system

Abstract

To provide a system.SOLUTION: A system includes means for allowing a user to input a prompt sentence, means for allowing a server to generate content by using a generative AI, means for allowing the server to insert advertisement to the generated content, means for allowing the server to provide the user with final content, means for allowing a person in an image / video generated by an image and moving image generative AI to wear an advertising company brand, put a logo in a background, clothing, or tattoos, and easily generate an image in line with a lifestyle proposed by the advertising company, and means for coping with even advertising fee payments and targeting for secondary distribution on an SNS by diverting an existing digital advertising technology.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] With traditional advertising methods, it was difficult to advertise on text, images, and videos generated by AI. It was also difficult to generate images that matched the lifestyle proposed by the advertiser, such as wearing the advertiser's brand, adding logos to the background, clothing, or tattoos. Furthermore, it was difficult to pay advertising fees and target secondary distribution on social media. [Means for solving the problem]

[0005] This invention provides a means for placing advertisements on text, images, and videos generated by AI. It also provides a means for easily generating images that fit the lifestyles proposed by advertisers, such as having people in images / videos generated by image / video generation AI wear the advertiser's brand, or adding logos to the background, clothing, or tattoos. Furthermore, by utilizing existing digital advertising technology, it provides a means for supporting advertising fee payments and targeting for secondary distribution on social media. [Brief explanation of the drawings]

[0006] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0008] First, the terms used in the following description will be explained.

[0009] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0011] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0012] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0017] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0018] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0019] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0024] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0025] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] As one embodiment of the present invention, a system is provided that enables advertising in text, images, and videos generated by AI. Specifically, the system has the function of inserting advertising from advertising companies into text, images, and videos generated by AI. For example, it is possible to insert advertising text from advertising companies into blog articles generated by AI.

[0029] "Example 2"

[0030] In addition, the system also provides a function that makes it easier to generate images that match the lifestyles proposed by advertisers, such as having people in images / videos generated by the image / video generation AI wear the advertiser's brand, or adding logos to backgrounds, clothing, or tattoos. Specifically, it has a function that digitally adds the advertiser's logo to people in images / videos generated by the AI. For example, it is possible to digitally add the advertiser's logo to a T-shirt worn by a person in an AI-generated video.

[0031] "Example 3"

[0032] Furthermore, by utilizing existing digital advertising technology, the system also provides functionality for targeting and payment of advertising fees for secondary distribution on social media. Specifically, it has the ability to generate targeted advertisements based on user behavioral and profile data on social media. For example, it is possible to target advertisements from companies selling a particular product based on information that a user has "liked" a product on social media.

[0033] The processing flow of each embodiment will be described below.

[0034] "Example 1"

[0035] Step 1: AI generates text, images, and videos. For example, AI generates a blog post.

[0036] Step 2: Insert the sponsor's advertisement into the generated text, images, and videos. For example, insert the sponsor's advertisement text into the generated blog post.

[0037] "Example 2"

[0038] Step 1: AI generates images / videos. For example, AI generates a video.

[0039] Step 2: Digitally add the advertiser's logo to the person in the generated image / video. For example, digitally add the advertiser's logo to a T-shirt worn by the person in the generated video.

[0040] "Example 3"

[0041] Step 1: Collect user behavioral data and profile data on social media. For example, collect information on whether a user has "liked" a specific product on social media.

[0042] Step 2: Generate targeted ads based on the collected data, for example, targeting ads for companies selling products that users have "liked."

[0043] Example 1

[0044] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0045] Conventional advertising systems have difficulty inserting appropriate ads into AI-generated content, making it impossible to maximize advertising effectiveness. Furthermore, there is a lack of technology to increase the relevance of generated content and ads, making it difficult to effectively provide targeted ads based on users' interests. Furthermore, there is a lack of methods for handling advertising fee payments and targeting for secondary distribution on social media.

[0046] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes a means for a user to input a prompt sentence, a means for the server to generate content using a generation AI model, a means for the server to insert advertisements into the generated content, a means for the server to provide the final content to the user, a means for making it easier to generate images that match the lifestyle proposed by the advertiser by having people in the images / videos generated by the image / video generation AI wear the advertiser's brand, adding logos to the background, clothing, or tattoos, and so on, and a means for supporting advertising fee payments and targeting for secondary distribution on SNS by utilizing existing digital advertising technology. This makes it possible to insert appropriate advertisements into the generated content and effectively provide targeted advertisements based on the user's interests. Furthermore, it is also possible to support advertising fee payments and targeting for secondary distribution on SNS.

[0047] A "user" is an individual or entity that utilizes the system to enter prompts and receive generated content.

[0048] A "prompt sentence" is text that a user inputs to specifically instruct the system on the content they wish to generate.

[0049] "Server" refers to a computer system that generates content using a generative AI model, inserts advertisements, and provides the final content to users.

[0050] A "generative AI model" is an artificial intelligence model that generates content such as text, images, and videos based on prompts entered by users.

[0051] "Content" refers to information such as text, images, and videos generated by a generative AI model.

[0052] An "advertisement" is information such as text, images, and videos inserted into content to promote products or services offered by the advertising company.

[0053] "Advertiser" means a company that provides advertisements and inserts those advertisements into content through the system.

[0054] "Targeted advertising" refers to advertising that is optimized for a specific user based on the user's behavioral data and profile data.

[0055] "SNS" is an abbreviation for social networking service, an online platform for users to share information and interact with each other.

[0056] "Secondary distribution" refers to the re-sharing of generated content through social media and other means.

[0057] "Digital advertising technology" refers to technology for delivering advertisements on online platforms and measuring their effectiveness.

[0058] This invention relates to a system for inserting advertisements into text, images, and videos generated using a generative AI model. In this system, a user inputs a prompt sentence, a server generates content using a generative AI model, inserts advertisements, and provides the final content.

[0059] Hardware and software used

[0060] The server is a high-performance computing system for running generative AI models. Specifically, it uses the following hardware and software:

[0061] Hardware: A server with a powerful CPU, GPU, and sufficient memory

[0062] Software: Generative AI models (e.g., OpenAI's GPT-4 and DALL-E), natural language processing (NLP) libraries, and database management systems.

[0063] Data processing and calculation

[0064] The server receives the prompt entered by the user and uses the generative AI model to:

[0065] 1. Parse the prompt:

[0066] The server analyzes the prompt sentence entered by the user and determines the content to be generated.

[0067] Example: A user types, "Generate blog posts about summer travel."

[0068] 2. Content generation:

[0069] The server uses a generative AI model to generate text, images, and videos based on the prompt.

[0070] Example: A server generates a "summer travel blog post" that includes information about recommended travel spots and activities.

[0071] 3. Ad Insertion:

[0072] The server inserts appropriate advertisements into the generated content, performing topic analysis and relevance evaluation of the content to select the most suitable advertisement.

[0073] Example: Inserting advertising text into generated blog posts that reads, "Take advantage of our travel agency's special deals this summer!"

[0074] 4. Final Content Delivery:

[0075] The server generates the final content with the advertisements inserted and provides it to the user.

[0076] Example: A server displays a blog post with an ad inserted to a user, who then views the post.

[0077] Examples of concrete examples and prompts

[0078] Examples:

[0079] When a user enters the prompt "Generate a blog post about autumn leaves," the server generates a blog post about autumn leaves and inserts advertising text into it that reads, "Take beautiful photos with this camera manufacturer's new model during the autumn foliage season!"

[0080] Example prompt sentence:

[0081] "Generate blog posts about summer travel"

[0082] "Generate a review video for a new smartphone"

[0083] "Generate images of healthy recipes"

[0084] In this way, a system is realized in which the user inputs a prompt sentence, the server generates content using a generative AI model, inserts appropriate advertisements, and provides the final content.

[0085] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0086] Step 1:

[0087] The user inputs a prompt statement. The user inputs a prompt statement that specifically specifies the content they want to generate through the system interface. The input prompt statement is sent to the server. In a specific operation, the user inputs, "Generate a blog post about summer travel."

[0088] Input: The prompt text entered by the user

[0089] Output: The prompt sent to the server

[0090] Step 2:

[0091] The server receives the prompt and generates content using a generative AI model. The server analyzes the prompt and generates text, images, and videos using a generative AI model (for example, OpenAI's GPT-4 or DALL-E). Specifically, the server generates a "summer travel blog post."

[0092] Input: The prompt text sent by the user

[0093] Output: Generated text, images, and videos

[0094] Step 3:

[0095] The server inserts advertisements into the generated content. The server performs topic analysis and relevance assessment of the generated content, and selects appropriate advertisements from the advertising company's advertisement database. The selected advertisements are inserted at appropriate positions within the content. Specifically, the server inserts advertisement text into the generated blog post, such as "We recommend this travel agency's special plan for your summer trip!"

[0096] Input: Generated text, images, videos

[0097] Output: Text, images, and videos with ads inserted

[0098] Step 4:

[0099] The server provides the final content to the user. The server generates the final content with the advertisement inserted and provides it to the user. The user can view this content through the system interface. Specifically, the server displays the blog post with the advertisement inserted to the user.

[0100] Input: Text, images, and videos with ads inserted

[0101] Output: The final content that is delivered to the user

[0102] (Application example 1)

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

[0104] With conventional advertising systems, it was difficult to effectively insert ads into AI-generated text, images, and videos. Furthermore, the process of selecting and inserting appropriate ads into user-generated content was often done manually, resulting in inefficiency. Furthermore, the effectiveness of ads was not adequately measured, making it difficult to accurately determine the effectiveness of each ad. To solve these issues, an efficient advertising system utilizing AI is needed.

[0105] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0106] In this invention, the server includes a means for enabling advertisements to be placed in text, images, and videos generated by AI, a means for AI to select appropriate advertisements and insert them into content when users upload content generated by users to the application, and a means for incorporating an advertisement effectiveness measurement function and analyzing which advertisements received how many clicks and views. This makes it possible to efficiently insert advertisements using AI and accurately measure their effectiveness.

[0107] "AI-generated text, images, and videos" refers to text, still images, and videos that are automatically generated using artificial intelligence technology.

[0108] "Means enabling advertising" refers to methods or technologies that allow companies or individuals to insert advertisements into specific media or content.

[0109] "Image and video generation AI" refers to systems and algorithms that automatically generate images and videos using artificial intelligence technology.

[0110] "Wearing the advertiser's brand" refers to people in the generated images and videos displaying a specific company's brand or logo.

[0111] "Logo on background, clothing, tattoo" refers to the insertion of a specific company's logo on the background, clothing, or tattoo in the generated image or video.

[0112] "Images that are in line with the lifestyle proposed by the advertising company" refers to images that reflect the lifestyle and values ​​that a particular company promotes.

[0113] "Existing digital advertising technologies" refers to digital advertising technologies and methods that are currently in widespread use.

[0114] A "social networking service" is an online platform that allows people to share information and interact with each other over the Internet.

[0115] "Advertising fees for secondary distribution" refers to the payment of advertising fees that occurs when an advertisement is shared or reused again after its initial distribution.

[0116] "Targeting" refers to the method of delivering advertisements to specific user groups or market segments.

[0117] "User-generated content" means text, images or videos that are created by members of the public and uploaded to online platforms.

[0118] "Uploading to an Application" means sending and storing content created by a user to a specific software or platform.

[0119] "Selecting the right ad" refers to choosing the most relevant and effective ad for a particular content or user.

[0120] The "advertising effectiveness measurement function" is a function that analyzes the number of clicks and views an advertisement receives and evaluates its effectiveness.

[0121] The following system configuration will be described as an embodiment of the present invention.

[0122] System Configuration

[0123] This system includes a server, a user device, and an AI model. The server provides a means for placing advertisements in AI-generated text, images, and videos. The user device uploads user-generated content and provides an interface for the AI ​​to select appropriate advertisements and insert them into the content. The AI ​​model executes an algorithm to insert advertisements into the generated content and measure their effectiveness.

[0124] Hardware and software used

[0125] Hardware: Smartphones, servers

[0126] Software: Python, OpenAI API

[0127] Data processing and calculation

[0128] The server receives user-generated content and uses the AI ​​model to select appropriate ads. Specifically, the process involves the following steps:

[0129] 1. User input: The user inputs a prompt for the content they want to generate into the user terminal.

[0130] 2. Content Generation: The server uses the OpenAI API to generate text content based on the user's prompts.

[0131] 3. Advertisement selection: The server selects pre-prepared advertisement text for the generated content.

[0132] 4. Advertisement insertion: The server inserts the selected advertisements into the generated content.

[0133] 5. Effectiveness measurement: The server analyzes the number of clicks and views of the advertisement and measures its effectiveness.

[0134] Specific examples

[0135] User Input

[0136] The user enters a prompt like this:

[0137] "Generate a review article for a new smartphone"

[0138] "Generate articles about the latest fashion trends"

[0139] "Generate healthy eating advice"

[0140] "Generate a guide to the best places to visit in your travel destination."

[0141] Content Generation

[0142] The server uses the OpenAI API to generate text content like this:

[0143] "This phone is very powerful and the camera quality is excellent."

[0144] "This year's fashion trends are characterized by colorful accessories and simple designs."

[0145] "A balanced diet and moderate exercise are important for maintaining a healthy diet."

[0146] "The best travel destinations are those with beautiful scenery and rich culture."

[0147] Ad selection and insertion

[0148] The server inserts advertisements into the generated content, such as:

[0149] "Check this product out!"

[0150] Effectiveness measurement

[0151] The server analyzes the number of clicks and views the ad received and measures its effectiveness, allowing the user to accurately understand the effectiveness of the ad and use this information to improve the next ad placement.

[0152] In this way, an efficient advertising system utilizing AI will be realized.

[0153] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0154] Step 1:

[0155] The user inputs a prompt statement for the content that he or she wants to generate into the user terminal.

[0156] Input: The prompt text entered by the user (e.g., "Generate a review of a new smartphone.")

[0157] Output: Prompt sent from the user's terminal to the server

[0158] Specific operation: The user opens the application on their smartphone, enters the prompt for the content they want to generate, and presses the send button. The user's device then sends this prompt to the server.

[0159] Step 2:

[0160] The server uses the OpenAI API to generate text content based on the user's prompts.

[0161] Input: Prompt sent from the user's terminal

[0162] Output: Generated text content (e.g., "This smartphone is very powerful and the camera quality is excellent.")

[0163] Specific operation: The server sends the received prompt to the OpenAI API, and the AI ​​model generates text content based on the prompt. The generated text content is returned to the server.

[0164] Step 3:

[0165] The server selects pre-prepared advertising text for the generated content.

[0166] Input: Generated text content, ad database

[0167] Output: Selected ad text (e.g., "Check out this product!")

[0168] Specific operation: The server analyzes the generated text content and selects the most relevant advertising text from the advertising database.

[0169] Step 4:

[0170] The server inserts the selected advertisements into the generated content.

[0171] Input: Generated text content, selected advertising text

[0172] Output: The final content with the ad inserted (e.g., "This phone is very powerful and has an excellent camera.\n\n---\nAd: Check out this product!\n---")

[0173] Specific operation: The server inserts the selected advertising text into the appropriate position of the generated text content to generate the final content.

[0174] Step 5:

[0175] The server analyzes the number of clicks and views of the advertisements to measure their effectiveness.

[0176] Input: Final content with ad insertion, user behavior data

[0177] Output: Ad effectiveness measurement results (e.g., number of clicks, number of views)

[0178] How it works: The server delivers content with ads inserted, records the number of clicks and views by users, and analyzes this data to measure the effectiveness of the ads.

[0179] In this way, an efficient advertising system utilizing AI will be realized.

[0180] Example 2

[0181] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0182] With conventional digital advertising systems, it was difficult to effectively reflect the advertiser's brand in the generated images and videos. Inserting ads into user-generated content was also time-consuming and costly, and the accuracy of targeted advertising was insufficient. Furthermore, there was no system in place for paying advertising fees for secondary distribution on online platforms.

[0183] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for a user to input a prompt text, a means for the server to receive the prompt text and call a generative AI model, a means for the server to acquire the generated images and videos and add the logo of the advertising company, a means for the server to send the processed images and videos to the user, and a means for supporting payment of advertising fees and targeting for secondary distribution on online platforms by utilizing existing digital advertising technology. This enables users to easily generate images and videos incorporating the brand of the advertising company and improve the accuracy of targeted advertising. A system for payment of advertising fees for secondary distribution on online platforms is also established.

[0184] A "user" is an individual or entity that utilizes the system to input prompts and receive generated images and videos.

[0185] A "prompt" is text that a user inputs into a generative AI model, describing the content of the image or video they want to generate.

[0186] The "server" is a computer system that receives prompt text from the user, invokes the generative AI model, retrieves the generated images and videos, processes them, and finally sends them to the user.

[0187] A "generative AI model" is an artificial intelligence model that generates images and videos based on prompt text.

[0188] A "logo" is a digital image or text that represents the advertiser's brand and is added to the generated image or video.

[0189] "Sponsor" means a company or organization that sponsors an advertisement and whose brand or logo is to be reflected in the generated images and videos.

[0190] "Targeted advertising" refers to advertising that is optimized for a specific user based on the user's behavioral data and profile data.

[0191] An "online platform" is a general term for services and applications provided over the Internet, and is a place where users can share content they generate.

[0192] "Secondary distribution" refers to the redistribution of generated content through other users or platforms after its initial release.

[0193] "Advertising payment" refers to the fee paid by an advertiser for an advertisement being displayed or clicked on.

[0194] This invention is a system that allows users to input prompt text, generates images and videos using a generative AI model, and adds the sponsor's logo. A specific embodiment of this system is described below.

[0195] Hardware and software used

[0196] Hardware: Servers, terminals

[0197] Software: Generative AI models (e.g., OpenAI's DALL-E, Stable Diffusion), image editing software (e.g., Adobe Photoshop API)

[0198] Program processing

[0199] The user enters a prompt statement

[0200] The user inputs a prompt into the input form on the device that describes the image or video they want to generate. For example, they input a prompt such as "Generate an image of a man wearing a blue shirt jogging in a park."

[0201] The server receives the prompt.

[0202] The prompt text entered by the user is sent from the terminal to the server, which receives it and prepares to proceed with the next process.

[0203] The server invokes the generative AI model

[0204] The server passes the received prompt sentence to the generative AI model, which then begins calculations to generate images and videos based on the prompt sentence.

[0205] The server retrieves the generated images and videos.

[0206] Once the generative AI model has finished generating images and videos based on the prompt, the server retrieves the generated results, which are temporarily stored on the server.

[0207] The server adds the advertiser's logo

[0208] The server digitally adds the advertiser's logo to the people in the generated images and videos, for example, by adding the advertiser's logo to a T-shirt worn by the people in the generated images, using image editing software (e.g., Adobe Photoshop API).

[0209] The server sends the processed images and videos to the user.

[0210] The server sends the images and videos with the logo added to them to the user, who can then view the processed images and videos on their device. The transmission is done using the HTTP protocol.

[0211] Specific examples

[0212] Prompt Sentence Examples

[0213] "Generate an image of a woman in a red dress walking on the beach"

[0214] "Generate a video of a man in a black suit giving a presentation in an office."

[0215] In this way, users can easily create and review images and videos incorporating the advertiser's brand. This system will improve the accuracy of targeted advertising and will also establish a system for paying advertising fees for secondary distribution on online platforms.

[0216] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0217] Step 1:

[0218] The user enters a prompt statement

[0219] The user inputs a prompt that describes the image or video they want to generate into the input form on their device. For example, they might input a prompt such as "Generate an image of a man in a blue shirt jogging in a park." The input prompt is then sent from the device to the server.

[0220] Step 2:

[0221] The server receives the prompt.

[0222] The server receives the prompt sent from the device, parses the received prompt, and prepares to pass it to the generative AI model. The input is the prompt, and the output is the parsed prompt.

[0223] Step 3:

[0224] The server invokes the generative AI model

[0225] The server passes the parsed prompt sentence to the generative AI model, which then begins calculations to generate images and videos based on the prompt sentence. The input is the parsed prompt sentence, and the output is the generated image or video data.

[0226] Step 4:

[0227] The server retrieves the generated images and videos.

[0228] Once the generative AI model has finished generating images and videos based on the prompt, the server retrieves the generated results. The generated images and videos are temporarily stored on the server. The input is the generated results from the generative AI model, and the output is the image and video data stored on the server.

[0229] Step 5:

[0230] The server adds the advertiser's logo

[0231] The server digitally adds the sponsor's logo to the people in the generated images and videos. For example, the sponsor's logo is added to a T-shirt worn by a person in the generated image. This process is performed using image editing software (e.g., Adobe Photoshop API). The input is the image or video data stored on the server, and the output is the image or video data with the logo added.

[0232] Step 6:

[0233] The server sends the processed images and videos to the user.

[0234] The server sends the images or videos with the logo added to the user, who can then view the processed images or videos on their device. Transmission is performed using the HTTP protocol. The input is the image or video data with the logo added, and the output is the processed image or video sent to the user's device.

[0235] (Application example 2)

[0236] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0237] With conventional advertising methods, it was difficult to automatically add specific brand logos or lifestyle elements to images and videos taken by users. Furthermore, there was a lack of effective ways to expose brands within the generated content, and there was a need for improved accuracy in targeted advertising.

[0238] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for enabling advertisements to be placed on text, images, and videos generated by AI; a means for making it easier to generate images that match the lifestyle proposed by the advertising company by having people in images / videos generated by image and video generation AI wear the advertising company's brand or add logos to backgrounds, clothing, or tattoos; and a means for automatically adding specific brand logos and lifestyle elements to images and videos taken by users. This makes it possible to effectively expose brands to content taken by users.

[0239] "AI-generated text, images, and videos" refers to text, still images, and video automatically generated using artificial intelligence technology.

[0240] "Means enabling advertising placement" refers to the methods and technologies that allow advertisers to place advertisements in specific media.

[0241] "Image and video generation AI" refers to systems and algorithms that use artificial intelligence technology to automatically generate still images and videos.

[0242] "Advertising company brand" refers to the trademark, logo, and brand image of the company placing the advertisement.

[0243] "Logo on background, clothing, tattoos" refers to the digital addition of a logo to a background, person's clothing, or tattoos in a generated image or video.

[0244] "Lifestyle images" are images created based on a particular lifestyle or values.

[0245] "Existing digital advertising technologies" refers to online advertising technologies and methods currently in widespread use.

[0246] "Secondary distribution on social media" refers to users sharing or reposting content on social networking services.

[0247] "Targeted advertising" refers to the technology and methods used to deliver advertisements optimized for specific user groups or individuals.

[0248] "User behavior data" refers to data about the actions and behavior of users online.

[0249] "Profile Data" refers to data about a user's attributes, interests, and concerns.

[0250] "Training data" refers to a data set used to train an artificial intelligence.

[0251] "Brand image" refers to the image or perception that consumers have of a particular brand.

[0252] A system for implementing this invention has the following configuration: A server includes means for enabling advertisements to be placed on text, images, and videos generated by AI, means for making it easier to generate images that fit the lifestyle proposed by the advertising company by having people in the images / videos generated by the image / video generation AI wear the advertising company's brand or add logos to the background, clothing, or tattoos, and means for automatically adding specific brand logos and lifestyle elements to images and videos taken by the user.

[0253] Hardware and software used

[0254] Hardware: Smartphone (iOS or ANDROID (registered trademark))

[0255] Software: Image and video generation AI (e.g., OpenAI's DALL-E), image processing library (e.g., OpenCV), cloud storage (e.g., AWS (registered trademark) S3)

[0256] Data processing and calculation

[0257] Uploading images and videos

[0258] Users upload images and videos they have taken using their smartphones to the application, and the uploaded data is stored in cloud storage (AWS S3).

[0259] AI analysis and logo addition

[0260] The server uses an image and video generation AI (DALL-E) to analyze uploaded images and videos. Based on the analysis results, it adds the specified brand logo and lifestyle elements. It uses an image processing library (OpenCV) to place the logo and background elements in the appropriate position.

[0261] Preview and save the generated results

[0262] It shows the user a preview of the generated image or video, and if the user is satisfied, it saves the generated result to cloud storage and provides a download link.

[0263] Specific examples

[0264] scenario

[0265] Consider a case where a user wants to add the logo of a particular sports brand to a photo they take with their friends.

[0266] Prompt Sentence Examples

[0267] "Take a photo with your friends and add a sports brand logo to your T-shirt."

[0268] "Add a beverage brand advertisement in the background of this photo."

[0269] "Please add a clothing brand logo to the jacket worn by the person in this video."

[0270] "Change the background of this image to a beach and add a surfing brand logo."

[0271] In this way, it is possible to effectively expose the brand to content shot by users.

[0272] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0273] Step 1:

[0274] Users upload images and videos taken using their smartphones to the application. The input is the images and videos taken by the user, and the output is the data stored in cloud storage (AWS S3). Specifically, the user taps the upload button on the application and selects the images or videos from the file selection screen.

[0275] Step 2:

[0276] The server retrieves uploaded images and videos from cloud storage. The input is the images and videos stored in cloud storage, and the output is data in a format that can be processed within the server. Specifically, the server downloads the data using the AWS S3 API.

[0277] Step 3:

[0278] The server uses the image and video generation AI (DALL-E) to analyze the acquired images and videos. The input is images and videos in a format that can be processed within the server, and the output is the analysis results. Specifically, the server calls the DALL-E API and analyzes the content of the images and videos.

[0279] Step 4:

[0280] The server adds the specified brand logo and lifestyle elements based on the analysis results. The input is the analysis results and the data of the brand logo and lifestyle elements to be added, and the output is an image or video with the logo or elements added. Specifically, the server uses an image processing library (OpenCV) to place the logo and elements in the appropriate position.

[0281] Step 5:

[0282] The server displays a preview of the generated image or video to the user. The input is the image or video with the logo or elements added, and the output is the preview screen displayed on the user's smartphone. Specifically, the server sends the generated data to the user's smartphone, and the application displays the preview screen.

[0283] Step 6:

[0284] If the user is satisfied with the generated results, the server saves the results in cloud storage and provides a download link. The input is the user's satisfaction confirmation and the generated image or video, and the output is the data stored in cloud storage and a download link. Specifically, the user taps the save button in the application, and the server saves the data in AWS S3 and generates a download link.

[0285] Example 3

[0286] Next, a description will be given of a third embodiment of the third embodiment. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0287] Conventional digital advertising systems have had difficulty effectively utilizing user behavioral and profile data to generate targeted ads. They also lacked a mechanism for measuring the effectiveness of generated ads and providing feedback for the next ad generation. Furthermore, there were limited means for automatically generating ad content, resulting in insufficient personalization of ads.

[0288] The identification process by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means. In this invention, the server includes means for collecting user behavioral data and profile data, means for storing the collected data in a database, means for analyzing the stored data and generating targeted advertisements, means for automatically generating advertisement content using a generative AI model, means for delivering the generated advertisements, and means for measuring the effectiveness of the advertisements and providing feedback for the next advertisement generation. This makes it possible to effectively utilize user behavioral data and profile data to generate and deliver personalized targeted advertisements. Furthermore, measuring the effectiveness of the advertisements and providing feedback for the next advertisement generation can improve the accuracy and effectiveness of the advertisements.

[0289] "User behavioral data" refers to data regarding actions such as "likes," shares, and comments taken by users on social media platforms.

[0290] "Profile data" refers to data that includes personal information and attribute information such as a user's age, gender, and interests.

[0291] A "database" is a system for storing and managing collected user behavioral data and profile data.

[0292] "Analysis" is the process of analyzing user interests and behavioral patterns based on stored data.

[0293] "Targeted advertising" refers to advertising that is personalized for specific users based on analysis results.

[0294] A "generative AI model" is a model that uses artificial intelligence technology to automatically generate advertising content.

[0295] A "prompt" is an instruction entered into a generative AI model, and is text that prompts the generation of advertising copy.

[0296] "Serving ads" is the process of sending the generated ads to social media platforms and displaying them in users' feeds.

[0297] "Effectiveness measurement" is the process of collecting data such as the number of clicks and conversion rates of delivered advertisements to evaluate their effectiveness.

[0298] "Feedback" is the process of reflecting the results of effectiveness measurement in the generation of the next advertisement.

[0299] MODE FOR CARRYING OUT THE INVENTION

[0300] This invention relates to a system for generating and delivering targeted advertisements by utilizing user behavior data and profile data. Specific embodiments of this system are described below.

[0301] 1. Program Generation

[0302] The server collects user behavioral data and profile data from SNS platforms (e.g., SNS service A, SNS service B) and generates a program that generates targeted advertisements based on that data. This program automatically creates the content of the advertisements using a generative AI model (e.g., generative AI model A).

[0303] 2. Program processing explanation

[0304] The server collects user behavior data (e.g., likes, shares, comments) and profile data (e.g., age, gender, interests) from the social networking platform. This data is stored in databases (e.g., Database A, Database B).

[0305] The server then analyzes the collected data and generates targeted ads based on specific conditions. For example, if a user "likes" a particular product, it generates ads for companies selling that product. This ad generation uses a generative AI model (e.g., Generative AI Model A).

[0306] The generated advertisements are sent to social media platforms and displayed in users' feeds. To measure the effectiveness of the advertisements, the servers also collect and analyze data such as the number of clicks and conversion rates.

[0307] 3. Examples of concrete examples and prompts

[0308] As a concrete example, consider the case where a user "likes" a "smartphone" on a social networking site. Based on this information, the server generates advertisements for companies that sell smartphones.

[0309] Example prompt sentence:

[0310] Generate ads for companies selling smartphones based on users' "likes" on social media. Include the latest smartphone features, prices, and purchase links in the ads.

[0311] By feeding this prompt into a generative AI model, the following ad is generated:

[0312] Introducing the latest smartphone! High-performance camera, long battery life, and a great price. Click the Buy Now link to find out more!

[0313] In this way, the server utilizes user behavior data on the SNS to provide a system that effectively generates and distributes targeted advertisements. This system improves the effectiveness of advertisements by promoting personalization of advertisements and displaying advertisements based on the user's interests. In addition, measurement of advertisement effectiveness and feedback improves the accuracy of next advertisement generation. The flow of the identification process in Example 3 will be described with reference to FIG. 15.

[0314] Step 1: Collect user behavior data

[0315] The server collects user behavior data from the social media platform. Specifically, it obtains data such as posts that users have "liked," content that they have shared, and comments on through the API. It receives the data obtained from the social media platform's API as input and converts the behavior data into a format that can be stored in a database as output.

[0316] Step 2: Save your data

[0317] The server stores the collected behavioral data in a database. The database contains information such as the user ID, type of behavior, content ID of the behavior, and timestamp. The server receives the behavioral data collected in step 1 as input and stores it in the database as output.

[0318] Step 3: Analyze the data

[0319] The server analyzes the stored data, using data mining techniques and machine learning algorithms. For example, if a user has many "likes" for products in a particular category, it can be determined that the user has a high level of interest in that category. The server receives the behavioral data stored in the database as input and obtains the analysis results as output.

[0320] Step 4: Generate targeted ads

[0321] The server generates targeted ads based on the analysis results. At this time, it uses a generative AI model to automatically generate the ad content. Specifically, it inputs the prompt text into the generative AI model to generate ad copy. It receives the analysis results and the prompt text as input, and obtains the generated ad copy as output.

[0322] Example prompt sentence:

[0323] Generate ads for companies selling smartphones based on users' "likes" on social media. Include the latest smartphone features, prices, and purchase links in the ads.

[0324] Step 5: Serving Ads

[0325] The server sends the generated advertisement to the social media platform, which displays the advertisement in the user's feed. The server receives the generated advertisement copy as input and sends it as output to the social media platform.

[0326] Step 6: Measurement and feedback

[0327] The server measures the effectiveness of the delivered advertisements. Specifically, it collects and analyzes data such as the number of ad clicks, conversion rate, and duration of visit. Based on this data, it evaluates the effectiveness of the advertisements and provides feedback for the generation of the next advertisement. It receives the effectiveness measurement data obtained from the SNS platform as input, and obtains the analysis results and feedback information as output.

[0328] (Application example 3)

[0329] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0330] With conventional digital advertising technology, it was difficult to effectively utilize user behavior data on social media to generate targeted ads. Furthermore, there was a lack of a way to properly display the generated ads on users' smartphones, limiting the effectiveness of the ads. Furthermore, it was difficult to generate images and videos that reflected the brand image of the advertising company.

[0331] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes a means for enabling advertisements to be placed on text, images, and videos generated by AI; a means for easily generating images that match the lifestyle proposed by the advertising company by having people in images / videos generated by image and video generation AI wear the advertising company's brand or add logos to the background, clothing, or tattoos; a means for supporting advertising fee payments and targeting for secondary distribution on social media by utilizing existing digital advertising technology; and a means for generating targeted advertisements based on user behavioral data and profile data and displaying them on smartphones. This enables the generation and display of effective targeted advertisements based on user interests.

[0332] "AI" is an abbreviation for artificial intelligence, a technology that allows computers to imitate human intelligence and learn and reason.

[0333] "Text" refers to information expressed in the form of letters or sentences.

[0334] An "image" is static visual information that can be perceived visually.

[0335] "Video" refers to visual information that expresses movement by displaying a series of images at regular time intervals.

[0336] "Advertising" refers to the procedures and actions for placing an advertisement in a specific medium.

[0337] "Image generation AI" refers to systems and algorithms that generate images using artificial intelligence technology.

[0338] "People in video" refers to human characters or models that appear in the generated images or videos.

[0339] A "brand" is a name, logo, or image that identifies a particular company or product.

[0340] "Background" refers to the area behind the main subject in an image or video.

[0341] "Clothing" refers to the clothing and accessories worn by humans.

[0342] A "tattoo" is a pattern or design created by injecting ink into the skin.

[0343] A "logo" is a design or mark that symbolizes a company or brand.

[0344] A "lifestyle" is a pattern of behavior and values ​​that an individual or group chooses to live in their daily lives.

[0345] "Digital advertising technology" refers to technology for delivering advertisements using the Internet and digital devices.

[0346] "SNS" is an abbreviation for social networking services, a platform for people to interact with each other on the Internet.

[0347] "Secondary distribution" refers to a product being re-released on the market after going through primary distribution.

[0348] "Advertising Payment" means the fee paid for placing an advertisement.

[0349] "Targeting" is a method of delivering advertisements to specific user groups.

[0350] "Behavioral Data" refers to information about the actions you take online and offline.

[0351] "Profile data" refers to information including a user's attributes, interests, behavioral history, etc.

[0352] A "smartphone" is a highly functional mobile phone that can connect to the Internet and use applications.

[0353] A system for implementing this invention has the following configuration: The server includes means for enabling advertisements to be placed on text, images, and videos generated by AI, means for easily generating images that match the lifestyle proposed by the advertising company, such as by having people in the images / videos generated by the image / video generation AI wear the advertising company's brand or adding logos to the background, clothing, or tattoos, means for handling advertising fee payments and targeting for secondary distribution on SNS by utilizing existing digital advertising technology, and means for generating targeted advertisements based on user behavioral data and profile data and displaying them on smartphones.

[0354] Hardware and software used

[0355] Hardware: Servers, smartphones

[0356] Software: Python, SNS API, scikit-learn, TfidfVectorizer, linear_kernel

[0357] Data processing and calculation

[0358] The server uses the SNS API to obtain user behavior data. Specifically, it collects data on products and posts that users have "liked" on SNS. This data reflects the user's interests and concerns, and is therefore important information for generating targeted advertisements.

[0359] Next, the server uses TfidfVectorizer to vectorize the user's "like" data and the ad data, converting the text data into numerical data for easier calculations. It then uses linear_kernel to calculate the cosine similarity between the user's "like" data and the ad data, allowing it to select the ad that most closely matches the user's interests.

[0360] The selected ads are then displayed on smartphones, allowing users to view ads based on their interests, increasing the effectiveness of the ads.

[0361] Specific examples

[0362] For example, if a user "likes" a "new fashion item" on a social networking site, that data is sent to a server. The server uses that data to generate fashion-related advertisements and displays them on the user's smartphone. These advertisements include information about new products and sales from the brand the user "liked."

[0363] Prompt Sentence Examples

[0364] "Generate targeted ads based on products that users have liked on social media. User ID is "user123"."

[0365] In this manner, the present invention enables the generation and display of effective targeted advertisements based on user interests.

[0366] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0367] Step 1:

[0368] The server uses the SNS API to obtain user behavior data. Specifically, it collects data on products and posts that users have "liked" on the SNS. The input is the user ID, and the output is the user's "like" data. This data reflects the user's interests and concerns, and is therefore important information for generating targeted advertisements.

[0369] Step 2:

[0370] The server vectorizes the retrieved user "like" data using TfidfVectorizer. The input is the user "like" data, and the output is the vectorized user data. This process converts text data into numerical data, making it easier to perform calculations.

[0371] Step 3:

[0372] The server retrieves the ad descriptions from the ad database and vectorizes them using TfidfVectorizer as well. The input is the ad database, and the output is the vectorized ad data. This prepares the ad content for comparison with user interests.

[0373] Step 4:

[0374] The server uses the linear_kernel to calculate the cosine similarity between the vectorized user "like" data and the ad data. The input is the vectorized user data and ad data, and the output is the similarity score. This process allows us to select the ad that is closest to the user's interests.

[0375] Step 5:

[0376] The server selects the most suitable advertisement based on the similarity score and generates data to display on the smartphone. The input is the similarity score, and the output is the selected advertisement data. This advertisement data includes information on new products and sales from brands that the user has "liked."

[0377] Step 6:

[0378] The terminal (smartphone) receives the advertising data sent from the server and displays it to the user. The input is the selected advertising data, and the output is the advertisement displayed on the user's smartphone screen. This allows the user to view advertisements based on their interests.

[0379] In this way, the server and the terminal work together to generate targeted advertisements based on user behavior data and display them effectively.

[0380] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0381] "Example 1"

[0382] One embodiment of the present invention is a system in which a means for placing advertisements on AI-generated text, images, and videos includes a function for generating advertisements based on the user's emotions using an emotion engine that recognizes the user's emotions. Specifically, the emotion engine recognizes the user's emotions, and the AI ​​generates advertisements based on those emotions. For example, if the user expresses joy, the AI ​​generates an advertisement that emphasizes the joy in line with that emotion.

[0383] "Example 2"

[0384] In addition, some systems use an emotion engine that recognizes user emotions to generate brand images that correspond to the user's emotions, making it easier to generate images that match the lifestyle proposed by the advertiser, such as having people in the images / videos generated by the image / video generation AI wear the advertiser's brand, or adding logos to the background, clothing, or tattoos. Specifically, the emotion engine recognizes the user's emotions, and the AI ​​generates a brand image based on those emotions. For example, if the user expresses a sense of security, the AI ​​generates a brand image that emphasizes that sense of security, matching that emotion.

[0385] "Example 3"

[0386] Furthermore, by utilizing existing digital advertising technology, there are also systems that use an emotion engine that recognizes user emotions to generate targeted ads based on the user's emotions, which can also support advertising fee payments and targeting for secondary distribution on social media. Specifically, the emotion engine recognizes the user's emotions, and the AI ​​generates targeted ads based on those emotions. For example, if the user expresses excitement, the AI ​​generates targeted ads that emphasize that excitement.

[0387] The processing flow of each embodiment will be described below.

[0388] "Example 1"

[0389] Step 1: The emotion engine recognizes the user's emotion.

[0390] Step 2: The AI ​​generates an ad based on the recognized emotion.

[0391] Step 3: The generated advertisement is displayed using AI-generated text, images, and videos.

[0392] "Example 2"

[0393] Step 1: The emotion engine recognizes the user's emotion.

[0394] Step 2: AI generates a brand image based on the recognized emotion.

[0395] Step 3: Based on the generated brand image, the AI ​​generates images that fit the lifestyle proposed by the advertiser, such as people in the image / video wearing the advertiser's brand, adding logos to the background, clothing, or tattoos.

[0396] "Example 3"

[0397] Step 1: The emotion engine recognizes the user's emotion.

[0398] Step 2: Based on the emotions recognized, the AI ​​generates targeted ads.

[0399] Step 3: Based on the generated targeted advertisements, existing digital advertising technology is utilized to handle advertising payments and targeting for secondary distribution on social media.

[0400] Example 1

[0401] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0402] With conventional advertising systems, it was difficult to insert effective ads into AI-generated content. Furthermore, there was a lack of means to generate ads that corresponded to the user's emotions, making it impossible to provide ads that corresponded to the user's interests. Furthermore, there were insufficient means to handle advertising fee payments and targeting for secondary distribution on social media.

[0403] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. In this invention, the server includes: a means for enabling advertisements to be placed in text, images, and videos generated by AI; a means for easily generating images that match the lifestyle proposed by the advertising company by having people in images / videos generated by image and video generation AI wear the advertising company's brand or add logos to the background, clothing, or tattoos; a means for supporting advertising fee payments and targeting for secondary distribution on social media by utilizing existing digital advertising technology; a means for generating advertisements based on user emotions using an emotion engine that recognizes user emotions; and a means for generating advertisements by inputting prompt sentences into a generation AI model. This enables AI to generate effective advertisements based on user emotions and insert them into appropriate content.

[0404] "AI-generated text, images, and videos" refers to text, still images, and video automatically generated using artificial intelligence technology.

[0405] "Means enabling advertising placement" refers to methods or technologies for inserting and displaying advertisements into specific media or content.

[0406] "Image and video generation AI" refers to systems and algorithms that automatically generate images and videos using artificial intelligence technology.

[0407] "Wearing the advertiser's brand" refers to people in the generated images and videos displaying a specific company's brand or logo.

[0408] "Logo on background, clothing, tattoo" refers to the insertion of a specific company's logo on the background, clothing, or tattoo in the generated image or video.

[0409] "Images that are in line with the lifestyle proposed by the advertising company" refers to images that reflect the lifestyle and values ​​that a particular company promotes.

[0410] "Existing digital advertising technologies" refers to online advertising delivery and targeting technologies currently in use.

[0411] "Secondary distribution on SNS" refers to users sharing, reposting, or spreading content on social networking services.

[0412] An "emotion engine" is software or algorithms that analyze a user's emotions and identify their emotional state.

[0413] A "generative AI model" is a model that uses artificial intelligence techniques to generate text, images, videos, etc. based on specific input.

[0414] A "prompt" is an instruction given to a generative AI model to generate a specific output.

[0415] The present invention is a system for placing advertisements for text, images, and videos generated by AI. This system includes a function for recognizing user emotions and generating advertisements according to those emotions. Specific embodiments of the system are described below.

[0416] System configuration

[0417] This system consists of three main components: a server, a device, and a user. The server has an emotion engine, a generative AI model, and an ad insertion function. The device has the function of collecting user behavior data and sending it to the server. Users access the system through their device and view content with ads.

[0418] Hardware and software used

[0419] Emotion engine: Software used to analyze user emotions, for example, using Microsoft® Azure®'s Emotion API.

[0420] Generative AI model: An AI model used to generate ads based on prompts, for example, OpenAI's GPT-4.

[0421] Ad Insertion: Software for inserting generated ads into AI-generated content.

[0422] System Operation

[0423] 1. Collecting user emotion data

[0424] A user accesses the system through a terminal.

[0425] The device collects user input data (text input, clicks, scrolling, etc.) and behavioral data (viewing time, page transitions, etc.) in real time and sends them to the server.

[0426] 2. Emotion Data Analysis

[0427] The server passes the received user data to the emotion engine.

[0428] The emotion engine analyzes the user's emotions and identifies their emotional state (such as joy, sadness, surprise, etc.).

[0429] 3. Create an ad-generating prompt

[0430] The server creates prompt sentences to input into the generative AI model based on the user's emotional state.

[0431] For example, if the user is expressing a happy emotion, a prompt sentence such as "Generate an advertisement that is appropriate when the user is expressing a happy emotion" is created.

[0432] 4. Ad generation

[0433] The server inputs a prompt sentence into the generative AI model.

[0434] Based on the prompt, the generative AI model generates advertising text, images, and videos that match the user's emotions.

[0435] The server receives the generated advertisement.

[0436] 5. Ad Insertion

[0437] The server inserts the generated advertisements into the AI-generated content (text, images, videos).

[0438] For example, generated advertising text is inserted into an AI-generated blog post in the appropriate location.

[0439] 6. Display of ad-supported content

[0440] The server transmits content with advertisements to the terminal.

[0441] The terminal displays the received content with advertisement to the user.

[0442] The user views the content with advertisements.

[0443] Examples of concrete examples and prompts

[0444] Examples:

[0445] When a user is reading a blog post, the emotion engine recognizes the user's emotion of joy.

[0446] The device collects data on the user's clicks and scrolls and sends it to the server.

[0447] The server uses an emotion engine to analyze that the user is expressing the emotion of "joy."

[0448] The server inputs a prompt statement to the generative AI model: "Generate an appropriate ad when the user is expressing the emotion of joy."

[0449] The generative AI model generates the ad text, "Spread your joy with this new smartphone!"

[0450] The server inserts this advertising text into the appropriate position in the blog post and sends it to the terminal.

[0451] The device displays blog posts with advertisements to the user.

[0452] Users browse blog posts with ads and see ads that match their emotions of pleasure.

[0453] Example prompt sentence:

[0454] "Generate ads that are appropriate when users are expressing the emotion of joy."

[0455] "Generate ads that are appropriate when the user is expressing sadness."

[0456] In this way, a system will be realized in which AI generates advertisements based on user emotions and inserts them into appropriate content.

[0457] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0458] Step 1: Collecting user emotion data

[0459] Input: A user accesses the system through a terminal and views content.

[0460] Specific operation: When a user reads a blog post or watches a video, the device collects user input data (text entry, clicks, scrolling, etc.) and behavioral data (viewing time, page transitions, etc.) in real time.

[0461] Output: Collected user data is sent from the device to the server.

[0462] Step 2: Analyze the emotion data

[0463] Input: User input and behavior data sent from the device.

[0464] Specific operation: The server passes the received user data to the emotion engine, which then analyzes the user's emotions using, for example, Microsoft Azure's Emotion API.

[0465] Output: The user's emotional state (happiness, sadness, surprise, etc.) obtained from the emotion engine is returned to the server.

[0466] Step 3: Create an ad-generating prompt

[0467] Input: The user's emotional state obtained from the emotion engine.

[0468] Specific operation: The server creates a prompt sentence to be input to the generative AI model based on the user's emotional state. For example, if the user is expressing joy, the server creates a prompt sentence such as "Please generate an advertisement that is appropriate when the user is expressing joy."

[0469] Output: The generated prompt is fed into the generative AI model.

[0470] Step 4: Generate Ads

[0471] Input: A prompt statement created by the server.

[0472] How it works: The server inputs a prompt into a generative AI model (such as OpenAI's GPT-4), which then generates advertising text, images, and videos that match the user's emotions based on the prompt.

[0473] Output: The generated ad is returned to the server.

[0474] Step 5: Inserting Ads

[0475] Input: The ad returned by the generative AI model.

[0476] Specific operation: The server inserts the generated advertisement into the AI-generated content (text, images, videos). For example, it inserts the generated advertisement text into the appropriate position in the AI-generated blog post.

[0477] Output: The content with the ads inserted is saved on the server.

[0478] Step 6: Displaying Ad-Supported Content

[0479] Input: Content with ads inserted.

[0480] Specific operation: The server sends content with advertisements to the terminal, and the terminal displays the received content with advertisements to the user.

[0481] Output: User views content with ads.

[0482] (Application example 1)

[0483] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0484] Conventional advertising systems have had difficulty generating ads in real time based on user emotions and inserting them into content at the appropriate time. Furthermore, it was not possible to integrate technology to recognize user emotions with ad generation technology, making it difficult to maximize advertising effectiveness. Furthermore, when advertising on mobile devices such as smartphones, there was a lack of a means to provide personalized ads based on user emotions.

[0485] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0486] In this invention, the server includes: means for enabling advertisements to be placed on text, images, and videos generated by AI; means for easily generating images that match the lifestyles proposed by advertisers, such as by having people in images / videos generated by image and video generation AI wear the advertiser's brand or add logos to the background, clothing, or tattoos; means for supporting advertising fee payments and targeting for secondary distribution on social media by utilizing existing digital advertising technology; means for generating advertisements based on user emotions using an emotion engine that recognizes user emotions; and means for recognizing user emotions in real time using a smartphone camera and microphone, generating advertisements based on those emotions, and inserting them into content. This makes it possible to generate personalized advertisements based on user emotions in real time and insert them into content at the appropriate time.

[0487] "AI-generated text, images, and videos" refers to text, still images, and videos that are automatically generated using artificial intelligence technology.

[0488] "Means enabling advertising" refers to methods or technologies that allow companies or individuals to insert advertisements into specific media or content.

[0489] "Image and video generation AI" refers to systems and algorithms that automatically generate images and videos using artificial intelligence technology.

[0490] "Wearing the advertiser's brand" refers to people or characters appearing in an advertisement displaying a specific company's brand or logo.

[0491] "Logo in background, clothing, or tattoo" refers to the insertion of a company logo into the background of a generated image or video, the clothing of a character, or a tattoo.

[0492] "Images that are in line with the lifestyle proposed by the advertising company" refers to images that reflect the lifestyle and values ​​that the company advocates.

[0493] "Existing digital advertising technologies" refers to online advertising technologies and methods currently in widespread use.

[0494] "Secondary distribution on social media" refers to users sharing, reposting, or spreading content on social networking services.

[0495] "Advertising payments" are fees paid by companies to place advertisements.

[0496] "Targeting" refers to the techniques and methods used to deliver advertisements to specific user groups or individuals.

[0497] An "emotion engine" is a system or algorithm that recognizes a user's emotions and generates appropriate responses or outputs based on those emotions.

[0498] "Smartphone camera and microphone" refers to the devices built into a smartphone for capturing video and audio.

[0499] "Real-time awareness" refers to the immediate detection and processing of ongoing events and situations.

[0500] "Inserting into content" refers to incorporating generated advertisements or information into the text, images, videos, etc. that users view.

[0501] A system for implementing the present invention has the following configuration.

[0502] System Configuration

[0503] 1. Server

[0504] AI generation module: Contains artificial intelligence models for generating text, images, and videos.

[0505] Advertisement module: Contains functionality for inserting advertisements into generated content.

[0506] Emotion Recognition Engine: Contains algorithms for recognizing user emotions in real time.

[0507] Ad generation engine: Includes an artificial intelligence model for generating ads based on user sentiment.

[0508] 2. Device (smartphone)

[0509] Camera and microphone: Devices for capturing your facial expressions and voice.

[0510] Emotion recognition software: Software that processes data obtained from the camera and microphone to recognize the user's emotions.

[0511] Advertisement display module: Has the function to insert and display the generated advertisements into the content.

[0512] Program processing explanation

[0513] server

[0514] AI generation module: Uses generative AI models to generate text, images, and videos, for example to automatically generate blog posts or news articles for users to view.

[0515] Advertisement module: Inserts company advertisements into the generated content. Advertisements can be inserted in the form of text, images, or videos.

[0516] Emotion recognition engine: Analyzes the user's facial and voice data sent from the smartphone and recognizes the user's emotions in real time. It uses libraries such as OpenCV and Keras.

[0517] Ad Generation Engine: Generates appropriate ads based on the recognized emotions. Uses the Hugging Face generative AI model to generate ad text based on prompts.

[0518] Device (smartphone)

[0519] Camera and microphone: Captures your facial expressions and voice and sends them to emotion recognition software.

[0520] Emotion recognition software: Processes data from the camera and microphone to recognize the user's emotions. The recognized emotion data is sent to the server.

[0521] Advertisement display module: Inserts and displays advertisements sent from the server into the content viewed by the user.

[0522] Specific examples

[0523] For example, when a user is reading a news article on their smartphone, the camera captures the user's facial expression and emotion recognition software detects "joy." This emotion data is sent to a server, and an ad generation engine generates ads related to "joy" (e.g., ads for new entertainment services). The ads are then inserted at the bottom of the news article and displayed to the user.

[0524] Prompt Sentence Examples

[0525] Generate ads that are appropriate when users are expressing the emotion of joy.

[0526] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0527] Step 1:

[0528] The device uses a camera and microphone to capture the user's facial expressions and voice.

[0529] Input: Real-time video and audio data of the user.

[0530] Output: Captured video and audio data.

[0531] What it does: Your phone's camera takes a picture of your face and your microphone records your voice.

[0532] Step 2:

[0533] The device uses emotion recognition software to analyze the captured video and audio data and recognize the user's emotions.

[0534] Input: Captured video and audio data.

[0535] Output: Recognized user emotion data (e.g., happy, sad, surprised, etc.).

[0536] How it works: Using OpenCV and Keras, facial features are extracted from video data and fed into an emotion recognition model to determine emotions. Audio data is analyzed in the same way.

[0537] Step 3:

[0538] The device transmits the recognized emotion data to the server.

[0539] Input: Recognized user emotion data.

[0540] Output: Emotion data sent to the server.

[0541] Specific operation: Emotion data is sent to the server via the network.

[0542] Step 4:

[0543] Based on the emotion data received by the server, an appropriate advertisement is generated using an advertisement generation engine.

[0544] Input: User emotion data.

[0545] Output: Ad text generated based on sentiment.

[0546] What it does: Uses the Hugging Face generation AI model to generate ad text based on the prompt.

[0547] Example prompt: "Generate an ad that is appropriate when the user is expressing the emotion of joy."

[0548] Step 5:

[0549] The server transmits the generated advertising text to the terminal.

[0550] Input: The generated ad text.

[0551] Output: The ad text sent to the device.

[0552] Specific operation: Sends advertising text to the device via the network.

[0553] Step 6:

[0554] The device inserts the advertising text received into the content the user is viewing.

[0555] Input: The ad text received and the content the user is viewing.

[0556] Output: Content with ads inserted.

[0557] What it does: Adds advertising text to the bottom of news articles and blog posts.

[0558] Step 7:

[0559] A user views content that has advertisements inserted into it.

[0560] Input: Content with ads inserted.

[0561] Output: User browsing behavior data.

[0562] What happens: A user scrolls through content on their phone and sees an ad.

[0563] Example 2

[0564] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0565] With conventional digital advertising systems, it was difficult to generate brand images that matched user emotions, making it impossible to maximize the effectiveness of advertising. Furthermore, there was a lack of a way to naturally add the advertising company's brand logo to the generated images and videos, resulting in a lack of visual consistency in the ads. Furthermore, there were insufficient methods for handling advertising fee payments and targeting for secondary distribution on social media.

[0566] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for enabling advertisements to be placed in text, images, and videos generated by AI; a means for easily generating images that match the lifestyle proposed by the advertising company by having people in images / videos generated by image and video generation AI wear the advertising company's brand or add logos to the background, clothing, or tattoos; a means for generating a brand image that corresponds to the user's emotions using an emotion engine that recognizes the user's emotions; and a means for supporting advertising fee payments and targeting for secondary distribution on social media by utilizing existing digital advertising technology. This makes it possible to generate effective advertisements that correspond to the user's emotions and maximize advertising effectiveness on social media while maintaining visual consistency.

[0567] "AI-generated text, images, and videos" refers to text, images, and videos that are automatically generated using artificial intelligence technology.

[0568] "Means enabling advertising" refers to methods and technologies for inserting advertising into generated text, images, and videos.

[0569] "Image and video generation AI" refers to systems and algorithms that automatically generate images and videos using artificial intelligence technology.

[0570] "Advertising company brand" refers to brand elements such as the brand name, logo, and slogan of the company placing the advertisement.

[0571] An "emotion engine" refers to a technology or system that analyzes a user's emotions and generates appropriate responses or outputs based on those emotions.

[0572] "Brand image" refers to the image or impression that consumers have of a particular brand.

[0573] "Digital advertising technology" refers to technologies and methods for delivering advertising through the internet and digital media.

[0574] "Secondary distribution on social media" refers to secondary distribution such as users sharing, reposting, and commenting on advertising content on social networking services.

[0575] "Targeting" refers to techniques and methods for delivering advertisements based on specific user demographics or behavioral patterns.

[0576] The present invention is a system for generating a brand image according to a user's emotions and maximizing advertising effectiveness. A specific embodiment of this system will be described below.

[0577] First, a user accesses the system using a web browser or a dedicated application. When the user opens the app on their smartphone, the system's home screen appears. The user then provides emotional data via a camera or microphone. For example, when the user smiles into the camera, the image is sent to the system.

[0578] The server uses an emotion engine (e.g., Affectiva or IBM Watson®) to analyze the user's emotion data. The server analyzes the user's smile and determines that the user feels a sense of security. The server then sends a prompt to a generative AI model (e.g., DALL-E or MidJourney) based on the analysis results. For example, the server sends a prompt such as, "Generate a brand image that emphasizes a sense of security."

[0579] The generative AI model generates images and videos based on the prompt text. The model generates images of landscapes and people that emphasize a sense of security. The server digitally adds the advertising company's logo to the generated images and videos. For example, the "RelaxCo" logo is added to a T-shirt worn by a person in the generated image.

[0580] Finally, the server provides the generated images and videos to the user. The user can view and download the generated images within the app. As a specific example, consider the case where the AI ​​adds the "RelaxCo" logo to a T-shirt worn by a person in a video while the user is relaxing. In this case, the emotion engine recognizes the user's relaxed emotion, and the AI ​​generates a brand image with a relaxed atmosphere that matches that emotion.

[0581] Example prompt sentence:

[0582] Generate an image that emphasizes the relaxed brand image when the user is relaxing. Add the "RelaxCo" logo to the T-shirt worn by the person in the generated image.

[0583] In this way, the server generates a brand image that corresponds to the user's emotions, thereby increasing the advertising effectiveness of advertisers. This system makes it possible to generate advertisements that take the user's emotions into consideration, maximizing the effectiveness of advertisements on SNS while maintaining visual consistency.

[0584] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0585] Step 1:

[0586] A user accesses the system. The user accesses the system using a web browser or a dedicated application. For example, when a user opens an app on a smartphone, the system's home screen is displayed. The input is the user's access information, and the output is the system's home screen.

[0587] Step 2:

[0588] The user provides emotional data. The user provides emotional data through a camera or microphone. For example, when the user smiles into the camera, the video is sent to the system. The input is the user's video and audio data, and the output is emotional data.

[0589] Step 3:

[0590] The server uses an emotion engine to analyze the user's emotions. The server uses an emotion engine (e.g., Affectiva or IBM Watson) to analyze the user's emotion data. For example, the server analyzes the user's smile and determines that the user is feeling a sense of security. The input is emotion data, and the output is the analysis result.

[0591] Step 4:

[0592] The server sends a prompt to the generative AI model. The server sends a prompt to the generative AI model (e.g., DALL-E or MidJourney) based on the analysis results. For example, it sends a prompt such as, "Generate a brand image that emphasizes a sense of security." The input is the analysis result, and the output is the prompt.

[0593] Step 5:

[0594] A generative AI model generates images and videos. A generative AI model generates images and videos based on a prompt. For example, a generative AI model generates images of landscapes or people that emphasize a sense of security. The input is the prompt, and the output is the generated image or video.

[0595] Step 6:

[0596] The server digitally adds the advertiser's logo to the generated image or video. For example, adding the "RelaxCo" logo to a T-shirt worn by a person in the generated image. The input is the generated image or video, and the output is the final image or video with the logo added.

[0597] Step 7:

[0598] The server provides the final image or video to the user. The server provides the final image or video to the user. For example, the user can view and download the image generated within the app. The input is the final image or video with the logo added, and the output is the image or video provided to the user.

[0599] (Application example 2)

[0600] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0601] With conventional advertising systems, it was difficult to generate and display brand images in real time that matched the user's emotions. It was also difficult to reflect the advertising company's brand logo or lifestyle in the generated images and videos, making it impossible to maximize advertising effectiveness. Furthermore, there was a lack of means to handle advertising fee payments and targeting for secondary distribution on social media.

[0602] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0603] In this invention, the server includes: means for enabling advertisements to be placed on text, images, and videos generated by AI; means for easily generating images that match the lifestyle proposed by the advertising company, such as by having people in the images / videos generated by the image / video generation AI wear the advertising company's brand or adding logos to the background, clothing, or tattoos; means for supporting advertising fee payments and targeting for secondary distribution on social media by utilizing existing digital advertising technology; means for recognizing user emotions in real time and generating brand images corresponding to those emotions; and means for displaying the generated brand images. This makes it possible to generate and display optimal brand images corresponding to user emotions in real time.

[0604] "AI-generated text, images, and videos" refers to text, still images, and video automatically generated using artificial intelligence technology.

[0605] "Means enabling advertising" refers to methods and technologies for inserting and displaying advertisements into generated text, images, and videos.

[0606] "Image and video generation AI" refers to systems and algorithms that automatically generate images and videos using artificial intelligence technology.

[0607] "Wearing the advertiser's brand" refers to a situation in which people in the generated images or videos are wearing the advertiser's brand logo or products.

[0608] "Logo on background, clothing, tattoos" means the digital addition of the advertiser's logo to the background, clothing, or tattoos in the generated image or video.

[0609] "Means to facilitate the generation of images that are consistent with the lifestyles proposed by the advertiser" refers to methods or technologies for generating images that reflect the particular lifestyles proposed by the advertiser.

[0610] "Reusing existing digital advertising technology" refers to building a new advertising system using already existing digital advertising technologies and methods.

[0611] "Means that also support payment of advertising fees and targeting for secondary distribution on social networking services" refers to a system that allows payment of advertising fees for resharing or reposting content on social networking services, as well as methods and technologies for delivering advertisements targeted at specific user groups.

[0612] "Means for recognizing user emotions in real time" refers to methods and technologies that analyze a user's facial expressions and behavior to instantly determine their emotions at that time.

[0613] "Means for generating brand images according to emotions" refers to methods or technologies for automatically generating optimal brand images based on recognized user emotions.

[0614] The "means for displaying the generated brand image" refers to a method or technology for visually presenting the generated brand image to the user.

[0615] A system for implementing this invention has the following configuration: The server includes means for enabling advertisements to be placed on text, images, and videos generated by AI, means for easily generating images that match the lifestyle proposed by the advertising company, such as having people in images / videos generated by the image / video generation AI wear the advertising company's brand or adding logos to the background, clothing, or tattoos, means for handling advertising fee payments and targeting for secondary distribution on SNS by utilizing existing digital advertising technology, means for recognizing user emotions in real time and generating brand images according to those emotions, and means for displaying the generated brand images.

[0616] Hardware and software used

[0617] Hardware: Smartphone camera

[0618] Software: OpenCV, EmotionRecognizer library, ImageGenerationAI library

[0619] Data processing and calculation

[0620] The server captures video in real time using the smartphone camera. The captured video is then analyzed using the EmotionRecognizer library to recognize the user's emotions. Based on the results of this emotion recognition, the server generates prompts to be input into the generative AI model. For example, if the user is relaxed, the server generates a prompt such as, "A brand image that suits when the user is relaxed."

[0621] Next, the server uses the ImageGenerationAI library to generate a brand image based on the generated prompt. This brand image is optimized for the user's emotions, emphasizing, for example, a sense of relaxation. The generated brand image is then displayed on the smartphone screen.

[0622] Specific examples

[0623] For example, when the user is relaxed, a brand image that emphasizes a sense of relaxation is generated and displayed, and when the user is in a happy mood, a brand image that emphasizes a happy mood is generated and displayed.

[0624] Prompt Sentence Examples

[0625] "A brand image that suits users when they are relaxed"

[0626] "A brand image that suits users when they're in a happy mood"

[0627] In this way, it is possible to generate an optimal brand image in real time according to the user's emotions and display it as an advertisement.

[0628] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0629] Step 1:

[0630] The server captures video in real time using the smartphone's camera.

[0631] Input: Smartphone camera image

[0632] Output: Captured video frames

[0633] Specific operation: The smartphone camera is activated and captures the user's video in real time. The captured video frames are sent to the server.

[0634] Step 2:

[0635] The server analyzes the captured video frames using the EmotionRecognizer library to recognize the user's emotions.

[0636] Input: Captured video frames

[0637] Output: Recognized user emotion (e.g., relaxed, happy)

[0638] What it does: The server uses the EmotionRecognizer library to analyze the user's facial expressions in the video frames and identify their emotions, which are then used in the next step.

[0639] Step 3:

[0640] The server generates prompt sentences to input into the generative AI model based on the recognized emotions.

[0641] Input: Perceived user emotion

[0642] Output: Prompt sentence (e.g., "Brand image that suits the user when they are relaxed")

[0643] Specific operation: The server generates a prompt sentence corresponding to the recognized emotion. For example, if the user is relaxed, the server generates a prompt sentence such as "A brand image that suits when the user is relaxed."

[0644] Step 4:

[0645] The server uses the ImageGenerationAI library to generate a brand image based on the generated prompt text.

[0646] Input: prompt statement

[0647] Output: Generated brand image (image)

[0648] Specific operation: The server inputs the prompt sentence into the generative AI model to generate a brand image that is optimized for the user's emotions.

[0649] Step 5:

[0650] The server displays the generated brand image on the smartphone screen.

[0651] Input: Generated brand image

[0652] Output: Brand image displayed on a smartphone screen

[0653] How it works: The server sends the generated brand image to the smartphone and displays it on the user's screen, allowing the user to see the brand image in real time according to their emotions.

[0654] Example 3

[0655] Next, a description will be given of a third embodiment of the third embodiment. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0656] Conventional digital advertising systems were unable to fully utilize user behavioral and emotional data, limiting the effectiveness of targeted advertising. They also faced the challenge of being unable to handle advertising fees or targeting for secondary distribution on social media. Furthermore, it was difficult to generate ads that matched the user's emotions.

[0657] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0658] In this invention, the server includes a data collection means, a data analysis means, an emotion recognition means, an advertisement generation means, an advertisement distribution means, a means for enabling advertisement placement in AI-generated text, images, and videos, a means for easily generating images that match the lifestyle proposed by the advertiser by having people in the images / videos generated by the image / video generation AI wear the advertiser's brand, or by adding logos to the background, clothing, or tattoos, and a means for supporting advertising fee payments and targeting for secondary distribution on SNS by utilizing existing digital advertising technology. This enables the generation and distribution of effective targeted advertisements using user behavioral and emotional data.

[0659] "Data collection means" refers to the means used to collect user behavioral data and profile data from social media platforms.

[0660] "Data analysis means" refers to the means for analyzing collected data and identifying users' interests and concerns.

[0661] An "emotion recognition means" is a means for recognizing emotions from user posts and comments.

[0662] "Advertisement generation means" means for generating targeted advertisements based on the user's interests and emotions.

[0663] "Advertising distribution means" refers to the means for distributing the generated advertisements to the SNS platform.

[0664] "Means enabling advertising on text, images, and videos generated by AI" refers to means for placing advertisements on content generated by a generative AI model.

[0665] "Means to make it easier to generate images that are in line with the lifestyle proposed by the advertiser, such as having people in images / videos generated by image and video generation AI wear the advertiser's brand, or having logos in the background, clothing, or tattoos" refers to a means of generating content that is in line with the advertiser's brand and lifestyle by reflecting the advertiser's brand image in the AI's learning data.

[0666] "Method of utilizing existing digital advertising technology to enable payment of advertising fees and targeting for secondary distribution on social media" refers to a method of utilizing existing digital advertising technology to enable payment of advertising fees and targeting for secondary distribution on social media.

[0667] This invention is a system that generates and distributes targeted advertisements by utilizing user behavior data and emotion data on social networking sites. Specific embodiments of this system are described below.

[0668] Hardware and software used

[0669] Server: Collects data, analyzes, generates advertisements, and delivers advertisements. Specifically, it uses cloud services (e.g., Amazon Web Services, Google (registered trademark) Cloud Platform).

[0670] Device: The device that users use to access SNS. This includes smartphones and PCs.

[0671] Software: Social media platforms (e.g., Facebook, Twitter), emotion engines (e.g., IBM Watson Tone Analyzer), generative AI models (e.g., OpenAI GPT-4).

[0672] Data collection

[0673] The server collects user behavior data (e.g., likes, shares, comments) and profile data (e.g., age, gender, interests) from the social media platform via API, thereby obtaining basic data to understand the user's interests.

[0674] Data analysis

[0675] The server stores the collected data in a database and analyzes it. Specifically, it scores the user's level of interest in a particular product or service. For example, if a user "likes" a "new smartphone," the server sets the user's interest level for that product high.

[0676] emotion recognition

[0677] The server uses an emotion engine to recognize emotions from user posts and comments. For example, if a user posts, "I'm so happy I got my new smartphone!", the server recognizes the emotion "happy." This emotion data is then used to generate advertisements.

[0678] Ad Generation

[0679] The server uses a generative AI model to generate targeted ads based on the user's interests and emotions. Specifically, the user's interest and emotion data is input into the generative AI model, which then generates ad copy based on that data. For example, if a user is excited about a "new smartphone," the server generates ad copy such as "Enjoy a new experience with this smartphone!"

[0680] Ad serving

[0681] The server delivers the generated advertisements to the social media platform. Specifically, the generated advertisements are displayed in the user's feed via the social media platform's advertising API. For example, the generated smartphone advertisements are displayed while the user is browsing the social media.

[0682] Examples of concrete examples and prompts

[0683] Examples:

[0684] User behavior data: User A "likes" a "new smartphone" on social media.

[0685] Emotion data: User A expresses the emotion "excitement" in a post about a "new smartphone."

[0686] Example prompt sentence:

[0687] If User A "likes" a "new smartphone" on social media and expresses excitement, what kind of targeted ads should be generated for that user?

[0688] This system can generate and deliver more effective targeted advertisements by combining user behavior data and emotional data. For example, if user A is excited, the effectiveness of the advertisement can be enhanced by emphasizing an advertisement for a "new smartphone" in line with that emotion. The flow of the identification process in Example 3 will be described with reference to FIG. 21.

[0689] Step 1:

[0690] Data collection

[0691] Input: User behavior data (e.g., likes, shares, comments) and profile data (e.g., age, gender, interests) from social media platforms.

[0692] How it works: The server sends a request through the social media platform's API to obtain user behavioral data and profile data.

[0693] Output: Collected user behavior and profile data is stored in a database.

[0694] Step 2:

[0695] Data analysis

[0696] Input: User behavioral and profile data stored in a database.

[0697] What it does: The server retrieves data from the database, analyzes it, and scores how interested the user is in a particular product or service.

[0698] Output: Scoring data that indicates user interests.

[0699] Step 3:

[0700] emotion recognition

[0701] Input: User posts and comments.

[0702] Specific operation: The server sends the user's post to the emotion engine, which then extracts emotions (e.g., excitement, joy, sadness) from the post.

[0703] Output: Extracted emotion data.

[0704] Step 4:

[0705] Ad Generation

[0706] Input: User interest and emotion data.

[0707] Specific operation: The server inputs user interest data and emotion data into the generated AI model, and the model generates advertising copy based on that data.

[0708] Output: Generated targeted ad copy.

[0709] Step 5:

[0710] Ad serving

[0711] Input: Generated targeting ad copy.

[0712] Specific operation: The server displays the generated advertisement in the user's feed through the social media platform's advertising API.

[0713] Output: Targeted ads displayed in the user's feed.

[0714] In this way, the system leverages user behavioral and emotional data to generate and deliver effective targeted ads.

[0715] (Application example 3)

[0716] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0717] Conventional digital advertising technologies provided targeted advertising based on user behavioral and profile data, but did not generate ads based on user emotions. Furthermore, there were insufficient methods for paying advertising fees and targeting secondary distribution on social media. Furthermore, there were also insufficient methods for displaying ads in real time through applications installed on smartphones. This limited the effectiveness of advertising and made it difficult to provide optimal ads based on users' interests and emotions.

[0718] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0719] In this invention, the server includes: means for enabling advertisements to be placed on text, images, and videos generated by AI; means for easily generating images that match the lifestyles proposed by advertisers, such as by having people in images / videos generated by the image / video generation AI wear the advertiser's brand or adding logos to the background, clothing, or tattoos; means for supporting advertising fee payments and targeting for secondary distribution on social media by utilizing existing digital advertising technology; means for recognizing user emotions using an emotion engine and generating targeted advertisements based on those emotions; and means for collecting user behavioral data and profile data through an application installed on a smartphone and displaying advertisements in real time. This makes it possible to generate optimal targeted advertisements based on the user's behavioral data and emotions and display them in real time.

[0720] "AI" is an abbreviation for artificial intelligence, a technology that enables computer systems to imitate human intelligence to learn, reason, recognize, and make judgments.

[0721] "Text" refers to information expressed in the form of letters or sentences.

[0722] An "image" is a still image that represents visual information.

[0723] "Video" is a medium that expresses movement by playing a series of images along a time axis.

[0724] "Advertising" refers to the procedures and actions required to place an advertisement in a medium.

[0725] "Image generation AI" is a technology that uses artificial intelligence to generate new images.

[0726] "Video" refers to a medium for expressing moving visual information.

[0727] A "person" is an object that represents the appearance or shape of a human being.

[0728] A "brand" is a name, logo, or image that identifies a particular company or product.

[0729] "Background" refers to the part of an image or video that is located behind the main subject.

[0730] "Clothing" refers to fabric products worn by humans.

[0731] A "tattoo" is a pattern or design created by injecting ink into the skin.

[0732] A "logo" is a designed symbol or letter that identifies a company or brand.

[0733] "Lifestyle" refers to people's lifestyles, values, and behavioral patterns.

[0734] "Digital advertising technology" refers to technology for delivering advertisements using the Internet and digital media.

[0735] "Secondary distribution" refers to a product being re-released on the market after going through primary distribution.

[0736] "Advertising Payment" means the fee paid for placing an advertisement.

[0737] "Targeting" is a method of delivering advertisements to specific user groups.

[0738] An "emotion engine" is a technology that recognizes a user's emotions and generates an appropriate response based on those emotions.

[0739] A "smartphone" is a multi-functional mobile device that, in addition to the functions of a mobile phone, can also connect to the Internet and use applications.

[0740] "Behavioral Data" refers to information about the actions you take online and offline.

[0741] "Profile data" refers to data that compiles information such as a user's attributes, interests, and behavioral history.

[0742] "Real-time" means that data and information are processed immediately and results are reflected immediately.

[0743] The system for implementing this invention includes a server, a smartphone, an emotion engine, and an advertisement generation AI. Details of each component and their operation will be described below.

[0744] server

[0745] The server collects user behavioral data and profile data and generates targeted advertisements based on this data. The server obtains user behavioral data through SNS APIs and stores it in a database. It also links the emotion engine with ad generation AI to generate advertisements based on user emotions.

[0746] Smartphone

[0747] The smartphone functions as a user interface and displays advertisements in real time. The application installed on the smartphone receives advertisements sent from the server and displays them to the user. It also collects user behavior data and sends it to the server.

[0748] Emotion Engine

[0749] The emotion engine analyzes users' social media posts and behavioral data to recognize their emotions. The emotion engine uses natural language processing technology to analyze text data and classify the user's emotions. For example, if a user posts, "I want a new smartphone," the emotion engine will recognize "excitement."

[0750] Ad generation AI

[0751] The ad generation AI generates optimally targeted ads based on the user's emotions and behavioral data recognized by the emotion engine. The ad generation AI uses a generative AI model to create advertising content tailored to the user's emotions. For example, if a user expresses "excitement," it generates an ad for the latest smartphone.

[0752] Specific examples

[0753] If a user posts on social media that they want a new smartphone, the emotion engine recognizes the excitement and the ad generation AI generates ads for the latest smartphones that match that emotion. The ads are then displayed to users in real time through an application installed on their smartphone.

[0754] Prompt Sentence Examples

[0755] If a user posts on social media that they want a new smartphone, the emotion engine will recognize the "excitement" and the AI ​​will generate an ad for the latest smartphone that matches that emotion.

[0756] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0757] Step 1:

[0758] The server collects user behavior data through the SNS API. Specifically, it obtains data such as user posts, comments, and likes. The input is user behavior data from the SNS API, and the output is behavior data stored in the server's database. The server periodically collects this data and updates it in real time.

[0759] Step 2:

[0760] The server uses an emotion engine to analyze the collected behavioral data and recognize the user's emotions. Specifically, it uses natural language processing technology to analyze text data and classify the user's emotions. The input is the behavioral data stored in the server's database, and the output is the recognized user's emotion data. The server periodically runs the emotion engine to obtain the latest emotion data.

[0761] Step 3:

[0762] The server uses ad generation AI to generate targeted ads based on the recognized user emotions and behavioral data. Specifically, it uses a generative AI model to create ad content that matches the user's emotions. The input is the recognized user emotional data and behavioral data, and the output is the generated ad content. The server runs the ad generation AI to generate the optimal ad.

[0763] Step 4:

[0764] The server transmits the generated advertising content to the smartphone. Specifically, the advertising content is transmitted to the application installed on the smartphone by push notification. The input is the generated advertising content, and the output is the advertising content transmitted to the smartphone. The server transmits the advertising content in real time.

[0765] Step 5:

[0766] The smartphone displays the received advertising content to the user. Specifically, it displays a pop-up advertisement through an application. The input is the advertising content sent from the server, and the output is the advertisement displayed to the user. The smartphone immediately displays the advertisement and collects the user's response.

[0767] Step 6:

[0768] The smartphone sends user reaction data to the server. Specifically, it collects reaction data such as clicks, likes, and comments on ads and sends it to the server. The input is the user reaction data, and the output is the reaction data sent to the server. The smartphone collects user reactions in real time and sends them to the server.

[0769] Step 7:

[0770] The server stores the received user response data in a database and uses it to generate the next advertisement. Specifically, it analyzes the user response data and evaluates the effectiveness of the advertisement. The input is the user response data sent from the smartphone, and the output is the evaluation data stored in the database. The server continuously evaluates the effectiveness of the advertisement and reflects it in generating the next advertisement.

[0771] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0772] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0773] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are listed.

[0774] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0775] [Second embodiment]

[0776] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0777] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0778] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0779] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0780] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0781] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0782] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0783] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0784] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0785] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0786] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0787] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0788] "Example 1"

[0789] As one embodiment of the present invention, a system is provided that enables advertising in text, images, and videos generated by AI. Specifically, the system has the function of inserting advertising from advertising companies into text, images, and videos generated by AI. For example, it is possible to insert advertising text from advertising companies into blog articles generated by AI.

[0790] "Example 2"

[0791] In addition, the system also provides a function that makes it easier to generate images that match the lifestyles proposed by advertisers, such as having people in images / videos generated by the image / video generation AI wear the advertiser's brand, or adding logos to backgrounds, clothing, or tattoos. Specifically, it has a function that digitally adds the advertiser's logo to people in images / videos generated by the AI. For example, it is possible to digitally add the advertiser's logo to a T-shirt worn by a person in an AI-generated video.

[0792] "Example 3"

[0793] Furthermore, by utilizing existing digital advertising technology, the system also provides functionality for targeting and payment of advertising fees for secondary distribution on social media. Specifically, it has the ability to generate targeted advertisements based on user behavioral and profile data on social media. For example, it is possible to target advertisements from companies selling a particular product based on information that a user has "liked" a product on social media.

[0794] The processing flow of each embodiment will be described below.

[0795] "Example 1"

[0796] Step 1: AI generates text, images, and videos. For example, AI generates a blog post.

[0797] Step 2: Insert the sponsor's advertisement into the generated text, images, and videos. For example, insert the sponsor's advertisement text into the generated blog post.

[0798] "Example 2"

[0799] Step 1: AI generates images / videos. For example, AI generates a video.

[0800] Step 2: Digitally add the advertiser's logo to the person in the generated image / video. For example, digitally add the advertiser's logo to a T-shirt worn by the person in the generated video.

[0801] "Example 3"

[0802] Step 1: Collect user behavioral data and profile data on social media. For example, collect information on whether a user has "liked" a specific product on social media.

[0803] Step 2: Generate targeted ads based on the collected data, for example, targeting ads for companies selling products that users have "liked."

[0804] Example 1

[0805] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0806] Conventional advertising systems have difficulty inserting appropriate ads into AI-generated content, making it impossible to maximize advertising effectiveness. Furthermore, there is a lack of technology to increase the relevance of generated content and ads, making it difficult to effectively provide targeted ads based on users' interests. Furthermore, there is a lack of methods for handling advertising fee payments and targeting for secondary distribution on social media.

[0807] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes a means for a user to input a prompt sentence, a means for the server to generate content using a generation AI model, a means for the server to insert advertisements into the generated content, a means for the server to provide the final content to the user, a means for making it easier to generate images that match the lifestyle proposed by the advertiser by having people in the images / videos generated by the image / video generation AI wear the advertiser's brand, adding logos to the background, clothing, or tattoos, and so on, and a means for supporting advertising fee payments and targeting for secondary distribution on SNS by utilizing existing digital advertising technology. This makes it possible to insert appropriate advertisements into the generated content and effectively provide targeted advertisements based on the user's interests. Furthermore, it is also possible to support advertising fee payments and targeting for secondary distribution on SNS.

[0808] A "user" is an individual or entity that utilizes the system to enter prompts and receive generated content.

[0809] A "prompt sentence" is text that a user inputs to specifically instruct the system on the content they wish to generate.

[0810] "Server" refers to a computer system that generates content using a generative AI model, inserts advertisements, and provides the final content to users.

[0811] A "generative AI model" is an artificial intelligence model that generates content such as text, images, and videos based on prompts entered by users.

[0812] "Content" refers to information such as text, images, and videos generated by a generative AI model.

[0813] An "advertisement" is information such as text, images, and videos inserted into content to promote products or services offered by the advertising company.

[0814] "Advertiser" means a company that provides advertisements and inserts those advertisements into content through the system.

[0815] "Targeted advertising" refers to advertising that is optimized for a specific user based on the user's behavioral data and profile data.

[0816] "SNS" is an abbreviation for social networking service, an online platform for users to share information and interact with each other.

[0817] "Secondary distribution" refers to the re-sharing of generated content through social media and other means.

[0818] "Digital advertising technology" refers to technology for delivering advertisements on online platforms and measuring their effectiveness.

[0819] This invention relates to a system for inserting advertisements into text, images, and videos generated using a generative AI model. In this system, a user inputs a prompt sentence, a server generates content using a generative AI model, inserts advertisements, and provides the final content.

[0820] Hardware and software used

[0821] The server is a high-performance computing system for running generative AI models. Specifically, it uses the following hardware and software:

[0822] Hardware: A server with a powerful CPU, GPU, and sufficient memory

[0823] Software: Generative AI models (e.g., OpenAI's GPT-4 and DALL-E), natural language processing (NLP) libraries, database management systems

[0824] Data processing and calculation

[0825] The server receives the prompt entered by the user and uses the generative AI model to:

[0826] 1. Parse the prompt:

[0827] The server analyzes the prompt sentence entered by the user and determines the content to be generated.

[0828] Example: A user types, "Generate blog posts about summer travel."

[0829] 2. Content generation:

[0830] The server uses a generative AI model to generate text, images, and videos based on the prompt.

[0831] Example: A server generates a "summer travel blog post" that includes information about recommended travel spots and activities.

[0832] 3. Ad Insertion:

[0833] The server inserts appropriate advertisements into the generated content, performing topic analysis and relevance evaluation of the content to select the most suitable advertisement.

[0834] Example: Inserting advertising text into generated blog posts that reads, "Take advantage of our travel agency's special deals this summer!"

[0835] 4. Final Content Delivery:

[0836] The server generates the final content with the advertisements inserted and provides it to the user.

[0837] Example: A server displays a blog post with an ad inserted to a user, who then views the post.

[0838] Examples of concrete examples and prompts

[0839] Examples:

[0840] When a user enters the prompt "Generate a blog post about autumn leaves," the server generates a blog post about autumn leaves and inserts advertising text into it that reads, "Take beautiful photos with this camera manufacturer's new model during the autumn foliage season!"

[0841] Example prompt sentence:

[0842] "Generate blog posts about summer travel"

[0843] "Generate a review video for a new smartphone"

[0844] "Generate images of healthy recipes"

[0845] In this way, a system is realized in which the user inputs a prompt sentence, the server generates content using a generative AI model, inserts appropriate advertisements, and provides the final content.

[0846] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0847] Step 1:

[0848] The user inputs a prompt statement. The user inputs a prompt statement that specifically specifies the content they want to generate through the system interface. The input prompt statement is sent to the server. In a specific operation, the user inputs, "Generate a blog post about summer travel."

[0849] Input: The prompt text entered by the user

[0850] Output: The prompt sent to the server

[0851] Step 2:

[0852] The server receives the prompt and generates content using a generative AI model. The server analyzes the prompt and generates text, images, and videos using a generative AI model (for example, OpenAI's GPT-4 or DALL-E). Specifically, the server generates a "summer travel blog post."

[0853] Input: The prompt text sent by the user

[0854] Output: Generated text, images, and videos

[0855] Step 3:

[0856] The server inserts advertisements into the generated content. The server performs topic analysis and relevance assessment of the generated content, and selects appropriate advertisements from the advertising company's advertisement database. The selected advertisements are inserted at appropriate positions within the content. Specifically, the server inserts advertisement text into the generated blog post, such as "We recommend this travel agency's special plan for your summer trip!"

[0857] Input: Generated text, images, videos

[0858] Output: Text, images, and videos with ads inserted

[0859] Step 4:

[0860] The server provides the final content to the user. The server generates the final content with the advertisement inserted and provides it to the user. The user can view this content through the system interface. Specifically, the server displays the blog post with the advertisement inserted to the user.

[0861] Input: Text, images, and videos with ads inserted

[0862] Output: The final content that is delivered to the user

[0863] (Application example 1)

[0864] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0865] With conventional advertising systems, it was difficult to effectively insert ads into AI-generated text, images, and videos. Furthermore, the process of selecting and inserting appropriate ads into user-generated content was often done manually, resulting in inefficiency. Furthermore, the effectiveness of ads was not adequately measured, making it difficult to accurately determine the effectiveness of each ad. To solve these issues, an efficient advertising system utilizing AI is needed.

[0866] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0867] In this invention, the server includes a means for enabling advertisements to be placed in text, images, and videos generated by AI, a means for AI to select appropriate advertisements and insert them into content when users upload content generated by users to the application, and a means for incorporating an advertisement effectiveness measurement function and analyzing which advertisements received how many clicks and views. This makes it possible to efficiently insert advertisements using AI and accurately measure their effectiveness.

[0868] "AI-generated text, images, and videos" refers to text, still images, and videos that are automatically generated using artificial intelligence technology.

[0869] "Means enabling advertising" refers to methods or technologies that allow companies or individuals to insert advertisements into specific media or content.

[0870] "Image and video generation AI" refers to systems and algorithms that automatically generate images and videos using artificial intelligence technology.

[0871] "Wearing the advertiser's brand" refers to people in the generated images and videos displaying a specific company's brand or logo.

[0872] "Logo on background, clothing, tattoo" refers to the insertion of a specific company's logo on the background, clothing, or tattoo in the generated image or video.

[0873] "Images that are in line with the lifestyle proposed by the advertising company" refers to images that reflect the lifestyle and values ​​that a particular company promotes.

[0874] "Existing digital advertising technologies" refers to digital advertising technologies and methods that are currently in widespread use.

[0875] A "social networking service" is an online platform that allows people to share information and interact with each other over the Internet.

[0876] "Advertising fees for secondary distribution" refers to the payment of advertising fees that occurs when an advertisement is shared or reused again after its initial distribution.

[0877] "Targeting" refers to the method of delivering advertisements to specific user groups or market segments.

[0878] "User-generated content" means text, images or videos that are created by members of the public and uploaded to online platforms.

[0879] "Uploading to an Application" means sending and storing content created by a user to a specific software or platform.

[0880] "Selecting the right ad" refers to choosing the most relevant and effective ad for a particular content or user.

[0881] The "advertising effectiveness measurement function" is a function that analyzes the number of clicks and views an advertisement receives and evaluates its effectiveness.

[0882] The following system configuration will be described as an embodiment of the present invention.

[0883] System Configuration

[0884] This system includes a server, a user device, and an AI model. The server provides a means for placing advertisements in AI-generated text, images, and videos. The user device uploads user-generated content and provides an interface for the AI ​​to select appropriate advertisements and insert them into the content. The AI ​​model executes an algorithm to insert advertisements into the generated content and measure their effectiveness.

[0885] Hardware and software used

[0886] Hardware: Smartphones, servers

[0887] Software: Python, OpenAI API

[0888] Data processing and calculation

[0889] The server receives user-generated content and uses the AI ​​model to select appropriate ads. Specifically, the process involves the following steps:

[0890] 1. User input: The user inputs a prompt for the content they want to generate into the user terminal.

[0891] 2. Content Generation: The server uses the OpenAI API to generate text content based on the user's prompts.

[0892] 3. Advertisement selection: The server selects pre-prepared advertisement text for the generated content.

[0893] 4. Advertisement insertion: The server inserts the selected advertisements into the generated content.

[0894] 5. Effectiveness measurement: The server analyzes the number of clicks and views of the advertisement and measures its effectiveness.

[0895] Specific examples

[0896] User Input

[0897] The user enters a prompt like this:

[0898] "Generate a review article for a new smartphone"

[0899] "Generate articles about the latest fashion trends"

[0900] "Generate healthy eating advice"

[0901] "Generate a guide to the best places to visit in your travel destination."

[0902] Content Generation

[0903] The server uses the OpenAI API to generate text content like this:

[0904] "This phone is very powerful and the camera quality is excellent."

[0905] "This year's fashion trends are characterized by colorful accessories and simple designs."

[0906] "A balanced diet and moderate exercise are important for maintaining a healthy diet."

[0907] "The best travel destinations are those with beautiful scenery and rich culture."

[0908] Ad selection and insertion

[0909] The server inserts advertisements into the generated content, such as:

[0910] "Check this product out!"

[0911] Effectiveness measurement

[0912] The server analyzes the number of clicks and views the ad received and measures its effectiveness, allowing the user to accurately understand the effectiveness of the ad and use this information to improve the next ad placement.

[0913] In this way, an efficient advertising system utilizing AI will be realized.

[0914] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0915] Step 1:

[0916] The user inputs a prompt statement for the content that he or she wants to generate into the user terminal.

[0917] Input: The prompt text entered by the user (e.g., "Generate a review of a new smartphone.")

[0918] Output: Prompt sent from the user's terminal to the server

[0919] Specific operation: The user opens the application on their smartphone, enters the prompt for the content they want to generate, and presses the send button. The user's device then sends this prompt to the server.

[0920] Step 2:

[0921] The server uses the OpenAI API to generate text content based on the user's prompts.

[0922] Input: Prompt sent from the user's terminal

[0923] Output: Generated text content (e.g., "This smartphone is very powerful and the camera quality is excellent.")

[0924] Specific operation: The server sends the received prompt to the OpenAI API, and the AI ​​model generates text content based on the prompt. The generated text content is returned to the server.

[0925] Step 3:

[0926] The server selects pre-prepared advertising text for the generated content.

[0927] Input: Generated text content, ad database

[0928] Output: Selected ad text (e.g., "Check out this product!")

[0929] Specific operation: The server analyzes the generated text content and selects the most relevant advertising text from the advertising database.

[0930] Step 4:

[0931] The server inserts the selected advertisements into the generated content.

[0932] Input: Generated text content, selected advertising text

[0933] Output: The final content with the ad inserted (e.g., "This phone is very powerful and has an excellent camera.\n\n---\nAd: Check out this product!\n---")

[0934] Specific operation: The server inserts the selected advertising text into the appropriate position of the generated text content to generate the final content.

[0935] Step 5:

[0936] The server analyzes the number of clicks and views of the advertisements to measure their effectiveness.

[0937] Input: Final content with ad insertion, user behavior data

[0938] Output: Ad effectiveness measurement results (e.g., number of clicks, number of views)

[0939] How it works: The server delivers content with ads inserted, records the number of clicks and views by users, and analyzes this data to measure the effectiveness of the ads.

[0940] In this way, an efficient advertising system utilizing AI will be realized.

[0941] Example 2

[0942] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0943] With conventional digital advertising systems, it was difficult to effectively reflect the advertiser's brand in the generated images and videos. Inserting ads into user-generated content was also time-consuming and costly, and the accuracy of targeted advertising was insufficient. Furthermore, there was no system in place for paying advertising fees for secondary distribution on online platforms.

[0944] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for a user to input a prompt text, a means for the server to receive the prompt text and call a generative AI model, a means for the server to acquire the generated images and videos and add the logo of the advertising company, a means for the server to send the processed images and videos to the user, and a means for supporting payment of advertising fees and targeting for secondary distribution on online platforms by utilizing existing digital advertising technology. This enables users to easily generate images and videos incorporating the brand of the advertising company and improve the accuracy of targeted advertising. A system for payment of advertising fees for secondary distribution on online platforms is also established.

[0945] A "user" is an individual or entity that utilizes the system to input prompts and receive generated images and videos.

[0946] A "prompt" is text that a user inputs into a generative AI model, describing the content of the image or video they want to generate.

[0947] The "server" is a computer system that receives prompt text from the user, invokes the generative AI model, retrieves the generated images and videos, processes them, and finally sends them to the user.

[0948] A "generative AI model" is an artificial intelligence model that generates images and videos based on prompt text.

[0949] A "logo" is a digital image or text that represents the advertiser's brand and is added to the generated image or video.

[0950] "Sponsor" means a company or organization that sponsors an advertisement and whose brand or logo is to be reflected in the generated images and videos.

[0951] "Targeted advertising" refers to advertising that is optimized for a specific user based on the user's behavioral data and profile data.

[0952] An "online platform" is a general term for services and applications provided over the Internet, and is a place where users can share content they generate.

[0953] "Secondary distribution" refers to the redistribution of generated content through other users or platforms after its initial release.

[0954] "Advertising payment" refers to the fee paid by an advertiser for an advertisement being displayed or clicked on.

[0955] This invention is a system that allows users to input prompt text, generates images and videos using a generative AI model, and adds the sponsor's logo. A specific embodiment of this system is described below.

[0956] Hardware and software used

[0957] Hardware: Servers, terminals

[0958] Software: Generative AI models (e.g., OpenAI's DALL-E, Stable Diffusion), image editing software (e.g., Adobe Photoshop API)

[0959] Program processing

[0960] The user enters a prompt statement

[0961] The user inputs a prompt into the input form on the device that describes the image or video they want to generate. For example, they input a prompt such as "Generate an image of a man wearing a blue shirt jogging in a park."

[0962] The server receives the prompt.

[0963] The prompt text entered by the user is sent from the terminal to the server, which receives it and prepares to proceed with the next process.

[0964] The server invokes the generative AI model

[0965] The server passes the received prompt sentence to the generative AI model, which then begins calculations to generate images and videos based on the prompt sentence.

[0966] The server retrieves the generated images and videos.

[0967] Once the generative AI model has finished generating images and videos based on the prompt, the server retrieves the generated results, which are temporarily stored on the server.

[0968] The server adds the advertiser's logo

[0969] The server digitally adds the advertiser's logo to the people in the generated images and videos, for example, by adding the advertiser's logo to a T-shirt worn by the people in the generated images, using image editing software (e.g., Adobe Photoshop API).

[0970] The server sends the processed images and videos to the user.

[0971] The server sends the images and videos with the logo added to them to the user, who can then view the processed images and videos on their device. The transmission is done using the HTTP protocol.

[0972] Specific examples

[0973] Prompt Sentence Examples

[0974] "Generate an image of a woman in a red dress walking on the beach"

[0975] "Generate a video of a man in a black suit giving a presentation in an office."

[0976] In this way, users can easily create and review images and videos incorporating the advertiser's brand. This system will improve the accuracy of targeted advertising and will also establish a system for paying advertising fees for secondary distribution on online platforms.

[0977] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0978] Step 1:

[0979] The user enters a prompt statement

[0980] The user inputs a prompt that describes the image or video they want to generate into the input form on their device. For example, they might input a prompt such as "Generate an image of a man in a blue shirt jogging in a park." The input prompt is then sent from the device to the server.

[0981] Step 2:

[0982] The server receives the prompt.

[0983] The server receives the prompt sent from the device, parses the received prompt, and prepares to pass it to the generative AI model. The input is the prompt, and the output is the parsed prompt.

[0984] Step 3:

[0985] The server invokes the generative AI model

[0986] The server passes the parsed prompt sentence to the generative AI model, which then begins calculations to generate images and videos based on the prompt sentence. The input is the parsed prompt sentence, and the output is the generated image or video data.

[0987] Step 4:

[0988] The server retrieves the generated images and videos.

[0989] Once the generative AI model has finished generating images and videos based on the prompt, the server retrieves the generated results. The generated images and videos are temporarily stored on the server. The input is the generated results from the generative AI model, and the output is the image and video data stored on the server.

[0990] Step 5:

[0991] The server adds the advertiser's logo

[0992] The server digitally adds the sponsor's logo to the people in the generated images and videos. For example, the sponsor's logo is added to a T-shirt worn by a person in the generated image. This process is performed using image editing software (e.g., Adobe Photoshop API). The input is the image or video data stored on the server, and the output is the image or video data with the logo added.

[0993] Step 6:

[0994] The server sends the processed images and videos to the user.

[0995] The server sends the images or videos with the logo added to the user, who can then view the processed images or videos on their device. Transmission is performed using the HTTP protocol. The input is the image or video data with the logo added, and the output is the processed image or video sent to the user's device.

[0996] (Application example 2)

[0997] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0998] With conventional advertising methods, it was difficult to automatically add specific brand logos or lifestyle elements to images and videos taken by users. Furthermore, there was a lack of effective ways to expose brands within the generated content, and there was a need for improved accuracy in targeted advertising.

[0999] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for enabling advertisements to be placed on text, images, and videos generated by AI; a means for making it easier to generate images that match the lifestyle proposed by the advertising company by having people in images / videos generated by image and video generation AI wear the advertising company's brand or add logos to backgrounds, clothing, or tattoos; and a means for automatically adding specific brand logos and lifestyle elements to images and videos taken by users. This makes it possible to effectively expose brands to content taken by users.

[1000] "AI-generated text, images, and videos" refers to text, still images, and video automatically generated using artificial intelligence technology.

[1001] "Means enabling advertising placement" refers to the methods and technologies that allow advertisers to place advertisements in specific media.

[1002] "Image and video generation AI" refers to systems and algorithms that use artificial intelligence technology to automatically generate still images and videos.

[1003] "Advertising company brand" refers to the trademark, logo, and brand image of the company placing the advertisement.

[1004] "Logo on background, clothing, tattoos" refers to the digital addition of a logo to a background, person's clothing, or tattoos in a generated image or video.

[1005] "Lifestyle images" are images created based on a particular lifestyle or values.

[1006] "Existing digital advertising technologies" refers to online advertising technologies and methods currently in widespread use.

[1007] "Secondary distribution on social media" refers to users sharing or reposting content on social networking services.

[1008] "Targeted advertising" refers to the technology and methods used to deliver advertisements optimized for specific user groups or individuals.

[1009] "User behavior data" refers to data about the actions and behavior of users online.

[1010] "Profile Data" refers to data about a user's attributes, interests, and concerns.

[1011] "Training data" refers to a data set used to train an artificial intelligence.

[1012] "Brand image" refers to the image or perception that consumers have of a particular brand.

[1013] A system for implementing this invention has the following configuration: A server includes means for enabling advertisements to be placed on text, images, and videos generated by AI, means for making it easier to generate images that fit the lifestyle proposed by the advertising company by having people in the images / videos generated by the image / video generation AI wear the advertising company's brand or add logos to the background, clothing, or tattoos, and means for automatically adding specific brand logos and lifestyle elements to images and videos taken by the user.

[1014] Hardware and software used

[1015] Hardware: Smartphone (iOS or Android)

[1016] Software: Image and video generation AI (e.g., OpenAI's DALL-E), image processing library (e.g., OpenCV), cloud storage (e.g., AWS S3)

[1017] Data processing and calculation

[1018] Uploading images and videos

[1019] Users upload images and videos they have taken using their smartphones to the application, and the uploaded data is stored in cloud storage (AWS S3).

[1020] AI analysis and logo addition

[1021] The server uses an image and video generation AI (DALL-E) to analyze uploaded images and videos. Based on the analysis results, it adds the specified brand logo and lifestyle elements. It uses an image processing library (OpenCV) to place the logo and background elements in the appropriate position.

[1022] Preview and save the generated results

[1023] It shows the user a preview of the generated image or video, and if the user is satisfied, it saves the generated result to cloud storage and provides a download link.

[1024] Specific examples

[1025] scenario

[1026] Consider a case where a user wants to add the logo of a particular sports brand to a photo they take with their friends.

[1027] Prompt Sentence Examples

[1028] "Take a photo with your friends and add a sports brand logo to your T-shirt."

[1029] "Add a beverage brand advertisement in the background of this photo."

[1030] "Please add a clothing brand logo to the jacket worn by the person in this video."

[1031] "Change the background of this image to a beach and add a surfing brand logo."

[1032] In this way, it is possible to effectively expose the brand to content shot by users.

[1033] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1034] Step 1:

[1035] Users upload images and videos taken using their smartphones to the application. The input is the images and videos taken by the user, and the output is the data stored in cloud storage (AWS S3). Specifically, the user taps the upload button on the application and selects the images or videos from the file selection screen.

[1036] Step 2:

[1037] The server retrieves uploaded images and videos from cloud storage. The input is the images and videos stored in cloud storage, and the output is data in a format that can be processed within the server. Specifically, the server downloads the data using the AWS S3 API.

[1038] Step 3:

[1039] The server uses the image and video generation AI (DALL-E) to analyze the acquired images and videos. The input is images and videos in a format that can be processed within the server, and the output is the analysis results. Specifically, the server calls the DALL-E API and analyzes the content of the images and videos.

[1040] Step 4:

[1041] The server adds the specified brand logo and lifestyle elements based on the analysis results. The input is the analysis results and the data of the brand logo and lifestyle elements to be added, and the output is an image or video with the logo or elements added. Specifically, the server uses an image processing library (OpenCV) to place the logo and elements in the appropriate position.

[1042] Step 5:

[1043] The server displays a preview of the generated image or video to the user. The input is the image or video with the logo or elements added, and the output is the preview screen displayed on the user's smartphone. Specifically, the server sends the generated data to the user's smartphone, and the application displays the preview screen.

[1044] Step 6:

[1045] If the user is satisfied with the generated results, the server saves the results in cloud storage and provides a download link. The input is the user's satisfaction confirmation and the generated image or video, and the output is the data stored in cloud storage and a download link. Specifically, the user taps the save button in the application, and the server saves the data in AWS S3 and generates a download link.

[1046] Example 3

[1047] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1048] Conventional digital advertising systems have had difficulty effectively utilizing user behavioral and profile data to generate targeted ads. They also lacked a mechanism for measuring the effectiveness of generated ads and providing feedback for the next ad generation. Furthermore, there were limited means for automatically generating ad content, resulting in insufficient personalization of ads.

[1049] The identification process by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means. In this invention, the server includes means for collecting user behavioral data and profile data, means for storing the collected data in a database, means for analyzing the stored data and generating targeted advertisements, means for automatically generating advertisement content using a generative AI model, means for delivering the generated advertisements, and means for measuring the effectiveness of the advertisements and providing feedback for the next advertisement generation. This makes it possible to effectively utilize user behavioral data and profile data to generate and deliver personalized targeted advertisements. Furthermore, measuring the effectiveness of the advertisements and providing feedback for the next advertisement generation can improve the accuracy and effectiveness of the advertisements.

[1050] "User behavioral data" refers to data regarding actions such as "likes," shares, and comments taken by users on social media platforms.

[1051] "Profile data" refers to data that includes personal information and attribute information such as a user's age, gender, and interests.

[1052] A "database" is a system for storing and managing collected user behavioral data and profile data.

[1053] "Analysis" is the process of analyzing user interests and behavioral patterns based on stored data.

[1054] "Targeted advertising" refers to advertising that is personalized for specific users based on analysis results.

[1055] A "generative AI model" is a model that uses artificial intelligence technology to automatically generate advertising content.

[1056] A "prompt" is an instruction entered into a generative AI model, and is text that prompts the generation of advertising copy.

[1057] "Serving ads" is the process of sending the generated ads to social media platforms and displaying them in users' feeds.

[1058] "Effectiveness measurement" is the process of collecting data such as the number of clicks and conversion rates of delivered advertisements to evaluate their effectiveness.

[1059] "Feedback" is the process of reflecting the results of effectiveness measurement in the generation of the next advertisement.

[1060] MODE FOR CARRYING OUT THE INVENTION

[1061] This invention relates to a system for generating and delivering targeted advertisements by utilizing user behavior data and profile data. Specific embodiments of this system are described below.

[1062] 1. Program Generation

[1063] The server collects user behavioral data and profile data from SNS platforms (e.g., SNS service A, SNS service B) and generates a program that generates targeted advertisements based on that data. This program automatically creates the content of the advertisements using a generative AI model (e.g., generative AI model A).

[1064] 2. Program processing explanation

[1065] The server collects user behavior data (e.g., likes, shares, comments) and profile data (e.g., age, gender, interests) from the social networking platform. This data is stored in databases (e.g., Database A, Database B).

[1066] The server then analyzes the collected data and generates targeted ads based on specific conditions. For example, if a user "likes" a particular product, it generates ads for companies selling that product. This ad generation uses a generative AI model (e.g., Generative AI Model A).

[1067] The generated advertisements are sent to social media platforms and displayed in users' feeds. To measure the effectiveness of the advertisements, the servers also collect and analyze data such as the number of clicks and conversion rates.

[1068] 3. Examples of concrete examples and prompts

[1069] As a concrete example, consider the case where a user "likes" a "smartphone" on a social networking site. Based on this information, the server generates advertisements for companies that sell smartphones.

[1070] Example prompt sentence:

[1071] Generate ads for companies selling smartphones based on users' "likes" on social media. Include the latest smartphone features, prices, and purchase links in the ads.

[1072] By feeding this prompt into a generative AI model, the following ad is generated:

[1073] Introducing the latest smartphone! High-performance camera, long battery life, and a great price. Click the Buy Now link to find out more!

[1074] In this way, the server utilizes user behavior data on the SNS to provide a system that effectively generates and distributes targeted advertisements. This system improves the effectiveness of advertisements by promoting personalization of advertisements and displaying advertisements based on the user's interests. In addition, measurement of advertisement effectiveness and feedback improves the accuracy of next advertisement generation. The flow of the identification process in Example 3 will be described with reference to FIG. 15.

[1075] Step 1: Collect user behavior data

[1076] The server collects user behavior data from the social media platform. Specifically, it obtains data such as posts that users have "liked," content that they have shared, and comments on through the API. It receives the data obtained from the social media platform's API as input and converts the behavior data into a format that can be stored in a database as output.

[1077] Step 2: Save your data

[1078] The server stores the collected behavioral data in a database. The database contains information such as the user ID, type of behavior, content ID of the behavior, and timestamp. The server receives the behavioral data collected in step 1 as input and stores it in the database as output.

[1079] Step 3: Analyze the data

[1080] The server analyzes the stored data, using data mining techniques and machine learning algorithms. For example, if a user has many "likes" for products in a particular category, it can be determined that the user has a high level of interest in that category. The server receives the behavioral data stored in the database as input and obtains the analysis results as output.

[1081] Step 4: Generate targeted ads

[1082] The server generates targeted ads based on the analysis results. At this time, it uses a generative AI model to automatically generate the ad content. Specifically, it inputs the prompt text into the generative AI model to generate ad copy. It receives the analysis results and the prompt text as input, and obtains the generated ad copy as output.

[1083] Example prompt sentence:

[1084] Generate ads for companies selling smartphones based on users' "likes" on social media. Include the latest smartphone features, prices, and purchase links in the ads.

[1085] Step 5: Serving Ads

[1086] The server sends the generated advertisement to the social media platform, which displays the advertisement in the user's feed. The server receives the generated advertisement copy as input and sends it as output to the social media platform.

[1087] Step 6: Measurement and feedback

[1088] The server measures the effectiveness of the delivered advertisements. Specifically, it collects and analyzes data such as the number of ad clicks, conversion rate, and duration of visit. Based on this data, it evaluates the effectiveness of the advertisements and provides feedback for the generation of the next advertisement. It receives the effectiveness measurement data obtained from the SNS platform as input, and obtains the analysis results and feedback information as output.

[1089] (Application example 3)

[1090] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1091] With conventional digital advertising technology, it was difficult to effectively utilize user behavior data on social media to generate targeted ads. Furthermore, there was a lack of a way to properly display the generated ads on users' smartphones, limiting the effectiveness of the ads. Furthermore, it was difficult to generate images and videos that reflected the brand image of the advertising company.

[1092] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes a means for enabling advertisements to be placed on text, images, and videos generated by AI; a means for easily generating images that match the lifestyle proposed by the advertising company by having people in images / videos generated by image and video generation AI wear the advertising company's brand or add logos to the background, clothing, or tattoos; a means for supporting advertising fee payments and targeting for secondary distribution on social media by utilizing existing digital advertising technology; and a means for generating targeted advertisements based on user behavioral data and profile data and displaying them on smartphones. This enables the generation and display of effective targeted advertisements based on user interests.

[1093] "AI" is an abbreviation for artificial intelligence, a technology that allows computers to imitate human intelligence and learn and reason.

[1094] "Text" refers to information expressed in the form of letters or sentences.

[1095] An "image" is static visual information that can be perceived visually.

[1096] "Video" refers to visual information that expresses movement by displaying a series of images at regular time intervals.

[1097] "Advertising" refers to the procedures and actions for placing an advertisement in a specific medium.

[1098] "Image generation AI" refers to systems and algorithms that generate images using artificial intelligence technology.

[1099] "People in video" refers to human characters or models that appear in the generated images or videos.

[1100] A "brand" is a name, logo, or image that identifies a particular company or product.

[1101] "Background" refers to the area behind the main subject in an image or video.

[1102] "Clothing" refers to the clothing and accessories worn by humans.

[1103] A "tattoo" is a pattern or design created by injecting ink into the skin.

[1104] A "logo" is a design or mark that symbolizes a company or brand.

[1105] A "lifestyle" is a pattern of behavior and values ​​that an individual or group chooses to live in their daily lives.

[1106] "Digital advertising technology" refers to technology for delivering advertisements using the Internet and digital devices.

[1107] "SNS" is an abbreviation for social networking services, a platform for people to interact with each other on the Internet.

[1108] "Secondary distribution" refers to a product being re-released on the market after going through primary distribution.

[1109] "Advertising Payment" means the fee paid for placing an advertisement.

[1110] "Targeting" is a method of delivering advertisements to specific user groups.

[1111] "Behavioral Data" refers to information about the actions you take online and offline.

[1112] "Profile data" refers to information including a user's attributes, interests, behavioral history, etc.

[1113] A "smartphone" is a highly functional mobile phone that can connect to the Internet and use applications.

[1114] A system for implementing this invention has the following configuration: The server includes means for enabling advertisements to be placed on text, images, and videos generated by AI, means for easily generating images that match the lifestyle proposed by the advertising company, such as by having people in the images / videos generated by the image / video generation AI wear the advertising company's brand or adding logos to the background, clothing, or tattoos, means for handling advertising fee payments and targeting for secondary distribution on SNS by utilizing existing digital advertising technology, and means for generating targeted advertisements based on user behavioral data and profile data and displaying them on smartphones.

[1115] Hardware and software used

[1116] Hardware: Servers, smartphones

[1117] Software: Python, SNS API, scikit-learn, TfidfVectorizer, linear_kernel

[1118] Data processing and calculation

[1119] The server uses the SNS API to obtain user behavior data. Specifically, it collects data on products and posts that users have "liked" on SNS. This data reflects the user's interests and concerns, and is therefore important information for generating targeted advertisements.

[1120] Next, the server uses TfidfVectorizer to vectorize the user's "like" data and the ad data, converting the text data into numerical data for easier calculations. It then uses linear_kernel to calculate the cosine similarity between the user's "like" data and the ad data, allowing it to select the ad that most closely matches the user's interests.

[1121] The selected ads are then displayed on smartphones, allowing users to view ads based on their interests, increasing the effectiveness of the ads.

[1122] Specific examples

[1123] For example, if a user "likes" a "new fashion item" on a social networking site, that data is sent to a server. The server uses that data to generate fashion-related advertisements and displays them on the user's smartphone. These advertisements include information about new products and sales from the brand the user "liked."

[1124] Prompt Sentence Examples

[1125] "Generate targeted ads based on products that users have liked on social media. User ID is "user123"."

[1126] In this manner, the present invention enables the generation and display of effective targeted advertisements based on user interests.

[1127] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1128] Step 1:

[1129] The server uses the SNS API to obtain user behavior data. Specifically, it collects data on products and posts that users have "liked" on the SNS. The input is the user ID, and the output is the user's "like" data. This data reflects the user's interests and concerns, and is therefore important information for generating targeted advertisements.

[1130] Step 2:

[1131] The server vectorizes the retrieved user "like" data using TfidfVectorizer. The input is the user "like" data, and the output is the vectorized user data. This process converts text data into numerical data, making it easier to perform calculations.

[1132] Step 3:

[1133] The server retrieves the ad descriptions from the ad database and vectorizes them using TfidfVectorizer as well. The input is the ad database, and the output is the vectorized ad data. This prepares the ad content for comparison with user interests.

[1134] Step 4:

[1135] The server uses the linear_kernel to calculate the cosine similarity between the vectorized user "like" data and the ad data. The input is the vectorized user data and ad data, and the output is the similarity score. This process allows us to select the ad that is closest to the user's interests.

[1136] Step 5:

[1137] The server selects the most suitable advertisement based on the similarity score and generates data to display on the smartphone. The input is the similarity score, and the output is the selected advertisement data. This advertisement data includes information on new products and sales from brands that the user has "liked."

[1138] Step 6:

[1139] The terminal (smartphone) receives the advertising data sent from the server and displays it to the user. The input is the selected advertising data, and the output is the advertisement displayed on the user's smartphone screen. This allows the user to view advertisements based on their interests.

[1140] In this way, the server and the terminal work together to generate targeted advertisements based on user behavior data and display them effectively.

[1141] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1142] "Example 1"

[1143] One embodiment of the present invention is a system in which a means for placing advertisements on AI-generated text, images, and videos includes a function for generating advertisements based on the user's emotions using an emotion engine that recognizes the user's emotions. Specifically, the emotion engine recognizes the user's emotions, and the AI ​​generates advertisements based on those emotions. For example, if the user expresses joy, the AI ​​generates an advertisement that emphasizes the joy in line with that emotion.

[1144] "Example 2"

[1145] In addition, some systems use an emotion engine that recognizes user emotions to generate brand images that correspond to the user's emotions, making it easier to generate images that match the lifestyle proposed by the advertiser, such as having people in the images / videos generated by the image / video generation AI wear the advertiser's brand, or adding logos to the background, clothing, or tattoos. Specifically, the emotion engine recognizes the user's emotions, and the AI ​​generates a brand image based on those emotions. For example, if the user expresses a sense of security, the AI ​​generates a brand image that emphasizes that sense of security, matching that emotion.

[1146] "Example 3"

[1147] Furthermore, by utilizing existing digital advertising technology, there are also systems that use an emotion engine that recognizes user emotions to generate targeted ads based on the user's emotions, which can also support advertising fee payments and targeting for secondary distribution on social media. Specifically, the emotion engine recognizes the user's emotions, and the AI ​​generates targeted ads based on those emotions. For example, if the user expresses excitement, the AI ​​generates targeted ads that emphasize that excitement.

[1148] The processing flow of each embodiment will be described below.

[1149] "Example 1"

[1150] Step 1: The emotion engine recognizes the user's emotion.

[1151] Step 2: The AI ​​generates an ad based on the recognized emotion.

[1152] Step 3: The generated advertisement is displayed using AI-generated text, images, and videos.

[1153] "Example 2"

[1154] Step 1: The emotion engine recognizes the user's emotion.

[1155] Step 2: AI generates a brand image based on the recognized emotion.

[1156] Step 3: Based on the generated brand image, the AI ​​generates images that fit the lifestyle proposed by the advertiser, such as people in the image / video wearing the advertiser's brand, adding logos to the background, clothing, or tattoos.

[1157] "Example 3"

[1158] Step 1: The emotion engine recognizes the user's emotion.

[1159] Step 2: Based on the emotions recognized, the AI ​​generates targeted ads.

[1160] Step 3: Based on the generated targeted advertisements, existing digital advertising technology is utilized to handle advertising payments and targeting for secondary distribution on social media.

[1161] Example 1

[1162] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1163] With conventional advertising systems, it was difficult to insert effective ads into AI-generated content. Furthermore, there was a lack of means to generate ads that corresponded to the user's emotions, making it impossible to provide ads that corresponded to the user's interests. Furthermore, there were insufficient means to handle advertising fee payments and targeting for secondary distribution on social media.

[1164] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. In this invention, the server includes: a means for enabling advertisements to be placed in text, images, and videos generated by AI; a means for easily generating images that match the lifestyle proposed by the advertising company by having people in images / videos generated by image and video generation AI wear the advertising company's brand or add logos to the background, clothing, or tattoos; a means for supporting advertising fee payments and targeting for secondary distribution on social media by utilizing existing digital advertising technology; a means for generating advertisements based on user emotions using an emotion engine that recognizes user emotions; and a means for generating advertisements by inputting prompt sentences into a generation AI model. This enables AI to generate effective advertisements based on user emotions and insert them into appropriate content.

[1165] "AI-generated text, images, and videos" refers to text, still images, and video automatically generated using artificial intelligence technology.

[1166] "Means enabling advertising placement" refers to methods or technologies for inserting and displaying advertisements into specific media or content.

[1167] "Image and video generation AI" refers to systems and algorithms that automatically generate images and videos using artificial intelligence technology.

[1168] "Wearing the advertiser's brand" refers to people in the generated images and videos displaying a specific company's brand or logo.

[1169] "Logo on background, clothing, tattoo" refers to the insertion of a specific company's logo on the background, clothing, or tattoo in the generated image or video.

[1170] "Images that are in line with the lifestyle proposed by the advertising company" refers to images that reflect the lifestyle and values ​​that a particular company promotes.

[1171] "Existing digital advertising technologies" refers to online advertising delivery and targeting technologies currently in use.

[1172] "Secondary distribution on SNS" refers to users sharing, reposting, or spreading content on social networking services.

[1173] An "emotion engine" is software or algorithms that analyze a user's emotions and identify their emotional state.

[1174] A "generative AI model" is a model that uses artificial intelligence techniques to generate text, images, videos, etc. based on specific input.

[1175] A "prompt" is an instruction given to a generative AI model to generate a specific output.

[1176] The present invention is a system for placing advertisements for text, images, and videos generated by AI. This system includes a function for recognizing user emotions and generating advertisements according to those emotions. Specific embodiments of the system are described below.

[1177] System configuration

[1178] This system consists of three main components: a server, a device, and a user. The server has an emotion engine, a generative AI model, and an ad insertion function. The device has the function of collecting user behavior data and sending it to the server. Users access the system through their device and view content with ads.

[1179] Hardware and software used

[1180] Emotion engine: Software used to analyze user emotions, for example, using Microsoft Azure's Emotion API.

[1181] Generative AI model: An AI model used to generate ads based on prompts, for example, OpenAI's GPT-4.

[1182] Ad Insertion: Software for inserting generated ads into AI-generated content.

[1183] System Operation

[1184] 1. Collecting user emotion data

[1185] A user accesses the system through a terminal.

[1186] The device collects user input data (text input, clicks, scrolling, etc.) and behavioral data (viewing time, page transitions, etc.) in real time and sends them to the server.

[1187] 2. Emotion Data Analysis

[1188] The server passes the received user data to the emotion engine.

[1189] The emotion engine analyzes the user's emotions and identifies their emotional state (such as joy, sadness, surprise, etc.).

[1190] 3. Create an ad-generating prompt

[1191] The server creates prompt sentences to input into the generative AI model based on the user's emotional state.

[1192] For example, if the user is expressing a happy emotion, a prompt sentence such as "Generate an advertisement that is appropriate when the user is expressing a happy emotion" is created.

[1193] 4. Ad generation

[1194] The server inputs a prompt sentence into the generative AI model.

[1195] Based on the prompt, the generative AI model generates advertising text, images, and videos that match the user's emotions.

[1196] The server receives the generated advertisement.

[1197] 5. Ad Insertion

[1198] The server inserts the generated advertisements into the AI-generated content (text, images, videos).

[1199] For example, generated advertising text is inserted into an AI-generated blog post in the appropriate location.

[1200] 6. Display of ad-supported content

[1201] The server transmits content with advertisements to the terminal.

[1202] The terminal displays the received content with advertisement to the user.

[1203] The user views the content with advertisements.

[1204] Examples of concrete examples and prompts

[1205] Examples:

[1206] When a user is reading a blog post, the emotion engine recognizes the user's emotion of joy.

[1207] The device collects data on the user's clicks and scrolls and sends it to the server.

[1208] The server uses an emotion engine to analyze that the user is expressing the emotion of "joy."

[1209] The server inputs a prompt statement to the generative AI model: "Generate an appropriate ad when the user is expressing the emotion of joy."

[1210] The generative AI model generates the ad text, "Spread your joy with this new smartphone!"

[1211] The server inserts this advertising text into the appropriate position in the blog post and sends it to the terminal.

[1212] The device displays blog posts with advertisements to the user.

[1213] Users browse blog posts with ads and see ads that match their emotions of pleasure.

[1214] Example prompt sentence:

[1215] "Generate ads that are appropriate when users are expressing the emotion of joy."

[1216] "Generate ads that are appropriate when the user is expressing sadness."

[1217] In this way, a system will be realized in which AI generates advertisements based on user emotions and inserts them into appropriate content.

[1218] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1219] Step 1: Collecting user emotion data

[1220] Input: A user accesses the system through a terminal and views content.

[1221] Specific operation: When a user reads a blog post or watches a video, the device collects user input data (text entry, clicks, scrolling, etc.) and behavioral data (viewing time, page transitions, etc.) in real time.

[1222] Output: Collected user data is sent from the device to the server.

[1223] Step 2: Analyze the emotion data

[1224] Input: User input and behavior data sent from the device.

[1225] Specific operation: The server passes the received user data to the emotion engine, which then analyzes the user's emotions using, for example, Microsoft Azure's Emotion API.

[1226] Output: The user's emotional state (happiness, sadness, surprise, etc.) obtained from the emotion engine is returned to the server.

[1227] Step 3: Create an ad-generating prompt

[1228] Input: The user's emotional state obtained from the emotion engine.

[1229] Specific operation: The server creates a prompt sentence to be input to the generative AI model based on the user's emotional state. For example, if the user is expressing joy, the server creates a prompt sentence such as "Please generate an advertisement that is appropriate when the user is expressing joy."

[1230] Output: The generated prompt is fed into the generative AI model.

[1231] Step 4: Generate Ads

[1232] Input: A prompt statement created by the server.

[1233] How it works: The server inputs a prompt into a generative AI model (such as OpenAI's GPT-4), which then generates advertising text, images, and videos that match the user's emotions based on the prompt.

[1234] Output: The generated ad is returned to the server.

[1235] Step 5: Inserting Ads

[1236] Input: The ad returned by the generative AI model.

[1237] Specific operation: The server inserts the generated advertisement into the AI-generated content (text, images, videos). For example, it inserts the generated advertisement text into the appropriate position in the AI-generated blog post.

[1238] Output: The content with the ads inserted is saved on the server.

[1239] Step 6: Displaying Ad-Supported Content

[1240] Input: Content with ads inserted.

[1241] Specific operation: The server sends content with advertisements to the terminal, and the terminal displays the received content with advertisements to the user.

[1242] Output: User views content with ads.

[1243] (Application example 1)

[1244] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1245] Conventional advertising systems have had difficulty generating ads in real time based on user emotions and inserting them into content at the appropriate time. Furthermore, it was not possible to integrate technology to recognize user emotions with ad generation technology, making it difficult to maximize advertising effectiveness. Furthermore, when advertising on mobile devices such as smartphones, there was a lack of a means to provide personalized ads based on user emotions.

[1246] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1247] In this invention, the server includes: means for enabling advertisements to be placed on text, images, and videos generated by AI; means for easily generating images that match the lifestyles proposed by advertisers, such as by having people in images / videos generated by image and video generation AI wear the advertiser's brand or add logos to the background, clothing, or tattoos; means for supporting advertising fee payments and targeting for secondary distribution on social media by utilizing existing digital advertising technology; means for generating advertisements based on user emotions using an emotion engine that recognizes user emotions; and means for recognizing user emotions in real time using a smartphone camera and microphone, generating advertisements based on those emotions, and inserting them into content. This makes it possible to generate personalized advertisements based on user emotions in real time and insert them into content at the appropriate time.

[1248] "AI-generated text, images, and videos" refers to text, still images, and videos that are automatically generated using artificial intelligence technology.

[1249] "Means enabling advertising" refers to methods or technologies that allow companies or individuals to insert advertisements into specific media or content.

[1250] "Image and video generation AI" refers to systems and algorithms that automatically generate images and videos using artificial intelligence technology.

[1251] "Wearing the advertiser's brand" refers to people or characters appearing in an advertisement displaying a specific company's brand or logo.

[1252] "Logo in background, clothing, or tattoo" refers to the insertion of a company logo into the background of a generated image or video, the clothing of a character, or a tattoo.

[1253] "Images that are in line with the lifestyle proposed by the advertising company" refers to images that reflect the lifestyle and values ​​that the company advocates.

[1254] "Existing digital advertising technologies" refers to online advertising technologies and methods currently in widespread use.

[1255] "Secondary distribution on social media" refers to users sharing, reposting, or spreading content on social networking services.

[1256] "Advertising payments" are fees paid by companies to place advertisements.

[1257] "Targeting" refers to the techniques and methods used to deliver advertisements to specific user groups or individuals.

[1258] An "emotion engine" is a system or algorithm that recognizes a user's emotions and generates appropriate responses or outputs based on those emotions.

[1259] "Smartphone camera and microphone" refers to the devices built into a smartphone for capturing video and audio.

[1260] "Real-time awareness" refers to the immediate detection and processing of ongoing events and situations.

[1261] "Inserting into content" refers to incorporating generated advertisements or information into the text, images, videos, etc. that users view.

[1262] A system for implementing the present invention has the following configuration.

[1263] System Configuration

[1264] 1. Server

[1265] AI generation module: Contains artificial intelligence models for generating text, images, and videos.

[1266] Advertisement module: Contains functionality for inserting advertisements into generated content.

[1267] Emotion Recognition Engine: Contains algorithms for recognizing user emotions in real time.

[1268] Ad generation engine: Includes an artificial intelligence model for generating ads based on user sentiment.

[1269] 2. Device (smartphone)

[1270] Camera and microphone: Devices for capturing your facial expressions and voice.

[1271] Emotion recognition software: Software that processes data obtained from the camera and microphone to recognize the user's emotions.

[1272] Advertisement display module: Has the function to insert and display the generated advertisements into the content.

[1273] Program processing explanation

[1274] server

[1275] AI generation module: Uses generative AI models to generate text, images, and videos, for example to automatically generate blog posts or news articles for users to view.

[1276] Advertisement module: Inserts company advertisements into the generated content. Advertisements can be inserted in the form of text, images, or videos.

[1277] Emotion recognition engine: Analyzes the user's facial and voice data sent from the smartphone and recognizes the user's emotions in real time. It uses libraries such as OpenCV and Keras.

[1278] Ad Generation Engine: Generates appropriate ads based on the recognized emotions. Uses the Hugging Face generative AI model to generate ad text based on prompts.

[1279] Device (smartphone)

[1280] Camera and microphone: Captures your facial expressions and voice and sends them to emotion recognition software.

[1281] Emotion recognition software: Processes data from the camera and microphone to recognize the user's emotions. The recognized emotion data is sent to the server.

[1282] Advertisement display module: Inserts and displays advertisements sent from the server into the content viewed by the user.

[1283] Specific examples

[1284] For example, when a user is reading a news article on their smartphone, the camera captures the user's facial expression and emotion recognition software detects "joy." This emotion data is sent to a server, and an ad generation engine generates ads related to "joy" (e.g., ads for new entertainment services). The ads are then inserted at the bottom of the news article and displayed to the user.

[1285] Prompt Sentence Examples

[1286] Generate ads that are appropriate when users are expressing the emotion of joy.

[1287] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1288] Step 1:

[1289] The device uses a camera and microphone to capture the user's facial expressions and voice.

[1290] Input: Real-time video and audio data of the user.

[1291] Output: Captured video and audio data.

[1292] What it does: Your phone's camera takes a picture of your face and your microphone records your voice.

[1293] Step 2:

[1294] The device uses emotion recognition software to analyze the captured video and audio data and recognize the user's emotions.

[1295] Input: Captured video and audio data.

[1296] Output: Recognized user emotion data (e.g., happy, sad, surprised, etc.).

[1297] How it works: Using OpenCV and Keras, facial features are extracted from video data and fed into an emotion recognition model to determine emotions. Audio data is analyzed in the same way.

[1298] Step 3:

[1299] The device transmits the recognized emotion data to the server.

[1300] Input: Recognized user emotion data.

[1301] Output: Emotion data sent to the server.

[1302] Specific operation: Emotion data is sent to the server via the network.

[1303] Step 4:

[1304] Based on the emotion data received by the server, an appropriate advertisement is generated using an advertisement generation engine.

[1305] Input: User emotion data.

[1306] Output: Ad text generated based on sentiment.

[1307] What it does: Uses the Hugging Face generation AI model to generate ad text based on the prompt.

[1308] Example prompt: "Generate an ad that is appropriate when the user is expressing the emotion of joy."

[1309] Step 5:

[1310] The server transmits the generated advertising text to the terminal.

[1311] Input: The generated ad text.

[1312] Output: The ad text sent to the device.

[1313] Specific operation: Sends advertising text to the device via the network.

[1314] Step 6:

[1315] The device inserts the advertising text received into the content the user is viewing.

[1316] Input: The ad text received and the content the user is viewing.

[1317] Output: Content with ads inserted.

[1318] What it does: Adds advertising text to the bottom of news articles and blog posts.

[1319] Step 7:

[1320] A user views content that has advertisements inserted into it.

[1321] Input: Content with ads inserted.

[1322] Output: User browsing behavior data.

[1323] What happens: A user scrolls through content on their phone and sees an ad.

[1324] Example 2

[1325] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1326] With conventional digital advertising systems, it was difficult to generate brand images that matched user emotions, making it impossible to maximize the effectiveness of advertising. Furthermore, there was a lack of a way to naturally add the advertising company's brand logo to the generated images and videos, resulting in a lack of visual consistency in the ads. Furthermore, there were insufficient methods for handling advertising fee payments and targeting for secondary distribution on social media.

[1327] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for enabling advertisements to be placed in text, images, and videos generated by AI; a means for easily generating images that match the lifestyle proposed by the advertising company by having people in images / videos generated by image and video generation AI wear the advertising company's brand or add logos to the background, clothing, or tattoos; a means for generating a brand image that corresponds to the user's emotions using an emotion engine that recognizes the user's emotions; and a means for supporting advertising fee payments and targeting for secondary distribution on social media by utilizing existing digital advertising technology. This makes it possible to generate effective advertisements that correspond to the user's emotions and maximize advertising effectiveness on social media while maintaining visual consistency.

[1328] "AI-generated text, images, and videos" refers to text, images, and videos that are automatically generated using artificial intelligence technology.

[1329] "Means enabling advertising" refers to methods and technologies for inserting advertising into generated text, images, and videos.

[1330] "Image and video generation AI" refers to systems and algorithms that automatically generate images and videos using artificial intelligence technology.

[1331] "Advertising company brand" refers to brand elements such as the brand name, logo, and slogan of the company placing the advertisement.

[1332] An "emotion engine" refers to a technology or system that analyzes a user's emotions and generates appropriate responses or outputs based on those emotions.

[1333] "Brand image" refers to the image or impression that consumers have of a particular brand.

[1334] "Digital advertising technology" refers to technologies and methods for delivering advertising through the internet and digital media.

[1335] "Secondary distribution on social media" refers to secondary distribution such as users sharing, reposting, and commenting on advertising content on social networking services.

[1336] "Targeting" refers to techniques and methods for delivering advertisements based on specific user demographics or behavioral patterns.

[1337] The present invention is a system for generating a brand image according to a user's emotions and maximizing advertising effectiveness. A specific embodiment of this system will be described below.

[1338] First, a user accesses the system using a web browser or a dedicated application. When the user opens the app on their smartphone, the system's home screen appears. The user then provides emotional data via a camera or microphone. For example, when the user smiles into the camera, the image is sent to the system.

[1339] The server uses an emotion engine (e.g., Affectiva or IBM Watson) to analyze the user's emotional data. The server analyzes the user's smile and determines that the user feels a sense of security. The server then sends a prompt to a generative AI model (e.g., DALL-E or MidJourney) based on the analysis results. For example, the server sends a prompt such as, "Generate a brand image that emphasizes a sense of security."

[1340] The generative AI model generates images and videos based on the prompt text. The model generates images of landscapes and people that emphasize a sense of security. The server digitally adds the advertising company's logo to the generated images and videos. For example, the "RelaxCo" logo is added to a T-shirt worn by a person in the generated image.

[1341] Finally, the server provides the generated images and videos to the user. The user can view and download the generated images within the app. As a specific example, consider the case where the AI ​​adds the "RelaxCo" logo to a T-shirt worn by a person in a video while the user is relaxing. In this case, the emotion engine recognizes the user's relaxed emotion, and the AI ​​generates a brand image with a relaxed atmosphere that matches that emotion.

[1342] Example prompt sentence:

[1343] Generate an image that emphasizes the relaxed brand image when the user is relaxing. Add the "RelaxCo" logo to the T-shirt worn by the person in the generated image.

[1344] In this way, the server generates a brand image that corresponds to the user's emotions, thereby increasing the advertising effectiveness of advertisers. This system makes it possible to generate advertisements that take the user's emotions into consideration, maximizing the effectiveness of advertisements on SNS while maintaining visual consistency.

[1345] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1346] Step 1:

[1347] A user accesses the system. The user accesses the system using a web browser or a dedicated application. For example, when a user opens an app on a smartphone, the system's home screen is displayed. The input is the user's access information, and the output is the system's home screen.

[1348] Step 2:

[1349] The user provides emotional data. The user provides emotional data through a camera or microphone. For example, when the user smiles into the camera, the video is sent to the system. The input is the user's video and audio data, and the output is emotional data.

[1350] Step 3:

[1351] The server uses an emotion engine to analyze the user's emotions. The server uses an emotion engine (e.g., Affectiva or IBM Watson) to analyze the user's emotion data. For example, the server analyzes the user's smile and determines that the user is feeling a sense of security. The input is emotion data, and the output is the analysis result.

[1352] Step 4:

[1353] The server sends a prompt to the generative AI model. The server sends a prompt to the generative AI model (e.g., DALL-E or MidJourney) based on the analysis results. For example, it sends a prompt such as, "Generate a brand image that emphasizes a sense of security." The input is the analysis result, and the output is the prompt.

[1354] Step 5:

[1355] A generative AI model generates images and videos. A generative AI model generates images and videos based on a prompt. For example, a generative AI model generates images of landscapes or people that emphasize a sense of security. The input is the prompt, and the output is the generated image or video.

[1356] Step 6:

[1357] The server digitally adds the advertiser's logo to the generated image or video. For example, adding the "RelaxCo" logo to a T-shirt worn by a person in the generated image. The input is the generated image or video, and the output is the final image or video with the logo added.

[1358] Step 7:

[1359] The server provides the final image or video to the user. The server provides the final image or video to the user. For example, the user can view and download the image generated within the app. The input is the final image or video with the logo added, and the output is the image or video provided to the user.

[1360] (Application example 2)

[1361] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1362] With conventional advertising systems, it was difficult to generate and display brand images in real time that matched the user's emotions. It was also difficult to reflect the advertising company's brand logo or lifestyle in the generated images and videos, making it impossible to maximize advertising effectiveness. Furthermore, there was a lack of means to handle advertising fee payments and targeting for secondary distribution on social media.

[1363] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1364] In this invention, the server includes: means for enabling advertisements to be placed on text, images, and videos generated by AI; means for easily generating images that match the lifestyle proposed by the advertising company, such as by having people in the images / videos generated by the image / video generation AI wear the advertising company's brand or adding logos to the background, clothing, or tattoos; means for supporting advertising fee payments and targeting for secondary distribution on social media by utilizing existing digital advertising technology; means for recognizing user emotions in real time and generating brand images corresponding to those emotions; and means for displaying the generated brand images. This makes it possible to generate and display optimal brand images corresponding to user emotions in real time.

[1365] "AI-generated text, images, and videos" refers to text, still images, and video automatically generated using artificial intelligence technology.

[1366] "Means enabling advertising" refers to methods and technologies for inserting and displaying advertisements into generated text, images, and videos.

[1367] "Image and video generation AI" refers to systems and algorithms that automatically generate images and videos using artificial intelligence technology.

[1368] "Wearing the advertiser's brand" refers to a situation in which people in the generated images or videos are wearing the advertiser's brand logo or products.

[1369] "Logo on background, clothing, tattoos" means the digital addition of the advertiser's logo to the background, clothing, or tattoos in the generated image or video.

[1370] "Means to facilitate the generation of images that are consistent with the lifestyles proposed by the advertiser" refers to methods or technologies for generating images that reflect the particular lifestyles proposed by the advertiser.

[1371] "Reusing existing digital advertising technology" refers to building a new advertising system using already existing digital advertising technologies and methods.

[1372] "Means that also support payment of advertising fees and targeting for secondary distribution on social networking services" refers to a system that allows payment of advertising fees for resharing or reposting content on social networking services, as well as methods and technologies for delivering advertisements targeted at specific user groups.

[1373] "Means for recognizing user emotions in real time" refers to methods and technologies that analyze a user's facial expressions and behavior to instantly determine their emotions at that time.

[1374] "Means for generating brand images according to emotions" refers to methods or technologies for automatically generating optimal brand images based on recognized user emotions.

[1375] The "means for displaying the generated brand image" refers to a method or technology for visually presenting the generated brand image to the user.

[1376] A system for implementing this invention has the following configuration: The server includes means for enabling advertisements to be placed on text, images, and videos generated by AI, means for easily generating images that match the lifestyle proposed by the advertising company, such as having people in images / videos generated by the image / video generation AI wear the advertising company's brand or adding logos to the background, clothing, or tattoos, means for handling advertising fee payments and targeting for secondary distribution on SNS by utilizing existing digital advertising technology, means for recognizing user emotions in real time and generating brand images according to those emotions, and means for displaying the generated brand images.

[1377] Hardware and software used

[1378] Hardware: Smartphone camera

[1379] Software: OpenCV, EmotionRecognizer library, ImageGenerationAI library

[1380] Data processing and calculation

[1381] The server captures video in real time using the smartphone camera. The captured video is then analyzed using the EmotionRecognizer library to recognize the user's emotions. Based on the results of this emotion recognition, the server generates prompts to be input into the generative AI model. For example, if the user is relaxed, the server generates a prompt such as, "A brand image that suits when the user is relaxed."

[1382] Next, the server uses the ImageGenerationAI library to generate a brand image based on the generated prompt. This brand image is optimized for the user's emotions, emphasizing, for example, a sense of relaxation. The generated brand image is then displayed on the smartphone screen.

[1383] Specific examples

[1384] For example, when the user is relaxed, a brand image that emphasizes a sense of relaxation is generated and displayed, and when the user is in a happy mood, a brand image that emphasizes a happy mood is generated and displayed.

[1385] Prompt Sentence Examples

[1386] "A brand image that suits users when they are relaxed"

[1387] "A brand image that suits users when they're in a happy mood"

[1388] In this way, it is possible to generate an optimal brand image in real time according to the user's emotions and display it as an advertisement.

[1389] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1390] Step 1:

[1391] The server captures video in real time using the smartphone's camera.

[1392] Input: Smartphone camera image

[1393] Output: Captured video frames

[1394] Specific operation: The smartphone camera is activated and captures the user's video in real time. The captured video frames are sent to the server.

[1395] Step 2:

[1396] The server analyzes the captured video frames using the EmotionRecognizer library to recognize the user's emotions.

[1397] Input: Captured video frames

[1398] Output: Recognized user emotion (e.g., relaxed, happy)

[1399] What it does: The server uses the EmotionRecognizer library to analyze the user's facial expressions in the video frames and identify their emotions, which are then used in the next step.

[1400] Step 3:

[1401] The server generates prompt sentences to input into the generative AI model based on the recognized emotions.

[1402] Input: Perceived user emotion

[1403] Output: Prompt sentence (e.g., "Brand image that suits the user when they are relaxed")

[1404] Specific operation: The server generates a prompt sentence corresponding to the recognized emotion. For example, if the user is relaxed, the server generates a prompt sentence such as "A brand image that suits when the user is relaxed."

[1405] Step 4:

[1406] The server uses the ImageGenerationAI library to generate a brand image based on the generated prompt text.

[1407] Input: prompt statement

[1408] Output: Generated brand image (image)

[1409] Specific operation: The server inputs the prompt sentence into the generative AI model to generate a brand image that is optimized for the user's emotions.

[1410] Step 5:

[1411] The server displays the generated brand image on the smartphone screen.

[1412] Input: Generated brand image

[1413] Output: Brand image displayed on a smartphone screen

[1414] How it works: The server sends the generated brand image to the smartphone and displays it on the user's screen, allowing the user to see the brand image in real time according to their emotions.

[1415] Example 3

[1416] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1417] Conventional digital advertising systems were unable to fully utilize user behavioral and emotional data, limiting the effectiveness of targeted advertising. They also faced the challenge of being unable to handle advertising fees or targeting for secondary distribution on social media. Furthermore, it was difficult to generate ads that matched the user's emotions.

[1418] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1419] In this invention, the server includes a data collection means, a data analysis means, an emotion recognition means, an advertisement generation means, an advertisement distribution means, a means for enabling advertisement placement in AI-generated text, images, and videos, a means for easily generating images that match the lifestyle proposed by the advertiser by having people in the images / videos generated by the image / video generation AI wear the advertiser's brand, or by adding logos to the background, clothing, or tattoos, and a means for supporting advertising fee payments and targeting for secondary distribution on SNS by utilizing existing digital advertising technology. This enables the generation and distribution of effective targeted advertisements using user behavioral and emotional data.

[1420] "Data collection means" refers to the means used to collect user behavioral data and profile data from social media platforms.

[1421] "Data analysis means" refers to the means for analyzing collected data and identifying users' interests and concerns.

[1422] An "emotion recognition means" is a means for recognizing emotions from user posts and comments.

[1423] "Advertisement generation means" means for generating targeted advertisements based on the user's interests and emotions.

[1424] "Advertising distribution means" refers to the means for distributing the generated advertisements to the SNS platform.

[1425] "Means enabling advertising on text, images, and videos generated by AI" refers to means for placing advertisements on content generated by a generative AI model.

[1426] "Means to make it easier to generate images that are in line with the lifestyle proposed by the advertiser, such as having people in images / videos generated by image and video generation AI wear the advertiser's brand, or having logos in the background, clothing, or tattoos" refers to a means of generating content that is in line with the advertiser's brand and lifestyle by reflecting the advertiser's brand image in the AI's learning data.

[1427] "Method of utilizing existing digital advertising technology to enable payment of advertising fees and targeting for secondary distribution on social media" refers to a method of utilizing existing digital advertising technology to enable payment of advertising fees and targeting for secondary distribution on social media.

[1428] This invention is a system that generates and distributes targeted advertisements by utilizing user behavior data and emotion data on social networking sites. Specific embodiments of this system are described below.

[1429] Hardware and software used

[1430] Server: Collects data, analyzes, generates ads, and delivers ads. Specifically, it uses cloud services (e.g., Amazon Web Services, Google Cloud Platform).

[1431] Device: The device that users use to access SNS. This includes smartphones and PCs.

[1432] Software: Social media platforms (e.g., Facebook, Twitter), emotion engines (e.g., IBM Watson Tone Analyzer), generative AI models (e.g., OpenAI GPT-4).

[1433] Data collection

[1434] The server collects user behavior data (e.g., likes, shares, comments) and profile data (e.g., age, gender, interests) from the social media platform via API, thereby obtaining basic data to understand the user's interests.

[1435] Data analysis

[1436] The server stores the collected data in a database and analyzes it. Specifically, it scores the user's level of interest in a particular product or service. For example, if a user "likes" a "new smartphone," the server sets the user's interest level for that product high.

[1437] emotion recognition

[1438] The server uses an emotion engine to recognize emotions from user posts and comments. For example, if a user posts, "I'm so happy I got my new smartphone!", the server recognizes the emotion "happy." This emotion data is then used to generate advertisements.

[1439] Ad Generation

[1440] The server uses a generative AI model to generate targeted ads based on the user's interests and emotions. Specifically, the user's interest and emotion data is input into the generative AI model, which then generates ad copy based on that data. For example, if a user is excited about a "new smartphone," the server generates ad copy such as "Enjoy a new experience with this smartphone!"

[1441] Ad serving

[1442] The server delivers the generated advertisements to the social media platform. Specifically, the generated advertisements are displayed in the user's feed via the social media platform's advertising API. For example, the generated smartphone advertisements are displayed while the user is browsing the social media.

[1443] Examples of concrete examples and prompts

[1444] Examples:

[1445] User behavior data: User A "likes" a "new smartphone" on social media.

[1446] Emotion data: User A expresses the emotion "excitement" in a post about a "new smartphone."

[1447] Example prompt sentence:

[1448] If User A "likes" a "new smartphone" on social media and expresses excitement, what kind of targeted ads should be generated for that user?

[1449] This system can generate and deliver more effective targeted advertisements by combining user behavior data and emotional data. For example, if user A is excited, the effectiveness of the advertisement can be enhanced by emphasizing an advertisement for a "new smartphone" in line with that emotion. The flow of the identification process in Example 3 will be described with reference to FIG. 21.

[1450] Step 1:

[1451] Data collection

[1452] Input: User behavior data (e.g., likes, shares, comments) and profile data (e.g., age, gender, interests) from social media platforms.

[1453] How it works: The server sends a request through the social media platform's API to obtain user behavioral data and profile data.

[1454] Output: Collected user behavior and profile data is stored in a database.

[1455] Step 2:

[1456] Data analysis

[1457] Input: User behavioral and profile data stored in a database.

[1458] What it does: The server retrieves data from the database, analyzes it, and scores how interested the user is in a particular product or service.

[1459] Output: Scoring data that indicates user interests.

[1460] Step 3:

[1461] emotion recognition

[1462] Input: User posts and comments.

[1463] Specific operation: The server sends the user's post to the emotion engine, which then extracts emotions (e.g., excitement, joy, sadness) from the post.

[1464] Output: Extracted emotion data.

[1465] Step 4:

[1466] Ad Generation

[1467] Input: User interest and emotion data.

[1468] Specific operation: The server inputs user interest data and emotion data into the generated AI model, and the model generates advertising copy based on that data.

[1469] Output: Generated targeted ad copy.

[1470] Step 5:

[1471] Ad serving

[1472] Input: Generated targeting ad copy.

[1473] Specific operation: The server displays the generated advertisement in the user's feed through the social media platform's advertising API.

[1474] Output: Targeted ads displayed in the user's feed.

[1475] In this way, the system leverages user behavioral and emotional data to generate and deliver effective targeted ads.

[1476] (Application example 3)

[1477] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1478] Conventional digital advertising technologies provided targeted advertising based on user behavioral and profile data, but did not generate ads based on user emotions. Furthermore, there were insufficient methods for paying advertising fees and targeting secondary distribution on social media. Furthermore, there were also insufficient methods for displaying ads in real time through applications installed on smartphones. This limited the effectiveness of advertising and made it difficult to provide optimal ads based on users' interests and emotions.

[1479] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1480] In this invention, the server includes: means for enabling advertisements to be placed on text, images, and videos generated by AI; means for easily generating images that match the lifestyles proposed by advertisers, such as by having people in images / videos generated by the image / video generation AI wear the advertiser's brand or adding logos to the background, clothing, or tattoos; means for supporting advertising fee payments and targeting for secondary distribution on social media by utilizing existing digital advertising technology; means for recognizing user emotions using an emotion engine and generating targeted advertisements based on those emotions; and means for collecting user behavioral data and profile data through an application installed on a smartphone and displaying advertisements in real time. This makes it possible to generate optimal targeted advertisements based on the user's behavioral data and emotions and display them in real time.

[1481] "AI" is an abbreviation for artificial intelligence, a technology that enables computer systems to imitate human intelligence to learn, reason, recognize, and make judgments.

[1482] "Text" refers to information expressed in the form of letters or sentences.

[1483] An "image" is a still image that represents visual information.

[1484] "Video" is a medium that expresses movement by playing a series of images along a time axis.

[1485] "Advertising" refers to the procedures and actions required to place an advertisement in a medium.

[1486] "Image generation AI" is a technology that uses artificial intelligence to generate new images.

[1487] "Video" refers to a medium for expressing moving visual information.

[1488] A "person" is an object that represents the appearance or shape of a human being.

[1489] A "brand" is a name, logo, or image that identifies a particular company or product.

[1490] "Background" refers to the part of an image or video that is located behind the main subject.

[1491] "Clothing" refers to fabric products worn by humans.

[1492] A "tattoo" is a pattern or design created by injecting ink into the skin.

[1493] A "logo" is a designed symbol or letter that identifies a company or brand.

[1494] "Lifestyle" refers to people's lifestyles, values, and behavioral patterns.

[1495] "Digital advertising technology" refers to technology for delivering advertisements using the Internet and digital media.

[1496] "Secondary distribution" refers to a product being re-released on the market after going through primary distribution.

[1497] "Advertising Payment" means the fee paid for placing an advertisement.

[1498] "Targeting" is a method of delivering advertisements to specific user groups.

[1499] An "emotion engine" is a technology that recognizes a user's emotions and generates an appropriate response based on those emotions.

[1500] A "smartphone" is a multi-functional mobile device that, in addition to the functions of a mobile phone, can also connect to the Internet and use applications.

[1501] "Behavioral Data" refers to information about the actions you take online and offline.

[1502] "Profile data" refers to data that compiles information such as a user's attributes, interests, and behavioral history.

[1503] "Real-time" means that data and information are processed immediately and results are reflected immediately.

[1504] The system for implementing this invention includes a server, a smartphone, an emotion engine, and an advertisement generation AI. Details of each component and their operation will be described below.

[1505] server

[1506] The server collects user behavioral data and profile data and generates targeted advertisements based on this data. The server obtains user behavioral data through SNS APIs and stores it in a database. It also links the emotion engine with ad generation AI to generate advertisements based on user emotions.

[1507] Smartphone

[1508] The smartphone functions as a user interface and displays advertisements in real time. The application installed on the smartphone receives advertisements sent from the server and displays them to the user. It also collects user behavior data and sends it to the server.

[1509] Emotion Engine

[1510] The emotion engine analyzes users' social media posts and behavioral data to recognize their emotions. The emotion engine uses natural language processing technology to analyze text data and classify the user's emotions. For example, if a user posts, "I want a new smartphone," the emotion engine will recognize "excitement."

[1511] Ad generation AI

[1512] The ad generation AI generates optimally targeted ads based on the user's emotions and behavioral data recognized by the emotion engine. The ad generation AI uses a generative AI model to create advertising content tailored to the user's emotions. For example, if a user expresses "excitement," it generates an ad for the latest smartphone.

[1513] Specific examples

[1514] If a user posts on social media that they want a new smartphone, the emotion engine recognizes the excitement and the ad generation AI generates ads for the latest smartphones that match that emotion. The ads are then displayed to users in real time through an application installed on their smartphone.

[1515] Prompt Sentence Examples

[1516] If a user posts on social media that they want a new smartphone, the emotion engine will recognize the "excitement" and the AI ​​will generate an ad for the latest smartphone that matches that emotion.

[1517] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1518] Step 1:

[1519] The server collects user behavior data through the SNS API. Specifically, it obtains data such as user posts, comments, and likes. The input is user behavior data from the SNS API, and the output is behavior data stored in the server's database. The server periodically collects this data and updates it in real time.

[1520] Step 2:

[1521] The server uses an emotion engine to analyze the collected behavioral data and recognize the user's emotions. Specifically, it uses natural language processing technology to analyze text data and classify the user's emotions. The input is the behavioral data stored in the server's database, and the output is the recognized user's emotion data. The server periodically runs the emotion engine to obtain the latest emotion data.

[1522] Step 3:

[1523] The server uses ad generation AI to generate targeted ads based on the recognized user emotions and behavioral data. Specifically, it uses a generative AI model to create ad content that matches the user's emotions. The input is the recognized user emotional data and behavioral data, and the output is the generated ad content. The server runs the ad generation AI to generate the optimal ad.

[1524] Step 4:

[1525] The server transmits the generated advertising content to the smartphone. Specifically, the advertising content is transmitted to the application installed on the smartphone by push notification. The input is the generated advertising content, and the output is the advertising content transmitted to the smartphone. The server transmits the advertising content in real time.

[1526] Step 5:

[1527] The smartphone displays the received advertising content to the user. Specifically, it displays a pop-up advertisement through an application. The input is the advertising content sent from the server, and the output is the advertisement displayed to the user. The smartphone immediately displays the advertisement and collects the user's response.

[1528] Step 6:

[1529] The smartphone sends user reaction data to the server. Specifically, it collects reaction data such as clicks, likes, and comments on ads and sends it to the server. The input is the user reaction data, and the output is the reaction data sent to the server. The smartphone collects user reactions in real time and sends them to the server.

[1530] Step 7:

[1531] The server stores the received user response data in a database and uses it to generate the next advertisement. Specifically, it analyzes the user response data and evaluates the effectiveness of the advertisement. The input is the user response data sent from the smartphone, and the output is the evaluation data stored in the database. The server continuously evaluates the effectiveness of the advertisement and reflects it in generating the next advertisement.

[1532] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1533] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1534] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are listed.

[1535] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1536] [Third embodiment]

[1537] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1538] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1539] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1540] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1541] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1542] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1543] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1544] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1545] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1546] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1547] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1548] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1549] "Example 1"

[1550] As one embodiment of the present invention, a system is provided that enables advertising in text, images, and videos generated by AI. Specifically, the system has the function of inserting advertising from advertising companies into text, images, and videos generated by AI. For example, it is possible to insert advertising text from advertising companies into blog articles generated by AI.

[1551] "Example 2"

[1552] In addition, the system also provides a function that makes it easier to generate images that match the lifestyles proposed by advertisers, such as having people in images / videos generated by the image / video generation AI wear the advertiser's brand, or adding logos to backgrounds, clothing, or tattoos. Specifically, it has a function that digitally adds the advertiser's logo to people in images / videos generated by the AI. For example, it is possible to digitally add the advertiser's logo to a T-shirt worn by a person in an AI-generated video.

[1553] "Example 3"

[1554] Furthermore, by utilizing existing digital advertising technology, the system also provides functionality for targeting and payment of advertising fees for secondary distribution on social media. Specifically, it has the ability to generate targeted advertisements based on user behavioral and profile data on social media. For example, it is possible to target advertisements from companies selling a particular product based on information that a user has "liked" a product on social media.

[1555] The processing flow of each embodiment will be described below.

[1556] "Example 1"

[1557] Step 1: AI generates text, images, and videos. For example, AI generates a blog post.

[1558] Step 2: Insert the sponsor's advertisement into the generated text, images, and videos. For example, insert the sponsor's advertisement text into the generated blog post.

[1559] "Example 2"

[1560] Step 1: AI generates images / videos. For example, AI generates a video.

[1561] Step 2: Digitally add the advertiser's logo to the person in the generated image / video. For example, digitally add the advertiser's logo to a T-shirt worn by the person in the generated video.

[1562] "Example 3"

[1563] Step 1: Collect user behavioral data and profile data on social media. For example, collect information on whether a user has "liked" a specific product on social media.

[1564] Step 2: Generate targeted ads based on the collected data, for example, targeting ads for companies selling products that users have "liked."

[1565] Example 1

[1566] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1567] Conventional advertising systems have difficulty inserting appropriate ads into AI-generated content, making it impossible to maximize advertising effectiveness. Furthermore, there is a lack of technology to increase the relevance of generated content and ads, making it difficult to effectively provide targeted ads based on users' interests. Furthermore, there is a lack of methods for handling advertising fee payments and targeting for secondary distribution on social media.

[1568] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes a means for a user to input a prompt sentence, a means for the server to generate content using a generation AI model, a means for the server to insert advertisements into the generated content, a means for the server to provide the final content to the user, a means for making it easier to generate images that match the lifestyle proposed by the advertiser by having people in the images / videos generated by the image / video generation AI wear the advertiser's brand, adding logos to the background, clothing, or tattoos, and so on, and a means for supporting advertising fee payments and targeting for secondary distribution on SNS by utilizing existing digital advertising technology. This makes it possible to insert appropriate advertisements into the generated content and effectively provide targeted advertisements based on the user's interests. Furthermore, it is also possible to support advertising fee payments and targeting for secondary distribution on SNS.

[1569] A "user" is an individual or entity that utilizes the system to enter prompts and receive generated content.

[1570] A "prompt sentence" is text that a user inputs to specifically instruct the system on the content they wish to generate.

[1571] "Server" refers to a computer system that generates content using a generative AI model, inserts advertisements, and provides the final content to users.

[1572] A "generative AI model" is an artificial intelligence model that generates content such as text, images, and videos based on prompts entered by users.

[1573] "Content" refers to information such as text, images, and videos generated by a generative AI model.

[1574] An "advertisement" is information such as text, images, and videos inserted into content to promote products or services offered by the advertising company.

[1575] "Advertiser" means a company that provides advertisements and inserts those advertisements into content through the system.

[1576] "Targeted advertising" refers to advertising that is optimized for a specific user based on the user's behavioral data and profile data.

[1577] "SNS" is an abbreviation for social networking service, an online platform for users to share information and interact with each other.

[1578] "Secondary distribution" refers to the re-sharing of generated content through social media and other means.

[1579] "Digital advertising technology" refers to technology for delivering advertisements on online platforms and measuring their effectiveness.

[1580] This invention relates to a system for inserting advertisements into text, images, and videos generated using a generative AI model. In this system, a user inputs a prompt sentence, a server generates content using a generative AI model, inserts advertisements, and provides the final content.

[1581] Hardware and software used

[1582] The server is a high-performance computing system for running generative AI models. Specifically, it uses the following hardware and software:

[1583] Hardware: A server with a powerful CPU, GPU, and sufficient memory

[1584] Software: Generative AI models (e.g., OpenAI's GPT-4 and DALL-E), natural language processing (NLP) libraries, database management systems

[1585] Data processing and calculation

[1586] The server receives the prompt entered by the user and uses the generative AI model to:

[1587] 1. Parse the prompt:

[1588] The server analyzes the prompt sentence entered by the user and determines the content to be generated.

[1589] Example: A user types, "Generate blog posts about summer travel."

[1590] 2. Content generation:

[1591] The server uses a generative AI model to generate text, images, and videos based on the prompt.

[1592] Example: A server generates a "summer travel blog post" that includes information about recommended travel spots and activities.

[1593] 3. Ad Insertion:

[1594] The server inserts appropriate advertisements into the generated content, performing topic analysis and relevance evaluation of the content to select the most suitable advertisement.

[1595] Example: Inserting advertising text into generated blog posts that reads, "Take advantage of our travel agency's special deals this summer!"

[1596] 4. Final Content Delivery:

[1597] The server generates the final content with the advertisements inserted and provides it to the user.

[1598] Example: A server displays a blog post with an ad inserted to a user, who then views the post.

[1599] Examples of concrete examples and prompts

[1600] Examples:

[1601] When a user enters the prompt "Generate a blog post about autumn leaves," the server generates a blog post about autumn leaves and inserts advertising text into it that reads, "Take beautiful photos with this camera manufacturer's new model during the autumn foliage season!"

[1602] Example prompt sentence:

[1603] "Generate blog posts about summer travel"

[1604] "Generate a review video for a new smartphone"

[1605] "Generate images of healthy recipes"

[1606] In this way, a system is realized in which the user inputs a prompt sentence, the server generates content using a generative AI model, inserts appropriate advertisements, and provides the final content.

[1607] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1608] Step 1:

[1609] The user inputs a prompt statement. The user inputs a prompt statement that specifically specifies the content they want to generate through the system interface. The input prompt statement is sent to the server. In a specific operation, the user inputs, "Generate a blog post about summer travel."

[1610] Input: The prompt text entered by the user

[1611] Output: The prompt sent to the server

[1612] Step 2:

[1613] The server receives the prompt and generates content using a generative AI model. The server analyzes the prompt and generates text, images, and videos using a generative AI model (for example, OpenAI's GPT-4 or DALL-E). Specifically, the server generates a "summer travel blog post."

[1614] Input: The prompt text sent by the user

[1615] Output: Generated text, images, and videos

[1616] Step 3:

[1617] The server inserts advertisements into the generated content. The server performs topic analysis and relevance assessment of the generated content, and selects appropriate advertisements from the advertising company's advertisement database. The selected advertisements are inserted at appropriate positions within the content. Specifically, the server inserts advertisement text into the generated blog post, such as "We recommend this travel agency's special plan for your summer trip!"

[1618] Input: Generated text, images, videos

[1619] Output: Text, images, and videos with ads inserted

[1620] Step 4:

[1621] The server provides the final content to the user. The server generates the final content with the advertisement inserted and provides it to the user. The user can view this content through the system interface. Specifically, the server displays the blog post with the advertisement inserted to the user.

[1622] Input: Text, images, and videos with ads inserted

[1623] Output: The final content that is delivered to the user

[1624] (Application example 1)

[1625] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1626] With conventional advertising systems, it was difficult to effectively insert ads into AI-generated text, images, and videos. Furthermore, the process of selecting and inserting appropriate ads into user-generated content was often done manually, resulting in inefficiency. Furthermore, the effectiveness of ads was not adequately measured, making it difficult to accurately determine the effectiveness of each ad. To solve these issues, an efficient advertising system utilizing AI is needed.

[1627] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1628] In this invention, the server includes a means for enabling advertisements to be placed in text, images, and videos generated by AI, a means for AI to select appropriate advertisements and insert them into content when users upload content generated by users to the application, and a means for incorporating an advertisement effectiveness measurement function and analyzing which advertisements received how many clicks and views. This makes it possible to efficiently insert advertisements using AI and accurately measure their effectiveness.

[1629] "AI-generated text, images, and videos" refers to text, still images, and videos that are automatically generated using artificial intelligence technology.

[1630] "Means enabling advertising" refers to methods or technologies that allow companies or individuals to insert advertisements into specific media or content.

[1631] "Image and video generation AI" refers to systems and algorithms that automatically generate images and videos using artificial intelligence technology.

[1632] "Wearing the advertiser's brand" refers to people in the generated images and videos displaying a specific company's brand or logo.

[1633] "Logo on background, clothing, tattoo" refers to the insertion of a specific company's logo on the background, clothing, or tattoo in the generated image or video.

[1634] "Images that are in line with the lifestyle proposed by the advertising company" refers to images that reflect the lifestyle and values ​​that a particular company promotes.

[1635] "Existing digital advertising technologies" refers to digital advertising technologies and methods that are currently in widespread use.

[1636] A "social networking service" is an online platform that allows people to share information and interact with each other over the Internet.

[1637] "Advertising fees for secondary distribution" refers to the payment of advertising fees that occurs when an advertisement is shared or reused again after its initial distribution.

[1638] "Targeting" refers to the method of delivering advertisements to specific user groups or market segments.

[1639] "User-generated content" means text, images or videos that are created by members of the public and uploaded to online platforms.

[1640] "Uploading to an Application" means sending and storing content created by a user to a specific software or platform.

[1641] "Selecting the right ad" refers to choosing the most relevant and effective ad for a particular content or user.

[1642] The "advertising effectiveness measurement function" is a function that analyzes the number of clicks and views an advertisement receives and evaluates its effectiveness.

[1643] The following system configuration will be described as an embodiment of the present invention.

[1644] System Configuration

[1645] This system includes a server, a user device, and an AI model. The server provides a means for placing advertisements in AI-generated text, images, and videos. The user device uploads user-generated content and provides an interface for the AI ​​to select appropriate advertisements and insert them into the content. The AI ​​model executes an algorithm to insert advertisements into the generated content and measure their effectiveness.

[1646] Hardware and software used

[1647] Hardware: Smartphones, servers

[1648] Software: Python, OpenAI API

[1649] Data processing and calculation

[1650] The server receives user-generated content and uses the AI ​​model to select appropriate ads. Specifically, the process involves the following steps:

[1651] 1. User input: The user inputs a prompt for the content they want to generate into the user terminal.

[1652] 2. Content Generation: The server uses the OpenAI API to generate text content based on the user's prompts.

[1653] 3. Advertisement selection: The server selects pre-prepared advertisement text for the generated content.

[1654] 4. Advertisement insertion: The server inserts the selected advertisements into the generated content.

[1655] 5. Effectiveness measurement: The server analyzes the number of clicks and views of the advertisement and measures its effectiveness.

[1656] Specific examples

[1657] User Input

[1658] The user enters a prompt like this:

[1659] "Generate a review article for a new smartphone"

[1660] "Generate articles about the latest fashion trends"

[1661] "Generate healthy eating advice"

[1662] "Generate a guide to the best places to visit in your travel destination."

[1663] Content Generation

[1664] The server uses the OpenAI API to generate text content like this:

[1665] "This phone is very powerful and the camera quality is excellent."

[1666] "This year's fashion trends are characterized by colorful accessories and simple designs."

[1667] "A balanced diet and moderate exercise are important for maintaining a healthy diet."

[1668] "The best travel destinations are those with beautiful scenery and rich culture."

[1669] Ad selection and insertion

[1670] The server inserts advertisements into the generated content, such as:

[1671] "Check this product out!"

[1672] Effectiveness measurement

[1673] The server analyzes the number of clicks and views the ad received and measures its effectiveness, allowing the user to accurately understand the effectiveness of the ad and use this information to improve the next ad placement.

[1674] In this way, an efficient advertising system utilizing AI will be realized.

[1675] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1676] Step 1:

[1677] The user inputs a prompt statement for the content that he or she wants to generate into the user terminal.

[1678] Input: The prompt text entered by the user (e.g., "Generate a review of a new smartphone.")

[1679] Output: Prompt sent from the user's terminal to the server

[1680] Specific operation: The user opens the application on their smartphone, enters the prompt for the content they want to generate, and presses the send button. The user's device then sends this prompt to the server.

[1681] Step 2:

[1682] The server uses the OpenAI API to generate text content based on the user's prompts.

[1683] Input: Prompt sent from the user's terminal

[1684] Output: Generated text content (e.g., "This smartphone is very powerful and the camera quality is excellent.")

[1685] Specific operation: The server sends the received prompt to the OpenAI API, and the AI ​​model generates text content based on the prompt. The generated text content is returned to the server.

[1686] Step 3:

[1687] The server selects pre-prepared advertising text for the generated content.

[1688] Input: Generated text content, ad database

[1689] Output: Selected ad text (e.g., "Check out this product!")

[1690] Specific operation: The server analyzes the generated text content and selects the most relevant advertising text from the advertising database.

[1691] Step 4:

[1692] The server inserts the selected advertisements into the generated content.

[1693] Input: Generated text content, selected advertising text

[1694] Output: The final content with the ad inserted (e.g., "This phone is very powerful and has an excellent camera.\n\n---\nAd: Check out this product!\n---")

[1695] Specific operation: The server inserts the selected advertising text into the appropriate position of the generated text content to generate the final content.

[1696] Step 5:

[1697] The server analyzes the number of clicks and views of the advertisements to measure their effectiveness.

[1698] Input: Final content with ad insertion, user behavior data

[1699] Output: Ad effectiveness measurement results (e.g., number of clicks, number of views)

[1700] How it works: The server delivers content with ads inserted, records the number of clicks and views by users, and analyzes this data to measure the effectiveness of the ads.

[1701] In this way, an efficient advertising system utilizing AI will be realized.

[1702] Example 2

[1703] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1704] With conventional digital advertising systems, it was difficult to effectively reflect the advertiser's brand in the generated images and videos. Inserting ads into user-generated content was also time-consuming and costly, and the accuracy of targeted advertising was insufficient. Furthermore, there was no system in place for paying advertising fees for secondary distribution on online platforms.

[1705] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for a user to input a prompt text, a means for the server to receive the prompt text and call a generative AI model, a means for the server to acquire the generated images and videos and add the logo of the advertising company, a means for the server to send the processed images and videos to the user, and a means for supporting payment of advertising fees and targeting for secondary distribution on online platforms by utilizing existing digital advertising technology. This enables users to easily generate images and videos incorporating the brand of the advertising company and improve the accuracy of targeted advertising. A system for payment of advertising fees for secondary distribution on online platforms is also established.

[1706] A "user" is an individual or entity that utilizes the system to input prompts and receive generated images and videos.

[1707] A "prompt" is text that a user inputs into a generative AI model, describing the content of the image or video they want to generate.

[1708] The "server" is a computer system that receives prompt text from the user, invokes the generative AI model, retrieves the generated images and videos, processes them, and finally sends them to the user.

[1709] A "generative AI model" is an artificial intelligence model that generates images and videos based on prompt text.

[1710] A "logo" is a digital image or text that represents the advertiser's brand and is added to the generated image or video.

[1711] "Sponsor" means a company or organization that sponsors an advertisement and whose brand or logo is to be reflected in the generated images and videos.

[1712] "Targeted advertising" refers to advertising that is optimized for a specific user based on the user's behavioral data and profile data.

[1713] An "online platform" is a general term for services and applications provided over the Internet, and is a place where users can share content they generate.

[1714] "Secondary distribution" refers to the redistribution of generated content through other users or platforms after its initial release.

[1715] "Advertising payment" refers to the fee paid by an advertiser for an advertisement being displayed or clicked on.

[1716] This invention is a system that allows users to input prompt text, generates images and videos using a generative AI model, and adds the sponsor's logo. A specific embodiment of this system is described below.

[1717] Hardware and software used

[1718] Hardware: Servers, terminals

[1719] Software: Generative AI models (e.g., OpenAI's DALL-E, Stable Diffusion), image editing software (e.g., Adobe Photoshop API)

[1720] Program processing

[1721] The user enters a prompt statement

[1722] The user inputs a prompt into the input form on the device that describes the image or video they want to generate. For example, they input a prompt such as "Generate an image of a man wearing a blue shirt jogging in a park."

[1723] The server receives the prompt.

[1724] The prompt text entered by the user is sent from the terminal to the server, which receives it and prepares to proceed with the next process.

[1725] The server invokes the generative AI model

[1726] The server passes the received prompt sentence to the generative AI model, which then begins calculations to generate images and videos based on the prompt sentence.

[1727] The server retrieves the generated images and videos.

[1728] Once the generative AI model has finished generating images and videos based on the prompt, the server retrieves the generated results, which are temporarily stored on the server.

[1729] The server adds the advertiser's logo

[1730] The server digitally adds the advertiser's logo to the people in the generated images and videos, for example, by adding the advertiser's logo to a T-shirt worn by the people in the generated images, using image editing software (e.g., Adobe Photoshop API).

[1731] The server sends the processed images and videos to the user.

[1732] The server sends the images and videos with the logo added to them to the user, who can then view the processed images and videos on their device. The transmission is done using the HTTP protocol.

[1733] Specific examples

[1734] Prompt Sentence Examples

[1735] "Generate an image of a woman in a red dress walking on the beach"

[1736] "Generate a video of a man in a black suit giving a presentation in an office."

[1737] In this way, users can easily create and review images and videos incorporating the advertiser's brand. This system will improve the accuracy of targeted advertising and will also establish a system for paying advertising fees for secondary distribution on online platforms.

[1738] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1739] Step 1:

[1740] The user enters a prompt statement

[1741] The user inputs a prompt that describes the image or video they want to generate into the input form on their device. For example, they might input a prompt such as "Generate an image of a man in a blue shirt jogging in a park." The input prompt is then sent from the device to the server.

[1742] Step 2:

[1743] The server receives the prompt.

[1744] The server receives the prompt sent from the device, parses the received prompt, and prepares to pass it to the generative AI model. The input is the prompt, and the output is the parsed prompt.

[1745] Step 3:

[1746] The server invokes the generative AI model

[1747] The server passes the parsed prompt sentence to the generative AI model, which then begins calculations to generate images and videos based on the prompt sentence. The input is the parsed prompt sentence, and the output is the generated image or video data.

[1748] Step 4:

[1749] The server retrieves the generated images and videos.

[1750] Once the generative AI model has finished generating images and videos based on the prompt, the server retrieves the generated results. The generated images and videos are temporarily stored on the server. The input is the generated results from the generative AI model, and the output is the image and video data stored on the server.

[1751] Step 5:

[1752] The server adds the advertiser's logo

[1753] The server digitally adds the sponsor's logo to the people in the generated images and videos. For example, the sponsor's logo is added to a T-shirt worn by a person in the generated image. This process is performed using image editing software (e.g., Adobe Photoshop API). The input is the image or video data stored on the server, and the output is the image or video data with the logo added.

[1754] Step 6:

[1755] The server sends the processed images and videos to the user.

[1756] The server sends the images or videos with the logo added to the user, who can then view the processed images or videos on their device. Transmission is performed using the HTTP protocol. The input is the image or video data with the logo added, and the output is the processed image or video sent to the user's device.

[1757] (Application example 2)

[1758] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1759] With conventional advertising methods, it was difficult to automatically add specific brand logos or lifestyle elements to images and videos taken by users. Furthermore, there was a lack of effective ways to expose brands within the generated content, and there was a need for improved accuracy in targeted advertising.

[1760] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for enabling advertisements to be placed on text, images, and videos generated by AI; a means for making it easier to generate images that match the lifestyle proposed by the advertising company by having people in images / videos generated by image and video generation AI wear the advertising company's brand or add logos to backgrounds, clothing, or tattoos; and a means for automatically adding specific brand logos and lifestyle elements to images and videos taken by users. This makes it possible to effectively expose brands to content taken by users.

[1761] "AI-generated text, images, and videos" refers to text, still images, and video automatically generated using artificial intelligence technology.

[1762] "Means enabling advertising placement" refers to the methods and technologies that allow advertisers to place advertisements in specific media.

[1763] "Image and video generation AI" refers to systems and algorithms that use artificial intelligence technology to automatically generate still images and videos.

[1764] "Advertising company brand" refers to the trademark, logo, and brand image of the company placing the advertisement.

[1765] "Logo on background, clothing, tattoos" refers to the digital addition of a logo to a background, person's clothing, or tattoos in a generated image or video.

[1766] "Lifestyle images" are images created based on a particular lifestyle or values.

[1767] "Existing digital advertising technologies" refers to online advertising technologies and methods currently in widespread use.

[1768] "Secondary distribution on social media" refers to users sharing or reposting content on social networking services.

[1769] "Targeted advertising" refers to the technology and methods used to deliver advertisements optimized for specific user groups or individuals.

[1770] "User behavior data" refers to data about the actions and behavior of users online.

[1771] "Profile Data" refers to data about a user's attributes, interests, and concerns.

[1772] "Training data" refers to a data set used to train an artificial intelligence.

[1773] "Brand image" refers to the image or perception that consumers have of a particular brand.

[1774] A system for implementing this invention has the following configuration: A server includes means for enabling advertisements to be placed on text, images, and videos generated by AI, means for making it easier to generate images that fit the lifestyle proposed by the advertising company by having people in the images / videos generated by the image / video generation AI wear the advertising company's brand or add logos to the background, clothing, or tattoos, and means for automatically adding specific brand logos and lifestyle elements to images and videos taken by the user.

[1775] Hardware and software used

[1776] Hardware: Smartphone (iOS or Android)

[1777] Software: Image and video generation AI (e.g., OpenAI's DALL-E), image processing library (e.g., OpenCV), cloud storage (e.g., AWS S3)

[1778] Data processing and calculation

[1779] Uploading images and videos

[1780] Users upload images and videos they have taken using their smartphones to the application, and the uploaded data is stored in cloud storage (AWS S3).

[1781] AI analysis and logo addition

[1782] The server uses an image and video generation AI (DALL-E) to analyze uploaded images and videos. Based on the analysis results, it adds the specified brand logo and lifestyle elements. It uses an image processing library (OpenCV) to place the logo and background elements in the appropriate position.

[1783] Preview and save the generated results

[1784] It shows the user a preview of the generated image or video, and if the user is satisfied, it saves the generated result to cloud storage and provides a download link.

[1785] Specific examples

[1786] scenario

[1787] Consider a case where a user wants to add the logo of a particular sports brand to a photo they take with their friends.

[1788] Prompt Sentence Examples

[1789] "Take a photo with your friends and add a sports brand logo to your T-shirt."

[1790] "Add a beverage brand advertisement in the background of this photo."

[1791] "Please add a clothing brand logo to the jacket worn by the person in this video."

[1792] "Change the background of this image to a beach and add a surfing brand logo."

[1793] In this way, it is possible to effectively expose the brand to content shot by users.

[1794] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1795] Step 1:

[1796] Users upload images and videos taken using their smartphones to the application. The input is the images and videos taken by the user, and the output is the data stored in cloud storage (AWS S3). Specifically, the user taps the upload button on the application and selects the images or videos from the file selection screen.

[1797] Step 2:

[1798] The server retrieves uploaded images and videos from cloud storage. The input is the images and videos stored in cloud storage, and the output is data in a format that can be processed within the server. Specifically, the server downloads the data using the AWS S3 API.

[1799] Step 3:

[1800] The server uses the image and video generation AI (DALL-E) to analyze the acquired images and videos. The input is images and videos in a format that can be processed within the server, and the output is the analysis results. Specifically, the server calls the DALL-E API and analyzes the content of the images and videos.

[1801] Step 4:

[1802] The server adds the specified brand logo and lifestyle elements based on the analysis results. The input is the analysis results and the data of the brand logo and lifestyle elements to be added, and the output is an image or video with the logo or elements added. Specifically, the server uses an image processing library (OpenCV) to place the logo and elements in the appropriate position.

[1803] Step 5:

[1804] The server displays a preview of the generated image or video to the user. The input is the image or video with the logo or elements added, and the output is the preview screen displayed on the user's smartphone. Specifically, the server sends the generated data to the user's smartphone, and the application displays the preview screen.

[1805] Step 6:

[1806] If the user is satisfied with the generated results, the server saves the results in cloud storage and provides a download link. The input is the user's satisfaction confirmation and the generated image or video, and the output is the data stored in cloud storage and a download link. Specifically, the user taps the save button in the application, and the server saves the data in AWS S3 and generates a download link.

[1807] Example 3

[1808] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1809] Conventional digital advertising systems have had difficulty effectively utilizing user behavioral and profile data to generate targeted ads. They also lacked a mechanism for measuring the effectiveness of generated ads and providing feedback for the next ad generation. Furthermore, there were limited means for automatically generating ad content, resulting in insufficient personalization of ads.

[1810] The identification process by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means. In this invention, the server includes means for collecting user behavioral data and profile data, means for storing the collected data in a database, means for analyzing the stored data and generating targeted advertisements, means for automatically generating advertisement content using a generative AI model, means for delivering the generated advertisements, and means for measuring the effectiveness of the advertisements and providing feedback for the next advertisement generation. This makes it possible to effectively utilize user behavioral data and profile data to generate and deliver personalized targeted advertisements. Furthermore, measuring the effectiveness of the advertisements and providing feedback for the next advertisement generation can improve the accuracy and effectiveness of the advertisements.

[1811] "User behavioral data" refers to data regarding actions such as "likes," shares, and comments taken by users on social media platforms.

[1812] "Profile data" refers to data that includes personal information and attribute information such as a user's age, gender, and interests.

[1813] A "database" is a system for storing and managing collected user behavioral data and profile data.

[1814] "Analysis" is the process of analyzing user interests and behavioral patterns based on stored data.

[1815] "Targeted advertising" refers to advertising that is personalized for specific users based on analysis results.

[1816] A "generative AI model" is a model that uses artificial intelligence technology to automatically generate advertising content.

[1817] A "prompt" is an instruction entered into a generative AI model, and is text that prompts the generation of advertising copy.

[1818] "Serving ads" is the process of sending the generated ads to social media platforms and displaying them in users' feeds.

[1819] "Effectiveness measurement" is the process of collecting data such as the number of clicks and conversion rates of delivered advertisements to evaluate their effectiveness.

[1820] "Feedback" is the process of reflecting the results of effectiveness measurement in the generation of the next advertisement.

[1821] MODE FOR CARRYING OUT THE INVENTION

[1822] This invention relates to a system for generating and delivering targeted advertisements by utilizing user behavior data and profile data. Specific embodiments of this system are described below.

[1823] 1. Program Generation

[1824] The server collects user behavioral data and profile data from SNS platforms (e.g., SNS service A, SNS service B) and generates a program that generates targeted advertisements based on that data. This program automatically creates the content of the advertisements using a generative AI model (e.g., generative AI model A).

[1825] 2. Program processing explanation

[1826] The server collects user behavior data (e.g., likes, shares, comments) and profile data (e.g., age, gender, interests) from the social networking platform. This data is stored in databases (e.g., Database A, Database B).

[1827] The server then analyzes the collected data and generates targeted ads based on specific conditions. For example, if a user "likes" a particular product, it generates ads for companies selling that product. This ad generation uses a generative AI model (e.g., Generative AI Model A).

[1828] The generated advertisements are sent to social media platforms and displayed in users' feeds. To measure the effectiveness of the advertisements, the servers also collect and analyze data such as the number of clicks and conversion rates.

[1829] 3. Examples of concrete examples and prompts

[1830] As a concrete example, consider the case where a user "likes" a "smartphone" on a social networking site. Based on this information, the server generates advertisements for companies that sell smartphones.

[1831] Example prompt sentence:

[1832] Generate ads for companies selling smartphones based on users' "likes" on social media. Include the latest smartphone features, prices, and purchase links in the ads.

[1833] By feeding this prompt into a generative AI model, the following ad is generated:

[1834] Introducing the latest smartphone! High-performance camera, long battery life, and a great price. Click the Buy Now link to find out more!

[1835] In this way, the server utilizes user behavior data on the SNS to provide a system that effectively generates and distributes targeted advertisements. This system improves the effectiveness of advertisements by promoting personalization of advertisements and displaying advertisements based on the user's interests. In addition, measurement of advertisement effectiveness and feedback improves the accuracy of next advertisement generation. The flow of the identification process in Example 3 will be described with reference to FIG. 15.

[1836] Step 1: Collect user behavior data

[1837] The server collects user behavior data from the social media platform. Specifically, it obtains data such as posts that users have "liked," content that they have shared, and comments on through the API. It receives the data obtained from the social media platform's API as input and converts the behavior data into a format that can be stored in a database as output.

[1838] Step 2: Save your data

[1839] The server stores the collected behavioral data in a database. The database contains information such as the user ID, type of behavior, content ID of the behavior, and timestamp. The server receives the behavioral data collected in step 1 as input and stores it in the database as output.

[1840] Step 3: Analyze the data

[1841] The server analyzes the stored data, using data mining techniques and machine learning algorithms. For example, if a user has many "likes" for products in a particular category, it can be determined that the user has a high level of interest in that category. The server receives the behavioral data stored in the database as input and obtains the analysis results as output.

[1842] Step 4: Generate targeted ads

[1843] The server generates targeted ads based on the analysis results. At this time, it uses a generative AI model to automatically generate the ad content. Specifically, it inputs the prompt text into the generative AI model to generate ad copy. It receives the analysis results and the prompt text as input, and obtains the generated ad copy as output.

[1844] Example prompt sentence:

[1845] Generate ads for companies selling smartphones based on users' "likes" on social media. Include the latest smartphone features, prices, and purchase links in the ads.

[1846] Step 5: Serving Ads

[1847] The server sends the generated advertisement to the social media platform, which displays the advertisement in the user's feed. The server receives the generated advertisement copy as input and sends it as output to the social media platform.

[1848] Step 6: Measurement and feedback

[1849] The server measures the effectiveness of the delivered advertisements. Specifically, it collects and analyzes data such as the number of ad clicks, conversion rate, and duration of visit. Based on this data, it evaluates the effectiveness of the advertisements and provides feedback for the generation of the next advertisement. It receives the effectiveness measurement data obtained from the SNS platform as input, and obtains the analysis results and feedback information as output.

[1850] (Application example 3)

[1851] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1852] With conventional digital advertising technology, it was difficult to effectively utilize user behavior data on social media to generate targeted ads. Furthermore, there was a lack of a way to properly display the generated ads on users' smartphones, limiting the effectiveness of the ads. Furthermore, it was difficult to generate images and videos that reflected the brand image of the advertising company.

[1853] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes a means for enabling advertisements to be placed on text, images, and videos generated by AI; a means for easily generating images that match the lifestyle proposed by the advertising company by having people in images / videos generated by image and video generation AI wear the advertising company's brand or add logos to the background, clothing, or tattoos; a means for supporting advertising fee payments and targeting for secondary distribution on social media by utilizing existing digital advertising technology; and a means for generating targeted advertisements based on user behavioral data and profile data and displaying them on smartphones. This enables the generation and display of effective targeted advertisements based on user interests.

[1854] "AI" is an abbreviation for artificial intelligence, a technology that allows computers to imitate human intelligence and learn and reason.

[1855] "Text" refers to information expressed in the form of letters or sentences.

[1856] An "image" is static visual information that can be perceived visually.

[1857] "Video" refers to visual information that expresses movement by displaying a series of images at regular time intervals.

[1858] "Advertising" refers to the procedures and actions for placing an advertisement in a specific medium.

[1859] "Image generation AI" refers to systems and algorithms that generate images using artificial intelligence technology.

[1860] "People in video" refers to human characters or models that appear in the generated images or videos.

[1861] A "brand" is a name, logo, or image that identifies a particular company or product.

[1862] "Background" refers to the area behind the main subject in an image or video.

[1863] "Clothing" refers to the clothing and accessories worn by humans.

[1864] A "tattoo" is a pattern or design created by injecting ink into the skin.

[1865] A "logo" is a design or mark that symbolizes a company or brand.

[1866] A "lifestyle" is a pattern of behavior and values ​​that an individual or group chooses to live in their daily lives.

[1867] "Digital advertising technology" refers to technology for delivering advertisements using the Internet and digital devices.

[1868] "SNS" is an abbreviation for social networking services, a platform for people to interact with each other on the Internet.

[1869] "Secondary distribution" refers to a product being re-released on the market after going through primary distribution.

[1870] "Advertising Payment" means the fee paid for placing an advertisement.

[1871] "Targeting" is a method of delivering advertisements to specific user groups.

[1872] "Behavioral Data" refers to information about the actions you take online and offline.

[1873] "Profile data" refers to information including a user's attributes, interests, behavioral history, etc.

[1874] A "smartphone" is a highly functional mobile phone that can connect to the Internet and use applications.

[1875] A system for implementing this invention has the following configuration: The server includes means for enabling advertisements to be placed on text, images, and videos generated by AI, means for easily generating images that match the lifestyle proposed by the advertising company, such as by having people in the images / videos generated by the image / video generation AI wear the advertising company's brand or adding logos to the background, clothing, or tattoos, means for handling advertising fee payments and targeting for secondary distribution on SNS by utilizing existing digital advertising technology, and means for generating targeted advertisements based on user behavioral data and profile data and displaying them on smartphones.

[1876] Hardware and software used

[1877] Hardware: Servers, smartphones

[1878] Software: Python, SNS API, scikit-learn, TfidfVectorizer, linear_kernel

[1879] Data processing and calculation

[1880] The server uses the SNS API to obtain user behavior data. Specifically, it collects data on products and posts that users have "liked" on SNS. This data reflects the user's interests and concerns, and is therefore important information for generating targeted advertisements.

[1881] Next, the server uses TfidfVectorizer to vectorize the user's "like" data and the ad data, converting the text data into numerical data for easier calculations. It then uses linear_kernel to calculate the cosine similarity between the user's "like" data and the ad data, allowing it to select the ad that most closely matches the user's interests.

[1882] The selected ads are then displayed on smartphones, allowing users to view ads based on their interests, increasing the effectiveness of the ads.

[1883] Specific examples

[1884] For example, if a user "likes" a "new fashion item" on a social networking site, that data is sent to a server. The server uses that data to generate fashion-related advertisements and displays them on the user's smartphone. These advertisements include information about new products and sales from the brand the user "liked."

[1885] Prompt Sentence Examples

[1886] "Generate targeted ads based on products that users have liked on social media. User ID is "user123"."

[1887] In this manner, the present invention enables the generation and display of effective targeted advertisements based on user interests.

[1888] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1889] Step 1:

[1890] The server uses the SNS API to obtain user behavior data. Specifically, it collects data on products and posts that users have "liked" on the SNS. The input is the user ID, and the output is the user's "like" data. This data reflects the user's interests and concerns, and is therefore importan...

Claims

1. a means for a user to input a prompt sentence; A means for the server to generate content using the generative AI model; means for inserting advertisements into the content generated by the server; means for the server to provide the final content to the user; The AI ​​can generate images and videos that are in line with the lifestyle of the advertiser, by having people in the images and videos wear the advertiser's brand, or by including logos in the background, clothing, or tattoos. By utilizing existing digital advertising technology, we will be able to handle payment of advertising fees and targeting for secondary distribution on SNS, A system including:

2. The system of claim 1 , wherein the generating means includes functionality for generating targeted advertisements based on user behavioral data and profile data.

3. The system of claim 1, wherein the means for making it easier to generate images that match the lifestyle proposed by the advertising company, such as by having people in the images / videos generated by the image / video generation AI wear the advertising company's brand, or by including logos in the background, clothing, or tattoos, includes a function for reflecting the advertising company's brand image in the AI's learning data.

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