based on information such as the popularity of a particular style of art in a certain region, it becomes possible to adjust sales prices and campaign timings.

[0453] The terminal displays information sent from the server to the user, providing an interface for the user to conduct promotional activities and communicate with customers based on this information. Users can interactively manage the process by inputting information and interacting with the server via the terminal.

[0454] Users upload their work and information to this system and act according to the analytics and promotional strategies provided by the server. This allows them to more effectively increase their market exposure and expand their customer base.

[0455] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0456] Step 1:

[0457] Users input data about the works they want to promote via their devices. Specifically, they use an interface to upload image files, titles, and descriptions of their works. The input data contains information for analysis, which forms the basis for the next steps.

[0458] Step 2:

[0459] The server receives artwork data sent from the terminal. The received data becomes input for subsequent analysis. The server feeds the artwork data into a generating AI model and extracts its characteristics. Specifically, it identifies colors, shapes, and themes through image analysis, and analyzes the style and target audience of the artwork through text analysis. This process outputs the style, theme, and target user group of the artwork.

[0460] Step 3:

[0461] The server automatically generates the optimal advertising strategy based on the analysis results. The generation algorithm takes the extracted characteristics information of the works as input and performs tasks such as selecting effective social media platforms and suggesting appropriate hashtags. The output is provided to the user as a concrete promotional strategy.

[0462] Step 4:

[0463] The server utilizes natural language processing technology to support communication with customers. Comments and messages received by users through their devices are sent to the server and analyzed using natural language processing. Based on the analysis data obtained, an appropriate response is generated and provided to the user as output.

[0464] Step 5:

[0465] The server analyzes sales data to understand market trends and proposes appropriate promotional strategies to users. This process takes market information obtained from external data sources as input and suggests the optimal selling price and promotional timing for the user's work. The output is specific market strategy information.

[0466] Step 6:

[0467] The terminal displays information sent from the server to the user. Based on this information, the user can conduct specific promotional activities and interact with customers. The terminal also provides a means of communication for sending user feedback to the server, enabling two-way information exchange.

[0468] This series of processes allows users to maximize the effectiveness of their promotions, strengthen customer relationships, and maintain a competitive edge in the market.

[0469] (Application Example 1)

[0470] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0471] Artists and creators require significant time and effort in promoting and marketing their work, as well as analyzing market information and actively communicating with fans. Therefore, they seek technologies that maximize the effectiveness of their promotional strategies and foster smooth relationships with their fans.

[0472] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0473] In this invention, the server includes means for analyzing the characteristics of a work using a generative model and proposing an optimal promotional strategy, means for facilitating communication with supporters using natural language processing technology, means for analyzing market information and proposing a sales strategy for the work, and means for acquiring work data, performing work analysis using visual devices, and providing suggestions in real time. This enables artists to automate the formulation of promotional strategies and effective communication with fans, thereby enhancing the market competitiveness of their works.

[0474] A "generative model" is an algorithm that automatically learns significant features from data and has the ability to analyze those features on new data.

[0475] "Advertising strategy" refers to a plan and methods for effectively promoting a product or work, using appropriate messages and media for the right target audience.

[0476] "Natural language processing technology" is a technology that enables computers to understand, generate, and manipulate the language that humans use in everyday life, and it can be used for semantic analysis of texts and dialogue generation, among other things.

[0477] "Communication with supporters" refers to the exchange of information and opinions between artists and creators and their fans, conducted to deepen understanding of and support for their work.

[0478] "Market information" refers to data such as market trends, consumer demand, and competitive landscape related to a specific product or service, and is an important element in formulating marketing strategies.

[0479] A "sales strategy for a work" refers to the methods and plans for effectively selling a work in the market, and includes pricing, sales channel selection, and promotional activities.

[0480] "Artwork data" refers to information about an artist's or creator's work, and consists of elements such as images, titles, and descriptions.

[0481] "Visual devices" are electronic devices used to acquire, analyze, and display images and video data, and include cameras and displays.

[0482] "Providing real-time suggestions" means instantly analyzing data and providing advice and strategies based on the results.

[0483] The system for realizing this invention operates through the coordinated efforts of a server, a terminal, and a user. The server receives artwork data sent from artists and creators and analyzes it using a generative model. This analysis extracts the characteristics of the artwork, and an optimal promotional strategy is formulated. The server also has the function of analyzing comments and messages from fans using natural language processing technology and generating corresponding responses.

[0484] The server provides users with proposed promotional strategies in real time and performs detailed analysis of the artwork using visual devices. This allows users to effectively promote their artwork and adjust their sales strategies based on the information. Specifically, it operates generative models using software such as TensorFlow and performs natural language processing using OpenAI technology.

[0485] The terminal has the functionality to visually present suggestions received from the server to the user and allow the user to interact with them. This allows the artist to get an overview of the strategy and make adjustments as needed.

[0486] For example, when a young artist uploads a new abstract painting, the server analyzes its colors and composition and makes suggestions such as, "This piece is perfect for contemporary art. It would be effective to post it on Instagram between 7 PM and 9 PM on weekdays."

[0487] An example of a prompt could be, "What target audience is this work best suited for?" This prompt allows the system to suggest the customer base that would be most receptive to the created work.

[0488] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0489] Step 1:

[0490] The server receives artwork data from the user. The input includes images, titles, and descriptions. This data is saved and prepared for analysis. The output is the saved artwork data.

[0491] Step 2:

[0492] The server inputs the stored artwork data into a generating AI model and performs feature extraction. The generating AI model analyzes the colors and themes of the images to identify the style and target audience. The output is characteristic information of the analyzed artwork.

[0493] Step 3:

[0494] The server uses a generative AI model to formulate the optimal promotional strategy based on characteristic information. Inputs include the style of the work and the target audience, while output is a specific promotional plan (e.g., timing and content of social media posts).

[0495] Step 4:

[0496] The server uses natural language processing technology to receive and analyze comments and messages from users. It takes text data as input, analyzes it using an AI model, and generates appropriate response sentences as output.

[0497] Step 5:

[0498] The terminal displays promotional strategies received from the server and the results of communication with fans to the user. Through the terminal, the user can interactively view a real-time overview of the strategy and the responses.

[0499] Step 6:

[0500] The user adjusts strategies and responses as needed via the terminal interface and executes the final promotional activities. The input is the suggestions from the server, and the output is the user's promotional implementation plan.

[0501] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0502] This invention provides a more personalized service by combining a system that supports the promotion and sales of artists' and creators' works with an emotion engine that recognizes user emotions. The system consists of three components: a server, a terminal, and a user.

[0503] The server first receives artwork data (images, titles, descriptions, etc.) submitted by the user. This data is analyzed by a generative model to generate the optimal promotional strategy based on the characteristics of the artwork. In addition, an emotion engine analyzes the user's emotional state and reflects it in the promotional strategy. For example, if the user is excited, an aggressive promotional campaign can be suggested.

[0504] The server also uses an emotion engine to analyze comments and messages from fans and determine their emotional tone. Using this information, it automatically generates recommended responses to help users communicate more effectively with their fans. For example, if a fan leaves a comment expressing joy, the server will recommend a positive response acknowledging their praise.

[0505] Furthermore, the server collects and analyzes market data and proposes market strategies that take into account the user's emotional state. For example, when a user is calm, it can recommend a strategy that prioritizes long-term profits. In this way, by utilizing the emotion engine, it becomes possible to provide services that nuancely reflect the user's emotions and achieve higher results.

[0506] The device displays information sent from the server to the user, allowing them to review promotional strategies and fan communication. Users can also send feedback to the server via the device to update the sentiment engine's analysis.

[0507] This system, by incorporating an emotion engine, provides a highly personalized user experience that cannot be obtained through conventional promotional activities. Therefore, this invention aims to maximize the effectiveness of artists' promotional activities and build stronger relationships with fans.

[0508] The following describes the processing flow.

[0509] Step 1:

[0510] The user inputs their artwork data (e.g., image, title, description) into their device and sends it to the server. The device then formats the data into the appropriate format and communicates it to the server's API.

[0511] Step 2:

[0512] The server analyzes the received artwork data using a generative model to extract the artwork's characteristics. This model recognizes the artwork's style and theme, and generates data to identify the target audience.

[0513] Step 3:

[0514] The server uses an emotion engine to analyze the user's emotions. Based on user input and past interaction data, it evaluates the user's current emotional state and reflects this in the promotional strategy. For example, if it determines that the user is in a challenging mood, it will suggest an aggressive campaign approach.

[0515] Step 4:

[0516] The server sends optimized information—the generated promotional strategy and the user's emotional state—to the terminal. The terminal displays this information in its user interface, allowing the user to confirm the strategy.

[0517] Step 5:

[0518] Users can review the promotional strategy through their devices and make adjustments as needed. They can also send their feedback from their devices to the server for future analysis.

[0519] Step 6:

[0520] The server receives comments from fans and analyzes them using an emotion engine. It determines the emotional tone of the comments and automatically generates appropriate replies. This information is sent to the user's device, where the user can review it and add their own response.

[0521] Step 7:

[0522] The server collects market data and uses an emotion engine to develop sales strategies tailored to the user's emotional state. This strategic information is sent to the terminal, where the user reviews it and uses it to implement the sales strategy.

[0523] This process allows the system to support promotional and sales activities that take user emotions into account, resulting in more effective marketing.

[0524] (Example 2)

[0525] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0526] In today's digital content market, it is crucial for artists and creators to effectively promote their work and communicate smoothly with consumers. However, traditional advertising strategies and sales plans have struggled to adequately reflect the characteristics of individual works and the emotional state of creators, and also have difficulty efficiently tailoring responses in communication with fans. This invention aims to solve these problems and provide more personalized promotional activities and communication methods.

[0527] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0528] This invention includes a server that analyzes the characteristics of digital content using a generation algorithm and creates an optimal advertising strategy based on that analysis; a server that uses natural language processing technology to streamline communication with enthusiasts; and a server that analyzes statistical information and constructs a sales plan for digital content. This enables highly personalized promotional activities based on the characteristics of individual works and the emotional state of the creators.

[0529] A "generation algorithm" is a set of calculation procedures that analyze the characteristics of digital content and automatically generate the optimal advertising strategy accordingly.

[0530] "Natural language processing technology" is a technology that allows computers to understand and analyze human language, and it is a means of efficiently communicating information with enthusiasts.

[0531] "Statistical information" refers to market data, specifically numerical data used to develop sales plans for digital content.

[0532] An "emotion analysis device" is a technology that analyzes a user's emotional state in real time and applies that analysis to advertising strategies.

[0533] "Response generation means" refers to technology that enables personalized information transmission tailored to the user's emotional state.

[0534] The embodiment of this invention utilizes advanced generative algorithms and natural language processing technologies to streamline the promotion of digital content and related communications. This system mainly consists of a server, terminals, and users, with each entity performing a specific function.

[0535] The server analyzes the features of received digital content using generative AI models. Specifically, machine learning frameworks such as TensorFlow and PyTorch are used, and the optimal advertising strategy is created based on the results. Furthermore, to act as an emotion analyzer, natural language processing techniques are used to evaluate the user's emotional state in detail. For natural language processing, models such as BERT and GPT are utilized to analyze text data and feedback from the user and generate emotion-based responses.

[0536] The terminal presents information obtained from the server to the user, allowing the user to view and confirm promotional strategies and responses. Furthermore, it functions as an interface for sending user feedback to the server. This makes it possible to improve the user experience through the terminal.

[0537] Users directly interact with promotional strategies provided by the server using their devices, communicating with their fans. User feedback is analyzed by the server and used to improve the next update of the generation algorithm.

[0538] A concrete example would be an artist selling artwork online using this system. When the artist uploads a new, colorful painting to the server, the generative AI model analyzes its features and recommends advertising messages that emphasize bright colors. If sentiment analysis reveals the artist is currently relaxed, it can then suggest a long-term strategy.

[0539] Examples of prompt messages include the following:

[0540] "Please generate a promotional message for the next piece I will upload. The data is 'Abstract painting with bright colors.' My current mood is relaxed."

[0541] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0542] Step 1:

[0543] The server receives digital content data (images, titles, descriptions, etc.) from the user. The input is the user's artwork data, and upon receiving it, the server checks the data's integrity. If the reception is successful, the server notifies the user that the data has been received. This process confirms that the data is ready for use in the next analysis step.

[0544] Step 2:

[0545] The server inputs the received artwork data into a generating AI model and analyzes its features. The input is the data received in step 1. The server uses a machine learning framework (e.g., TensorFlow, PyTorch) to extract features such as the artwork's colors and composition. As a result of the analysis, it outputs basic data for an optimal promotion strategy. This analysis concretizes the characteristics of the artwork, allowing the process to proceed to the next step.

[0546] Step 3:

[0547] The server analyzes the user's emotional state using an emotion analysis device. The input consists of user-provided feedback and text data. The server uses a natural language processing model (e.g., BERT, GPT) to extract emotional data from this input. The output is the user's emotional state, which is then reflected in the promotional strategy. This step enables adaptation based on the user's emotions.

[0548] Step 4:

[0549] The server generates an optimal promotional strategy based on the characteristics of the work and the user's emotional state. The input is the output from steps 2 and 3. The server combines this data to create advertising messages optimized for each individual work. The output is a specific promotional message, which is then delivered to the user. This process enables the implementation of personalized strategies.

[0550] Step 5:

[0551] The terminal displays the promotional strategy provided by the server to the user. The input is the output from step 4. The terminal displays this on the screen, and the user can refer to it and confirm its contents. This step achieves the visualization and use of the promotional strategy by the user.

[0552] Step 6:

[0553] Users send feedback and additional data to the server via their devices. The input consists of user feedback and new instructions. The server receives this feedback and adjusts and updates its analysis results and promotional strategies. This cycle allows the system to continuously improve, enabling more effective promotions.

[0554] (Application Example 2)

[0555] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0556] In today's world, the works of artists and creators are incredibly diverse, requiring appropriate promotional strategies. However, conventional promotional methods often lack personalized approaches that respond to user emotions. As a result, advertising effectiveness is diminished, leading to decreased user engagement.

[0557] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0558] In this invention, the server includes means for analyzing the characteristics of a work using a generative model and proposing an optimal promotion strategy, means for facilitating communication with fans using natural language processing technology, means for analyzing market data and proposing a sales strategy for the work, means for recognizing user emotions and personalizing advertisements, and means for analyzing emotions in real time and dynamically adjusting advertisement content. This makes it possible to optimize advertising and promotion strategies to suit user emotions.

[0559] A "generative model" is an algorithm that learns the characteristics of given data and automatically generates new data and strategies.

[0560] A "promotion strategy" is a method of planning how to approach a target market with the aim of promoting the sale of a product or service.

[0561] "Natural language processing technology" is a technology that uses computers to process human language and understand intentions and emotions.

[0562] "Market data" refers to information and statistics about a specific market, and is used to understand the competitive situation and trends within that market.

[0563] "Recognizing user emotions" is the process of analyzing a user's psychological state and identifying their current emotions.

[0564] "Personalizing ads" refers to customizing ad content to deliver the most relevant and effective ad content to specific users.

[0565] "Real-time emotion analysis" means instantly analyzing the user's emotional data to understand their current emotional state.

[0566] "Dynamically adjusting ad content" refers to the process of instantly changing the message and visuals of the ads presented to users according to their current psychological state and preferences.

[0567] To implement this invention, a system is constructed using specific hardware and software. The server receives artwork data and analyzes it using a generative AI model. In this process, the characteristics of the artwork are captured, and an optimal promotional strategy is formulated. This generative AI model receives visual and textual information of the artwork as input and extracts patterns useful for marketing.

[0568] Furthermore, the server uses natural language processing techniques to analyze comments and messages from fans. This allows it to provide advice and automated responses to help users communicate smoothly with their fans. This natural language processing technique utilizes libraries such as TensorFlow.

[0569] The server also collects market data and uses this data to analyze and optimize sales strategies for the products. Simultaneously, it leverages an emotion engine to understand the emotional states of users and fans, and personalize promotional and advertising content. OpenCV and other emotion analysis tools are used for this emotion recognition.

[0570] The terminal displays information sent from the server, allowing users to review promotional strategies and communication content. Users can also send feedback from the terminal to the server, which can be used to update the system's overall sentiment analysis. This feedback feature enhances the system's adaptability.

[0571] Specific examples of this system include suggesting promotional campaigns that emphasize a fun atmosphere when the user is expressing joy, and adopting a strategy that prioritizes providing detailed information when the user is calm.

[0572] An example of a prompt message is, "If the user's emotion is 'joyful,' please present ads that are related to an overall positive message."

[0573] In this way, the system aims to provide personalized and effective promotion and advertising strategies by utilizing emotion recognition and generative AI models.

[0574] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0575] Step 1:

[0576] The server receives artwork data sent by the user. This artwork data includes images, titles, and descriptions, and is received as input.

[0577] Step 2:

[0578] The server inputs the received artwork data into a generating AI model, which analyzes the characteristics of the artwork. The AI ​​model recognizes patterns and features in the data and extracts elements suitable for promotion. The results of this analysis are then output.

[0579] Step 3:

[0580] The server develops the optimal promotional strategy based on the promotional elements output from the generated AI model. This involves determining how to approach the target audience.

[0581] Step 4:

[0582] The server uses natural language processing technology to analyze comments and messages from fans. It receives text data as input and identifies the emotions expressed. This processing then outputs a response and communication strategy.

[0583] Step 5:

[0584] The server uses an emotion engine to analyze the user's emotional state. It uses real-time data obtained from the camera and microphone as input to identify the user's emotions. This allows for the determination of emotion-based actions.

[0585] Step 6:

[0586] The server dynamically adjusts and personalizes the ad content based on the sentiment analysis results. This ensures that ads best suited to the user's current psychological state are displayed.

[0587] Step 7:

[0588] The device displays promotional strategies and advertisements received from the server to the user. Based on this information, the user checks the progress of the promotion and sends feedback to the server as needed.

[0589] Step 8:

[0590] User feedback is received by the server, and data analysis is performed again to update promotion and advertising strategies. This ensures that the system is always operating in an optimized state.

[0591] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0592] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0593] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0594] [Fourth Embodiment]

[0595] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0596] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0597] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0598] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0599] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0600] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0601] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0602] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0603] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0604] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0605] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0606] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0607] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0608] This invention provides a system for artists and creators to effectively promote their work. The system consists of three components: a server, a terminal, and a user, each playing a specific role.

[0609] The server first receives artwork data sent from the user. This artwork data includes images, titles, descriptions, etc. The server analyzes this data using a generative model to extract the characteristics of the artwork. This analysis identifies the style, theme, and target audience of the artwork. For example, by analyzing the colors and themes of a digital artwork, the server may determine that the artwork belongs to a category such as "contemporary art" or "minimalism."

[0610] Next, the server automatically generates an optimal promotion strategy based on the analysis results. This promotion strategy includes how to post on social media, suggestions for appropriate hashtags, and the timing of advertising campaigns. For example, if the work has a style that is likely to be popular with younger generations, it will recommend campaigns on Instagram and TikTok.

[0611] Furthermore, the server utilizes natural language processing technology to support communication with fans. It receives comments and messages from users, analyzes them, and generates necessary responses. This allows users to quickly deepen their interactions with fans. For example, it can provide automated responses to fan questions, creating connections with more followers.

[0612] Market data is also analyzed on the server, and appropriate sales strategies are proposed to the user. Based on current market trends, the server suggests appropriate pricing and sales opportunities for the artwork, and helps the user implement a strategy based on that. For example, if a particular style of art is selling well in a specific region, the server will suggest adjusting the pricing in that market.

[0613] The terminal displays information sent from the server to the user and provides an interface that allows the user to respond interactively. The terminal is equipped with communication means for sending user input to the server, enabling smooth information exchange between the two.

[0614] This system enables artists to maximize the effectiveness of their promotions, strengthen their relationships with fans, and enhance their competitiveness in the market. The various technical means to achieve this work effectively in conjunction with the server, terminal, and user, thus fulfilling the objectives of the invention.

[0615] The following describes the processing flow.

[0616] Step 1:

[0617] The user inputs their artwork data (e.g., image, title, description, etc.) into the device and sends it to the server. The device converts the input data into the appropriate format and sends a request to the server's API endpoint.

[0618] Step 2:

[0619] The server sends the received artwork data to a generative model for analysis. The generative model analyzes the artwork's characteristics (e.g., style, color, theme) and identifies the target audience and category. Based on this information, it generates an optimal promotional strategy.

[0620] Step 3:

[0621] The server sends the generated promotional strategy to the user's device. The device displays this information in the user interface. The user reviews the proposed promotional strategy and decides on marketing activities based on it.

[0622] Step 4:

[0623] The server receives comments and inquiries from fans and analyzes them using natural language processing technology. The server automatically generates an appropriate response and sends the result to the user's terminal to notify them.

[0624] Step 5:

[0625] The terminal displays a suggested response from the server to the user. The user reviews the suggestion and can either add their own comments or send the provided response as is.

[0626] Step 6:

[0627] The server periodically collects and analyzes market data. It suggests pricing and sales channels for works based on market trends and demand, and sends this information to the user's terminal. The user then adjusts their sales strategy for their works based on this information.

[0628] (Example 1)

[0629] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0630] Currently, there is insufficient support for artists and creators to effectively promote their work, particularly in the digital realm, where optimized advertising strategies and rapid, effective communication with customers are difficult. Furthermore, developing sales strategies based on market trends is complex, highlighting the need for systems that can efficiently handle these tasks.

[0631] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0632] In this invention, the server includes means for analyzing the characteristics of content using a generation algorithm and proposing an optimal advertising strategy, means for facilitating information exchange with customers using natural language processing, and means for analyzing sales data and proposing a content promotion strategy. This enables users to efficiently conduct promotional activities, strengthen relationships with customers, and execute sales strategies based on the latest market trends.

[0633] A "generative algorithm" is a computational method for analyzing the characteristics of content and extracting its features.

[0634] "Content characteristics" refer to the style, theme, color, shape, and other features of creative works such as images and text.

[0635] "Advertising strategy" refers to a promotional plan designed to effectively deliver content to a specific target audience.

[0636] "Natural language processing" is a technology that enables computers to understand, generate, and manipulate human language.

[0637] "Information exchange with customers" refers to communication between users, buyers, and fans, including question-and-answer sessions and message exchanges.

[0638] "Sales data" refers to a dataset containing information about sales and market trends.

[0639] A "sales promotion strategy" refers to an implementation plan designed to increase sales of a specific product or service.

[0640] "Communication means" refers to technical means, including devices and protocols, for sending and receiving information.

[0641] This invention is a system designed to enable artists and creators to efficiently promote their work, strengthen relationships with customers, and enhance their competitiveness in the market. The system primarily consists of three components: a server, terminals, and users, each with its own specific role.

[0642] The server receives artwork data submitted by users and analyzes the characteristics of the artwork using a generative AI model. The software used here includes image analysis algorithms and natural language processing libraries. Based on the analyzed data, the system automatically generates an optimal advertising strategy. Specifically, this could include promotional strategies such as "suggesting SNS campaigns targeted at the target audience" and "selecting effective hashtags." As an example, by inputting a prompt such as "How should I promote digital illustrations targeting young people?" into the generative AI model, an optimal promotional strategy can be obtained.

[0643] Furthermore, the server utilizes natural language processing technology to support customer communication on behalf of the user. It provides the ability to analyze user comments and messages in real time and generate appropriate responses. This enables users to respond to customers quickly and strengthen relationships with their followers.

[0644] Furthermore, the server analyzes sales data and understands market trends and consumption patterns to propose appropriate promotional strategies for content. For example, based on information such as the popularity of a particular style of art in a certain region, it becomes possible to adjust sales prices and campaign timings.

[0645] The terminal displays information sent from the server to the user, providing an interface for the user to conduct promotional activities and communicate with customers based on this information. Users can interactively manage the process by inputting information and interacting with the server via the terminal.

[0646] Users upload their work and information to this system and act according to the analytics and promotional strategies provided by the server. This allows them to more effectively increase their market exposure and expand their customer base.

[0647] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0648] Step 1:

[0649] Users input data about the works they want to promote via their devices. Specifically, they use an interface to upload image files, titles, and descriptions of their works. The input data contains information for analysis, which forms the basis for the next steps.

[0650] Step 2:

[0651] The server receives artwork data sent from the terminal. The received data becomes input for subsequent analysis. The server feeds the artwork data into a generating AI model and extracts its characteristics. Specifically, it identifies colors, shapes, and themes through image analysis, and analyzes the style and target audience of the artwork through text analysis. This process outputs the style, theme, and target user group of the artwork.

[0652] Step 3:

[0653] The server automatically generates the optimal advertising strategy based on the analysis results. The generation algorithm takes the extracted characteristics information of the works as input and performs tasks such as selecting effective social media platforms and suggesting appropriate hashtags. The output is provided to the user as a concrete promotional strategy.

[0654] Step 4:

[0655] The server utilizes natural language processing technology to support communication with customers. Comments and messages received by users through their devices are sent to the server and analyzed using natural language processing. Based on the analysis data obtained, an appropriate response is generated and provided to the user as output.

[0656] Step 5:

[0657] The server analyzes sales data to understand market trends and proposes appropriate promotional strategies to users. This process takes market information obtained from external data sources as input and suggests the optimal selling price and promotional timing for the user's work. The output is specific market strategy information.

[0658] Step 6:

[0659] The terminal displays information sent from the server to the user. Based on this information, the user can conduct specific promotional activities and interact with customers. The terminal also provides a means of communication for sending user feedback to the server, enabling two-way information exchange.

[0660] This series of processes allows users to maximize the effectiveness of their promotions, strengthen customer relationships, and maintain a competitive edge in the market.

[0661] (Application Example 1)

[0662] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0663] Artists and creators require significant time and effort in promoting and marketing their work, as well as analyzing market information and actively communicating with fans. Therefore, they seek technologies that maximize the effectiveness of their promotional strategies and foster smooth relationships with their fans.

[0664] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0665] In this invention, the server includes means for analyzing the characteristics of a work using a generative model and proposing an optimal promotional strategy, means for facilitating communication with supporters using natural language processing technology, means for analyzing market information and proposing a sales strategy for the work, and means for acquiring work data, performing work analysis using visual devices, and providing suggestions in real time. This enables artists to automate the formulation of promotional strategies and effective communication with fans, thereby enhancing the market competitiveness of their works.

[0666] A "generative model" is an algorithm that automatically learns significant features from data and has the ability to analyze those features on new data.

[0667] "Advertising strategy" refers to a plan and methods for effectively promoting a product or work, using appropriate messages and media for the right target audience.

[0668] "Natural language processing technology" is a technology that enables computers to understand, generate, and manipulate the language that humans use in everyday life, and it can be used for semantic analysis of texts and dialogue generation, among other things.

[0669] "Communication with supporters" refers to the exchange of information and opinions between artists and creators and their fans, conducted to deepen understanding of and support for their work.

[0670] "Market information" refers to data such as market trends, consumer demand, and competitive landscape related to a specific product or service, and is an important element in formulating marketing strategies.

[0671] A "sales strategy for a work" refers to the methods and plans for effectively selling a work in the market, and includes pricing, sales channel selection, and promotional activities.

[0672] "Artwork data" refers to information about an artist's or creator's work, and consists of elements such as images, titles, and descriptions.

[0673] "Visual devices" are electronic devices used to acquire, analyze, and display images and video data, and include cameras and displays.

[0674] "Providing real-time suggestions" means instantly analyzing data and providing advice and strategies based on the results.

[0675] The system for realizing this invention operates through the coordinated efforts of a server, a terminal, and a user. The server receives artwork data sent from artists and creators and analyzes it using a generative model. This analysis extracts the characteristics of the artwork, and an optimal promotional strategy is formulated. The server also has the function of analyzing comments and messages from fans using natural language processing technology and generating corresponding responses.

[0676] The server provides users with proposed promotional strategies in real time and performs detailed analysis of the artwork using visual devices. This allows users to effectively promote their artwork and adjust their sales strategies based on the information. Specifically, it operates generative models using software such as TensorFlow and performs natural language processing using OpenAI technology.

[0677] The terminal has the functionality to visually present suggestions received from the server to the user and allow the user to interact with them. This allows the artist to get an overview of the strategy and make adjustments as needed.

[0678] For example, when a young artist uploads a new abstract painting, the server analyzes its colors and composition and makes suggestions such as, "This piece is perfect for contemporary art. It would be effective to post it on Instagram between 7 PM and 9 PM on weekdays."

[0679] An example of a prompt could be, "What target audience is this work best suited for?" This prompt allows the system to suggest the customer base that would be most receptive to the created work.

[0680] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0681] Step 1:

[0682] The server receives artwork data from the user. The input includes images, titles, and descriptions. This data is saved and prepared for analysis. The output is the saved artwork data.

[0683] Step 2:

[0684] The server inputs the stored artwork data into a generating AI model and performs feature extraction. The generating AI model analyzes the colors and themes of the images to identify the style and target audience. The output is characteristic information of the analyzed artwork.

[0685] Step 3:

[0686] The server uses a generative AI model to formulate the optimal promotional strategy based on characteristic information. Inputs include the style of the work and the target audience, while output is a specific promotional plan (e.g., timing and content of social media posts).

[0687] Step 4:

[0688] The server uses natural language processing technology to receive and analyze comments and messages from users. It takes text data as input, analyzes it using an AI model, and generates appropriate response sentences as output.

[0689] Step 5:

[0690] The terminal displays promotional strategies received from the server and the results of communication with fans to the user. Through the terminal, the user can interactively view a real-time overview of the strategy and the responses.

[0691] Step 6:

[0692] The user adjusts strategies and responses as needed via the terminal interface and executes the final promotional activities. The input is the suggestions from the server, and the output is the user's promotional implementation plan.

[0693] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0694] This invention provides a more personalized service by combining a system that supports the promotion and sales of artists' and creators' works with an emotion engine that recognizes user emotions. The system consists of three components: a server, a terminal, and a user.

[0695] The server first receives artwork data (images, titles, descriptions, etc.) submitted by the user. This data is analyzed by a generative model to generate the optimal promotional strategy based on the characteristics of the artwork. In addition, an emotion engine analyzes the user's emotional state and reflects it in the promotional strategy. For example, if the user is excited, an aggressive promotional campaign can be suggested.

[0696] The server also uses an emotion engine to analyze comments and messages from fans and determine their emotional tone. Using this information, it automatically generates recommended responses to help users communicate more effectively with their fans. For example, if a fan leaves a comment expressing joy, the server will recommend a positive response acknowledging their praise.

[0697] Furthermore, the server collects and analyzes market data and proposes market strategies that take into account the user's emotional state. For example, when a user is calm, it can recommend a strategy that prioritizes long-term profits. In this way, by utilizing the emotion engine, it becomes possible to provide services that nuancely reflect the user's emotions and achieve higher results.

[0698] The device displays information sent from the server to the user, allowing them to review promotional strategies and fan communication. Users can also send feedback to the server via the device to update the sentiment engine's analysis.

[0699] This system, by incorporating an emotion engine, provides a highly personalized user experience that cannot be obtained through conventional promotional activities. Therefore, this invention aims to maximize the effectiveness of artists' promotional activities and build stronger relationships with fans.

[0700] The following describes the processing flow.

[0701] Step 1:

[0702] The user inputs their artwork data (e.g., image, title, description) into their device and sends it to the server. The device then formats the data into the appropriate format and communicates it to the server's API.

[0703] Step 2:

[0704] The server analyzes the received artwork data using a generative model to extract the artwork's characteristics. This model recognizes the artwork's style and theme, and generates data to identify the target audience.

[0705] Step 3:

[0706] The server uses an emotion engine to analyze the user's emotions. Based on user input and past interaction data, it evaluates the user's current emotional state and reflects this in the promotional strategy. For example, if it determines that the user is in a challenging mood, it will suggest an aggressive campaign approach.

[0707] Step 4:

[0708] The server sends optimized information—the generated promotional strategy and the user's emotional state—to the terminal. The terminal displays this information in its user interface, allowing the user to confirm the strategy.

[0709] Step 5:

[0710] Users can review the promotional strategy through their devices and make adjustments as needed. They can also send their feedback from their devices to the server for future analysis.

[0711] Step 6:

[0712] The server receives comments from fans and analyzes them using an emotion engine. It determines the emotional tone of the comments and automatically generates appropriate replies. This information is sent to the user's device, where the user can review it and add their own response.

[0713] Step 7:

[0714] The server collects market data and uses an emotion engine to develop sales strategies tailored to the user's emotional state. This strategic information is sent to the terminal, where the user reviews it and uses it to implement the sales strategy.

[0715] This process allows the system to support promotional and sales activities that take user emotions into account, resulting in more effective marketing.

[0716] (Example 2)

[0717] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0718] In today's digital content market, it is crucial for artists and creators to effectively promote their work and communicate smoothly with consumers. However, traditional advertising strategies and sales plans have struggled to adequately reflect the characteristics of individual works and the emotional state of creators, and also have difficulty efficiently tailoring responses in communication with fans. This invention aims to solve these problems and provide more personalized promotional activities and communication methods.

[0719] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0720] This invention includes a server that analyzes the characteristics of digital content using a generation algorithm and creates an optimal advertising strategy based on that analysis; a server that uses natural language processing technology to streamline communication with enthusiasts; and a server that analyzes statistical information and constructs a sales plan for digital content. This enables highly personalized promotional activities based on the characteristics of individual works and the emotional state of the creators.

[0721] A "generation algorithm" is a set of calculation procedures that analyze the characteristics of digital content and automatically generate the optimal advertising strategy accordingly.

[0722] "Natural language processing technology" is a technology that allows computers to understand and analyze human language, and it is a means of efficiently communicating information with enthusiasts.

[0723] "Statistical information" refers to market data, specifically numerical data used to develop sales plans for digital content.

[0724] An "emotion analysis device" is a technology that analyzes a user's emotional state in real time and applies that analysis to advertising strategies.

[0725] "Response generation means" refers to technology that enables personalized information transmission tailored to the user's emotional state.

[0726] The embodiment of this invention utilizes advanced generative algorithms and natural language processing technologies to streamline the promotion of digital content and related communications. This system mainly consists of a server, terminals, and users, with each entity performing a specific function.

[0727] The server analyzes the features of received digital content using generative AI models. Specifically, machine learning frameworks such as TensorFlow and PyTorch are used, and the optimal advertising strategy is created based on the results. Furthermore, to act as an emotion analyzer, natural language processing techniques are used to evaluate the user's emotional state in detail. For natural language processing, models such as BERT and GPT are utilized to analyze text data and feedback from the user and generate emotion-based responses.

[0728] The terminal presents information obtained from the server to the user, allowing the user to view and confirm promotional strategies and responses. Furthermore, it functions as an interface for sending user feedback to the server. This makes it possible to improve the user experience through the terminal.

[0729] Users directly interact with promotional strategies provided by the server using their devices, communicating with their fans. User feedback is analyzed by the server and used to improve the next update of the generation algorithm.

[0730] A concrete example would be an artist selling artwork online using this system. When the artist uploads a new, colorful painting to the server, the generative AI model analyzes its features and recommends advertising messages that emphasize bright colors. If sentiment analysis reveals the artist is currently relaxed, it can then suggest a long-term strategy.

[0731] Examples of prompt messages include the following:

[0732] "Please generate a promotional message for the next piece I will upload. The data is 'Abstract painting with bright colors.' My current mood is relaxed."

[0733] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0734] Step 1:

[0735] The server receives digital content data (images, titles, descriptions, etc.) from the user. The input is the user's artwork data, and upon receiving it, the server checks the data's integrity. If the reception is successful, the server notifies the user that the data has been received. This process confirms that the data is ready for use in the next analysis step.

[0736] Step 2:

[0737] The server inputs the received artwork data into a generating AI model and analyzes its features. The input is the data received in step 1. The server uses a machine learning framework (e.g., TensorFlow, PyTorch) to extract features such as the artwork's colors and composition. As a result of the analysis, it outputs basic data for an optimal promotion strategy. This analysis concretizes the characteristics of the artwork, allowing the process to proceed to the next step.

[0738] Step 3:

[0739] The server analyzes the user's emotional state using an emotion analysis device. The input consists of user-provided feedback and text data. The server uses a natural language processing model (e.g., BERT, GPT) to extract emotional data from this input. The output is the user's emotional state, which is then reflected in the promotional strategy. This step enables adaptation based on the user's emotions.

[0740] Step 4:

[0741] The server generates an optimal promotional strategy based on the characteristics of the work and the user's emotional state. The input is the output from steps 2 and 3. The server combines this data to create advertising messages optimized for each individual work. The output is a specific promotional message, which is then delivered to the user. This process enables the implementation of personalized strategies.

[0742] Step 5:

[0743] The terminal displays the promotional strategy provided by the server to the user. The input is the output from step 4. The terminal displays this on the screen, and the user can refer to it and confirm its contents. This step achieves the visualization and use of the promotional strategy by the user.

[0744] Step 6:

[0745] Users send feedback and additional data to the server via their devices. The input consists of user feedback and new instructions. The server receives this feedback and adjusts and updates its analysis results and promotional strategies. This cycle allows the system to continuously improve, enabling more effective promotions.

[0746] (Application Example 2)

[0747] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0748] In today's world, the works of artists and creators are incredibly diverse, requiring appropriate promotional strategies. However, conventional promotional methods often lack personalized approaches that respond to user emotions. As a result, advertising effectiveness is diminished, leading to decreased user engagement.

[0749] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0750] In this invention, the server includes means for analyzing the characteristics of a work using a generative model and proposing an optimal promotion strategy, means for facilitating communication with fans using natural language processing technology, means for analyzing market data and proposing a sales strategy for the work, means for recognizing user emotions and personalizing advertisements, and means for analyzing emotions in real time and dynamically adjusting advertisement content. This makes it possible to optimize advertising and promotion strategies to suit user emotions.

[0751] A "generative model" is an algorithm that learns the characteristics of given data and automatically generates new data and strategies.

[0752] A "promotion strategy" is a method of planning how to approach a target market with the aim of promoting the sale of a product or service.

[0753] "Natural language processing technology" is a technology that uses computers to process human language and understand intentions and emotions.

[0754] "Market data" refers to information and statistics about a specific market, and is used to understand the competitive situation and trends within that market.

[0755] "Recognizing user emotions" is the process of analyzing a user's psychological state and identifying their current emotions.

[0756] "Personalizing ads" refers to customizing ad content to deliver the most relevant and effective ad content to specific users.

[0757] "Real-time emotion analysis" means instantly analyzing the user's emotional data to understand their current emotional state.

[0758] "Dynamically adjusting ad content" refers to the process of instantly changing the message and visuals of the ads presented to users according to their current psychological state and preferences.

[0759] To implement this invention, a system is constructed using specific hardware and software. The server receives artwork data and analyzes it using a generative AI model. In this process, the characteristics of the artwork are captured, and an optimal promotional strategy is formulated. This generative AI model receives visual and textual information of the artwork as input and extracts patterns useful for marketing.

[0760] Furthermore, the server uses natural language processing techniques to analyze comments and messages from fans. This allows it to provide advice and automated responses to help users communicate smoothly with their fans. This natural language processing technique utilizes libraries such as TensorFlow.

[0761] The server also collects market data and uses this data to analyze and optimize sales strategies for the products. Simultaneously, it leverages an emotion engine to understand the emotional states of users and fans, and personalize promotional and advertising content. OpenCV and other emotion analysis tools are used for this emotion recognition.

[0762] The terminal displays information sent from the server, allowing users to review promotional strategies and communication content. Users can also send feedback from the terminal to the server, which can be used to update the system's overall sentiment analysis. This feedback feature enhances the system's adaptability.

[0763] Specific examples of this system include suggesting promotional campaigns that emphasize a fun atmosphere when the user is expressing joy, and adopting a strategy that prioritizes providing detailed information when the user is calm.

[0764] An example of a prompt message is, "If the user's emotion is 'joyful,' please present ads that are related to an overall positive message."

[0765] In this way, the system aims to provide personalized and effective promotion and advertising strategies by utilizing emotion recognition and generative AI models.

[0766] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0767] Step 1:

[0768] The server receives artwork data sent by the user. This artwork data includes images, titles, and descriptions, and is received as input.

[0769] Step 2:

[0770] The server inputs the received artwork data into a generating AI model, which analyzes the characteristics of the artwork. The AI ​​model recognizes patterns and features in the data and extracts elements suitable for promotion. The results of this analysis are then output.

[0771] Step 3:

[0772] The server develops the optimal promotional strategy based on the promotional elements output from the generated AI model. This involves determining how to approach the target audience.

[0773] Step 4:

[0774] The server uses natural language processing technology to analyze comments and messages from fans. It receives text data as input and identifies the emotions expressed. This processing then outputs a response and communication strategy.

[0775] Step 5:

[0776] The server uses an emotion engine to analyze the user's emotional state. It uses real-time data obtained from the camera and microphone as input to identify the user's emotions. This allows for the determination of emotion-based actions.

[0777] Step 6:

[0778] The server dynamically adjusts and personalizes the ad content based on the sentiment analysis results. This ensures that ads best suited to the user's current psychological state are displayed.

[0779] Step 7:

[0780] The device displays promotional strategies and advertisements received from the server to the user. Based on this information, the user checks the progress of the promotion and sends feedback to the server as needed.

[0781] Step 8:

[0782] User feedback is received by the server, and data analysis is performed again to update promotion and advertising strategies. This ensures that the system is always operating in an optimized state.

[0783] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0784] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0785] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0786] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0787] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0788] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0789] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0790] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0791] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0792] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0793] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0794] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0795] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0796] 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.

[0797] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0798] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0799] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0800] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0801] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0802] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0803] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0804] The following is further disclosed regarding the embodiments described above.

[0805] (Claim 1)

[0806] A method for analyzing the characteristics of a work using a generative model and proposing the optimal promotion strategy,

[0807] A means of facilitating communication with fans using natural language processing technology,

[0808] A means of analyzing market data and proposing sales strategies for works,

[0809] A system that includes this.

[0810] (Claim 2)

[0811] The system according to claim 1, which includes means for automatically generating planning and presentation materials for crowdfunding projects and supporting fundraising.

[0812] (Claim 3)

[0813] The system according to claim 1, including communication means for receiving user artwork data and project information and notifying the user of the analysis results.

[0814] "Example 1"

[0815] (Claim 1)

[0816] A method for analyzing content characteristics using generation algorithms and proposing the optimal advertising strategy,

[0817] A means of facilitating information exchange with customers using natural language processing,

[0818] A means of analyzing sales data and proposing content promotion strategies,

[0819] A means of communication for receiving information from the user and notifying the user of the analysis results,

[0820] A system that includes this.

[0821] (Claim 2)

[0822] The system according to claim 1, which includes a process for receiving content input from a user and performing characteristic analysis of that content.

[0823] (Claim 3)

[0824] The system according to claim 1, which displays information from a server via a communication device and provides an environment in which the user can respond interactively.

[0825] "Application Example 1"

[0826] (Claim 1)

[0827] A method for analyzing the characteristics of a work using a generative model and proposing the optimal promotional strategy,

[0828] A means of facilitating communication with supporters using natural language processing technology,

[0829] A means of analyzing market information and proposing sales strategies for works,

[0830] A means of acquiring artwork data, performing artwork analysis using visual devices, and providing suggestions in real time,

[0831] A system that includes this.

[0832] (Claim 2)

[0833] The system according to claim 1, which includes means for automatically creating planning and explanatory materials for crowd fundraising projects and supporting fundraising.

[0834] (Claim 3)

[0835] The system according to claim 1, including a communication means for receiving user artwork information and project information and notifying the user of the analysis results.

[0836] "Example 2 of combining an emotion engine"

[0837] (Claim 1)

[0838] A means of analyzing the characteristics of digital content using a generation algorithm and creating an optimal advertising strategy based on that analysis,

[0839] A means to streamline information communication with enthusiasts using natural language processing technology,

[0840] A means of analyzing statistical information and constructing a sales plan for digital content,

[0841] A means of analyzing users' emotional states using an emotion analysis device and reflecting that in advertising strategies,

[0842] A means for creating responses that enables personalized information delivery according to the user's emotional state,

[0843] ...

[0844] A system that includes this.

[0845] (Claim 2)

[0846] The system according to claim 1, which includes means for automatically creating planning and explanatory materials for fundraising activities and supporting resource procurement.

[0847] (Claim 3)

[0848] The system according to claim 1, including communication means for receiving user's digital content data and planning information, and notifying the user of the analysis results.

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

[0850] (Claim 1)

[0851] A method for analyzing the characteristics of a work using a generative model and proposing the optimal promotion strategy,

[0852] A means of facilitating communication with fans using natural language processing technology,

[0853] A means of analyzing market data and proposing sales strategies for works,

[0854] A means of recognizing user emotions and personalizing ads,

[0855] A means of analyzing emotions in real time and dynamically adjusting advertising content,

[0856] A system that includes this.

[0857] (Claim 2)

[0858] The system according to claim 1, comprising means for customizing the content of advertisements displayed based on emotional state.

[0859] (Claim 3)

[0860] The system according to claim 1, comprising means for analyzing the user's advertising history in accordance with their emotional state and proposing a long-term advertising strategy. [Explanation of Symbols]

[0861] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A method for analyzing the characteristics of a work using a generative model and proposing the optimal promotion strategy, A means of facilitating communication with fans using natural language processing technology, A means of analyzing market data and proposing sales strategies for works, A system that includes this.

2. The system according to claim 1, which includes means for automatically generating planning and presentation materials for crowdfunding projects and supporting fundraising.

3. The system according to claim 1, including communication means for receiving user artwork data and project information and notifying the user of the analysis results.

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