system

Abstract

We provide a system that enables smooth business negotiations between users and designers. [Solution] The system includes a means for users to register personal information through various input forms, a means for sending the registered information to a server and saving it in a database, a means for verifying registered user information to perform authentication, a means for designers to upload design works and input metadata related to the works, a means for sending the design works and their metadata to the server and saving them in the database, a means for users to input search queries and send them to the server, a means for the server to search for related designs from the database and perform analysis using AI to generate suggestions based on the user's tastes and preferences, a means for displaying the search results and suggested design works to the user, and a means for users to issue purchase requests and notify the designer of the request.

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] While demand for architectural designs and artworks (including NFT works) has increased in recent years, there is a lack of platforms that allow freelance designers to efficiently present their work and match it with buyers. Furthermore, there is no system that automatically proposes designs based on a user's individual tastes and preferences, making it difficult for users to find the design that best suits them. Therefore, there is a need for a system that improves convenience for both designers and users and enables efficient matching. [Means for solving the problem]

[0005] The present invention provides a means for users to register personal information through various input forms, and then transmits that information to a server and stores it in a database. The registered user information is verified through authentication means. The present invention also provides a system that allows designers to upload their own designs and input their metadata (title, description, tags, etc.), and transmits that information to a server and stores it in a database.

[0006] Furthermore, the system provides a means for a user to input a search query and send it to a server, which then searches for related designs from a database and performs analysis using AI. This allows the system to generate suggestions based on the user's tastes and preferences, and display the search results and proposed design works to the user. Additionally, the system includes a means for the user to issue a purchase request and notify the designer of the request. The server also includes a step of collecting the user's past search history, purchase history, and browsing history, and identifying the user's preference trends using AI.

[0007] Finally, a system is provided that enables smooth business negotiations between users and designers by including a means for the server to receive purchase approval or rejection from the designer and notify the user of the result. This system allows users to intuitively and efficiently find their ideal design, and enables designers to efficiently sell their works.

[0008] "User" refers to an individual or corporation that uses the system and searches for and purchases works, registers personal information, etc.

[0009] "Designers" are individuals or corporations who upload their own design works to the system and wish to sell or match them.

[0010] "Server" means a computer system that processes information submitted by users and designers and stores the information in a database.

[0011] A "database" is a data storage system for systematically storing and managing user information, designer information, metadata of design works, etc.

[0012] "AI" stands for artificial intelligence, a technology that analyzes users' tastes and preferences based on the aforementioned data and generates personalized suggestions.

[0013] "Metadata" refers to additional information about a design work, such as the title, description, and tags associated with the work.

[0014] "Search Query" means the keywords or categories entered by a User to search for Design Works through the System.

[0015] "Purchase Request" means a request by a User to notify a Designer that the User wishes to purchase a particular Design Product. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0024] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0037] The present invention is a system for efficiently matching users and designers, and is implemented in the following manner.

[0038] First, the user accesses the system and enters personal information such as name, email address, and password on the new registration page. The terminal sends this information to the server, which stores the received information in a database. If registration is successful, the terminal displays a registration success message to the user.

[0039] Next, the designer uploads the image file, title, description, tags, and other metadata of the work to be exhibited. The device temporarily saves this information, checks the format and content, and then sends it to the server. The server saves the received information in a database and returns a message to the device indicating that the save was successful, displaying a message to the designer indicating that the exhibit was successful.

[0040] When a user searches for a design work, they access the search screen and enter a search query. The device sends the entered search query to the server, which then searches and extracts relevant design works from the database. The server then uses AI to analyze the user's past search history, purchase history, and browsing history to generate design work suggestions based on the user's preferences. The search results and suggested design works are sent to the device and displayed to the user.

[0041] When a user wants to purchase a specific design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, who responds with an interface that allows the user to choose whether to approve or reject the request. When the server receives a response from the designer, it notifies the user of the result. If approval is granted, further negotiations and the purchase process can proceed.

[0042] For example, when a user searches for "modern designer house," the server searches the database for related design works and uses AI analysis to make optimal suggestions based on past history. Multiple design works are displayed to the user as search results. If the user likes one of them and submits a purchase request, the designer is notified, and the deal is concluded after the designer's approval.

[0043] This system allows users to efficiently find their ideal design work and gives designers the opportunity to offer their work to the right users.

[0044] The processing flow will be explained below.

[0045] User Registration and Login

[0046] User registration process

[0047] Step 1:

[0048] The user accesses the registration screen and enters personal information such as name, email address, and password.

[0049] Step 2:

[0050] The terminal checks the information entered to see if there are any omissions or errors.

[0051] Step 3:

[0052] The device sends the verified information to the server.

[0053] Step 4:

[0054] The server receives the personal information sent and stores it in a database.

[0055] Step 5:

[0056] The server sends a save success message to the terminal.

[0057] Step 6:

[0058] The device displays a registration success message to the user.

[0059] Login process

[0060] Step 1:

[0061] The user accesses the login screen and enters their email address and password.

[0062] Step 2:

[0063] The device sends the entered email address and password to the server.

[0064] Step 3:

[0065] The server checks the user information against the information stored in its database.

[0066] Step 4:

[0067] The server sends the login success or failure status to the terminal.

[0068] Step 5:

[0069] The terminal displays a login success or login failure message to the user.

[0070] Submission of design works

[0071] Step 1:

[0072] The user (designer) accesses the work submission screen and enters metadata such as the work's image file, title, description, and tags.

[0073] Step 2:

[0074] The device temporarily stores the entered information and checks the file format and content.

[0075] Step 3:

[0076] The device sends the verified information to the server.

[0077] Step 4:

[0078] The server receives the transmitted information and stores it in a database.

[0079] Step 5:

[0080] The server sends a save success message to the terminal.

[0081] Step 6:

[0082] The device will display a listing success message to the designer.

[0083] Design search and suggestions

[0084] Search processing

[0085] Step 1:

[0086] The user accesses the search screen and enters a search query (keywords or category).

[0087] Step 2:

[0088] The terminal transmits the entered search query to the server.

[0089] Step 3:

[0090] The server searches the database for relevant designs and filters the results.

[0091] Step 4:

[0092] The server sends the filtered search results to the device.

[0093] Step 5:

[0094] The device displays the search results to the user.

[0095] Proposal Processing

[0096] Step 1:

[0097] The server retrieves the user's past search history, purchase history, and browsing history from a database.

[0098] Step 2:

[0099] The server analyzes this data using AI to identify user preferences.

[0100] Step 3:

[0101] The server searches the database for design works that may suit the user and generates a list of recommended works.

[0102] Step 4:

[0103] The server sends a list of recommended works to the terminal.

[0104] Step 5:

[0105] The device displays recommended works to the user.

[0106] Purchases and negotiations

[0107] Purchase Request Processing

[0108] Step 1:

[0109] The user accesses the details page of the design work they wish to purchase and clicks the "Purchase Request" button.

[0110] Step 2:

[0111] The device sends the purchase request information (user information, work information) to the server.

[0112] Step 3:

[0113] The server notifies the designer of the received request and saves the request in the database.

[0114] Step 4:

[0115] The server provides an interface for the designer to approve or deny the request.

[0116] Step 5:

[0117] The designer approves or denies the request and sends the response to the server.

[0118] Step 6:

[0119] The server receives the response from the designer and notifies the user of the result.

[0120] Step 7:

[0121] The device displays the results of the request to the user.

[0122] Example 1

[0123] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0124] The challenge is to efficiently match users with designers, enabling users to quickly and appropriately find the design works they are looking for, and enabling designers to effectively provide their work to interested users. The current system has difficulty accurately reflecting users' search intent and preferences, resulting in a long wait for users to find the work they are looking for. Designers also face the risk of missing sales opportunities, as they are uncertain whether their work will reach the right target audience.

[0125] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0126] In this invention, the server includes: means for users to register personal information through various input forms; means for transmitting the registered information to the server and saving it in a database; means for verifying registered user information and performing authentication; means for designers to upload design works and input metadata about the works (title, description, tags, etc.); means for transmitting the design works and their metadata to the server and saving them in the database; means for users to input search queries and send them to the server; means for the server to search for related designs from the database and generate suggestions based on the user's tastes and preferences using a generative AI model; means for users to issue purchase requests and notify designers of the requests; and means for receiving purchase approval or rejection from designers and notifying the user of the results. This allows users to efficiently find their ideal design works and gives designers the opportunity to offer their works to appropriate users.

[0127] "User" means any individual or entity that accesses the System to search, browse, and purchase Design Works.

[0128] "Designer" means an individual or entity that creates a design work and uploads it to the System.

[0129] "Server" means the central management system that receives, processes and stores information from Users and Designers.

[0130] "Database" refers to the collection of digital data managed by the server for storing and managing information submitted by Users and Designers.

[0131] "Personal information" refers to information that identifies an individual, such as name, email address, password, etc., that a user or designer registers in the system.

[0132] "Metadata" refers to additional information about a design work, such as title, description, and tags.

[0133] "Generative AI model" refers to an algorithm and the means to implement it that uses artificial intelligence to analyze a user's tastes and preferences and suggest optimal design works.

[0134] "Purchase Request" means a request by a User to indicate their intent to purchase a particular Design Work and notify a Designer of such intent.

[0135] "Authentication" refers to the process of verifying a user's or designer's registration information to ensure that the person has legitimate access rights.

[0136] "Proposal" refers to a design work selected based on the user's tastes and preferences as a result of analysis using a generative AI model.

[0137] "Notification" means a message or alert sent by the Server to provide specific information to a User or Designer.

[0138] The present invention is a system for efficiently matching users and designers, and is implemented using specific hardware and software. The system includes a series of processes for improving the experience for both users and designers. The details are described below.

[0139] First, a user accesses the system and registers. At this time, the user enters personal information such as name, email address, and password. The terminal sends this information to the server, which then stores the received information in a database. If the storage is successful, the server returns a registration success message to the terminal, which then displays this message to the user.

[0140] Next, when a designer wants to exhibit their design, they enter metadata such as the image file, title, description, and tags of the work. The device temporarily stores this information, checks the format and content, and then sends it to the server. The server stores the information in a database and returns a success message to the device, which then displays a successful exhibit message to the designer.

[0141] When a user searches for a design work, they access the search screen and enter a search query. The device sends the entered search query to the server, which then searches and extracts relevant design works from the database. The server then uses a generative AI model (e.g., TENSORFLOW (registered trademark), PyTorch) to analyze the user's past search history, purchase history, and browsing history, and generates design work suggestions based on the user's tastes and preferences. The search results and suggested design works are sent to the device, which then displays them to the user.

[0142] When a user wants to purchase a particular design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, who responds with an interface that allows the user to choose whether to approve or reject the request. Once the server receives a response from the designer, it notifies the user of the result. If approved, the user can proceed with detailed negotiations and the purchase process.

[0143] For example, if a user searches for "modern designer house," the server searches the database for related design works and uses a generative AI model to make optimal suggestions based on past history. Multiple design works are displayed to the user as search results, and the user submits a purchase request for the work they like. The designer is notified, and if approved, the deal is concluded.

[0144] Examples of prompts for generative AI models include:

[0145] "Suggest design pieces that might interest you based on your past search and purchase history."

[0146] "Search for design work related to modern designer homes and see the best results."

[0147] This system allows users to efficiently find their ideal design work, and gives designers the opportunity to offer their work to the right users. Furthermore, by using a generative AI model, highly accurate suggestions that match the user's tastes and preferences can be realized.

[0148] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0149] Step 1:

[0150] The user accesses the new registration page. The user enters personal information such as name, email address, and password. This input data is acquired by the terminal and sent to the server. The server stores the received information in a database. If the storage is successful, the server generates a registration success message and sends it to the terminal. The terminal displays this message to the user.

[0151] Input: Personal information such as name, email address, and password

[0152] Output: Registration successful message

[0153] Step 2:

[0154] The designer accesses the work submission page and enters metadata such as the work's image file, title, description, and tags. The device temporarily saves this information and checks its format and content. After format and content checks are complete, the device sends the information to the server. The server saves the received information in a database. If the save is successful, the server generates a save success message and sends it to the device. The device displays this message to the designer.

[0155] Input: Image file, metadata such as title, description, tags etc.

[0156] Output: Listing successful message

[0157] Step 3:

[0158] The user accesses the search screen and enters a search query. The device sends this search query to the server, which searches and extracts relevant design works from the database. The server then uses a generative AI model to analyze the user's past search history, purchase history, and browsing history to generate suggestions based on the user's tastes and preferences. The generated search results and suggestions are sent from the server to the device, which then displays them to the user.

[0159] Input: Search queries, user's past search history, purchase history, browsing history

[0160] Output: Search results and proposed design work

[0161] Step 4:

[0162] When a user wants to purchase a specific design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, who can then choose to approve or reject it. The designer's response is sent to the server, which then notifies the user accordingly. If the request is approved, the user can proceed with further negotiations and the purchase process.

[0163] Input: Purchase request information (user information, work information)

[0164] Output: Notification of purchase request outcome (approval or rejection)

[0165] The combination of specific processes at each step allows for smooth communication between the user and the designer, and the use of generative AI models allows for highly accurate suggestions based on the user's preferences.

[0166] (Application example 1)

[0167] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0168] In previous user-designer matching systems, users had limited access to detailed information and purchasing options for specific designs in physical stores, making efficient matching difficult. Furthermore, optimal suggestions based on a user's past purchase history were often not effectively provided. This made it difficult for users to find designs that matched their tastes, and prevented designers from making the most of opportunities to offer their work to the right users.

[0169] 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.

[0170] In this invention, the server includes: means for a user to register personal information through various input forms; means for transmitting the registered information to the server and saving it in a database; means for verifying registered user information and performing authentication; means for a designer to upload a design work and input metadata (title, description, tags, etc.) related to the work; means for transmitting the design work and its metadata to the server and saving it in the database; means for a user to input a search query and send it to the server; means for the server to search for related designs from the database and perform AI analysis to generate suggestions based on the user's tastes and preferences; means for the user to display the search results and suggested design works to the user; means for the user to issue a purchase request and notify the designer of the request; means for the user to read a two-dimensional code related to a target item; and means for displaying metadata and purchase options for the target item based on the read two-dimensional code. This allows users to intuitively and efficiently obtain detailed information about design works and submit purchase requests in physical stores, and also enables AI to suggest optimal design works based on past history.

[0171] "User" means any individual or organization that accesses the System to search for and request the purchase of Design Works.

[0172] "Designer" means an individual or organization that uploads and provides design work to the system.

[0173] "Personal information" refers to information such as name, email address, and password that users or designers register through various input forms.

[0174] "Metadata" refers to supplemental information, such as titles, descriptions, and tags, associated with a design work that specifically describes the characteristics of the work.

[0175] A "two-dimensional code" is a code pattern such as a QR code (registered trademark) that stores information and allows quick data access by reading it.

[0176] "Purchase Request" means a request made by a User to purchase a particular Design Work, which is communicated to a Designer.

[0177] A "database" is a storage area within a system that systematically stores information about users and designers, design works, and their metadata, and enables searching and retrieval.

[0178] A "server" is a computer device that receives and processes information sent by users and designers, and provides various functions in cooperation with a database.

[0179] "AI analysis" is the process of using artificial intelligence technology to analyze a user's past search history, purchase history, and browsing history, and generate design suggestions based on the user's preferences.

[0180] A "search query" is a keyword or phrase entered by a user to search for design work.

[0181] This invention is a system for efficiently matching users and designers, and is intended for use in brick-and-mortar stores. The system is composed of multiple hardware and software components.

[0182] 1. User Registration and Authentication:

[0183] Users access the system and enter personal information such as their name, email address, and password through various input forms. This information is sent from the terminal to the server, which stores the received information in a database. The registered user information is verified and authentication is performed. Through this procedure, the user gains access to the system.

[0184] Hardware used: User device (smartphone or tablet)

[0185] Software used: Web browser, Flask (Python web framework)

[0186] 2. Upload your design:

[0187] Designers upload their design work to the system and enter metadata about the work (title, description, tags, etc.). This information is temporarily stored on the device and sent to the server after format and content checks. The server stores the received information in a database, and the designer is notified of a successful upload.

[0188] Hardware used: Designer's device (PC or tablet)

[0189] Software used: Web browser, Flask, SQLite3

[0190] 3. QR Code Scan:

[0191] Users scan QR codes associated with design pieces displayed in physical stores with their smartphones. The scanned QR code is sent to a server to display the item's metadata and purchasing options. The server retrieves the corresponding information from a database and sends it back to the user's device, where the user can view detailed information about the piece.

[0192] Hardware used: User device (smartphone)

[0193] Software used: QR code reader, Flask, SQLite3

[0194] 4. AI Recommendations:

[0195] The server collects the user's past search history, purchase history, and browsing history and performs AI analysis. An AI model (e.g., RandomForestClassifier) ​​uses this data to identify the user's preferences and generate optimal design proposals. These recommendations are sent to the user's device and displayed to the user.

[0196] Hardware used: Server

[0197] Software used: scikit-learn (Python machine learning library), Flask, SQLite3

[0198] Examples:

[0199] When a user searches for "modern design furniture" in a physical store, the server searches the database for related design works and uses AI analysis to make optimal suggestions based on past history. Multiple recommended design works are displayed on the user's smartphone, and they can submit a purchase request from the detail page of the work they like.

[0200] Example prompt sentence:

[0201] User ID: 12345

[0202] Previous browsing history: ["modern design", "simple furniture", "Scandinavian style"]

[0203] Purchase history: ["Simple chair", "Scandinavian-style table"]

[0204] Please suggest designs based on this history.

[0205] This invention allows users to intuitively and efficiently obtain detailed information about design items and submit purchase requests in a physical store, while also enabling AI to suggest optimal design items based on past history.

[0206] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0207] Step 1:

[0208] The user uses a device to enter personal information (such as name, email address, and password) through various input forms. The entered personal information is sent from the device to the server. The server stores the received information in a database. At this stage, the entered information is recorded in the database as is (data storage).

[0209] Input: Personal information (name, email address, password)

[0210] Output: User information stored in the database

[0211] Step 2:

[0212] The server compares the received personal information with the database and authenticates the user. If the comparison is correct, it sends a message to the device indicating successful registration. During this process, the user is authenticated by comparing the information with the information in the database (data comparison and authentication).

[0213] Input: User information stored in the database

[0214] Output: Registration successful message

[0215] Step 3:

[0216] Designers use their devices to upload their design work to the system. They enter metadata such as the work's image file, title, description, and tags, and the uploaded information is temporarily stored on the device. It is then checked for format and content before being sent to the server. The server stores the received information in a database and displays a message to the designer indicating that the upload was successful. This is where metadata is entered and saved (data entry, checking, and saving).

[0217] Input: Image file of design work, metadata (title, description, tags, etc.)

[0218] Output: Design information saved in the database, upload success message

[0219] Step 4:

[0220] A user scans a QR code with their smartphone in a physical store. The data from the scanned QR code is sent from the device to a server, which retrieves the metadata and purchase options for the item from a database. The retrieved information is sent back to the device and displayed to the user. In this step, the QR code is scanned, the database is searched, and the information is retrieved and displayed (data retrieval and display).

[0221] Input: QR code data

[0222] Output: Metadata and purchase options for the item

[0223] Step 5:

[0224] The user enters a search query and sends it from their device to the server. The server searches for relevant designs in the database and performs AI analysis to generate recommendations based on the user's preferences. The generated recommendations are sent to the device and displayed to the user. In this step, analysis and recommendation generation are performed using an AI model (data analysis and recommendations).

[0225] Input: Search query

[0226] Output: Search results and recommendations

[0227] Step 6:

[0228] When a user wants to purchase a particular design work, they press the "Purchase Request" button on the details page. The terminal sends the purchase request information (user information, work information) to the server. The server notifies the designer of the request, and the designer responds with an interface that allows the user to choose whether to accept or reject. When the server receives the response from the designer, it notifies the user of the result. In this step, the purchase request is issued, notified, and responded to and notified (request generation and processing).

[0229] Input: Purchase request information (user information, work information)

[0230] Output: Designer's response results

[0231] Step 7:

[0232] The server collects the user's past search history, purchase history, and browsing history, and performs AI analysis based on this. An AI model (e.g., RandomForestClassifier) ​​uses this data to identify the user's tastes and preferences and recommend the most suitable design pieces. This process involves analysis and recommendation generation using machine learning models.

[0233] Input: Past search history, purchase history, browsing history

[0234] Output: Proposal of optimal design work

[0235] For example, here is a prompt example for a user searching for "modern furniture design":

[0236] Example prompt sentence:

[0237] User ID: 12345

[0238] Previous browsing history: ["modern design", "simple furniture", "Scandinavian style"]

[0239] Purchase history: ["Simple chair", "Scandinavian-style table"]

[0240] Please suggest designs based on this history.

[0241] Through these steps, users can efficiently obtain detailed information about design works and submit purchase requests, while AI can suggest the most suitable design works based on past history.

[0242] 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.

[0243] The present invention is a matching system for users and designers that combines an emotion engine, and is implemented in the following steps.

[0244] First, the user accesses the system and enters personal information such as name, email address, and password on the new registration page. The terminal sends this information to the server, which stores the received information in a database. If registration is successful, the terminal displays a registration success message to the user.

[0245] Next, the designer uploads the image file, title, description, tags, and other metadata of the work to be exhibited. The device temporarily saves this information, checks the format and content, and then sends it to the server. The server saves the received information in a database and returns a message to the device indicating that the save was successful, displaying a message to the designer indicating that the exhibit was successful.

[0246] When a user searches for a design work, they access the search screen and enter a search query. The device sends the entered search query to the server, which then searches for and extracts relevant design works from a database. The server then analyzes the user's past search history, purchase history, and browsing history and performs an AI analysis. An emotion engine also obtains emotional data from the user's reactions and facial expressions and sends that data to the server. The server combines this data to generate design work suggestions based on the user's tastes and preferences, and displays the search results and suggested design works to the user.

[0247] When a user wants to purchase a specific design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, who responds with an interface that allows the user to choose whether to approve or reject the request. When the server receives a response from the designer, it notifies the user of the result. If approval is granted, further negotiations and the purchase process can proceed.

[0248] As a specific example, when a user searches for "modern designer house," the server searches the database for related design works, combines AI analysis with data obtained from the emotion engine, and makes optimal suggestions based on the user's past history and reactions. For example, if the emotion engine recognizes an "interest" in a design work that the user is looking at with interest, it will recommend designs similar to that work. Multiple design works are displayed to the user as search results. If the user likes one of them and submits a purchase request, the designer is notified, and the deal is concluded after the designer's approval.

[0249] This system allows users to intuitively and efficiently find their ideal design work, and gives designers the opportunity to deliver their work to the right users. By combining it with an emotion engine, personalized suggestions based on user emotions can be made, resulting in even higher satisfaction.

[0250] The processing flow will be explained below.

[0251] User Registration and Login

[0252] User registration process

[0253] Step 1:

[0254] The user accesses the registration screen and enters personal information such as name, email address, and password.

[0255] Step 2:

[0256] The terminal checks the information entered to see if there are any omissions or errors.

[0257] Step 3:

[0258] The device sends the verified information to the server.

[0259] Step 4:

[0260] The server receives the personal information sent and stores it in a database.

[0261] Step 5:

[0262] The server sends a save success message to the terminal.

[0263] Step 6:

[0264] The device displays a registration success message to the user.

[0265] Login process

[0266] Step 1:

[0267] The user accesses the login screen and enters their email address and password.

[0268] Step 2:

[0269] The device sends the entered email address and password to the server.

[0270] Step 3:

[0271] The server checks the user information against the information stored in its database.

[0272] Step 4:

[0273] The server sends the login success or failure status to the terminal.

[0274] Step 5:

[0275] The terminal displays a login success or login failure message to the user.

[0276] Submission of design works

[0277] Step 1:

[0278] The user (designer) accesses the work submission screen and enters metadata such as the work's image file, title, description, and tags.

[0279] Step 2:

[0280] The device temporarily stores the entered information and checks the file format and content.

[0281] Step 3:

[0282] The device sends the verified information to the server.

[0283] Step 4:

[0284] The server receives the transmitted information and stores it in a database.

[0285] Step 5:

[0286] The server sends a save success message to the terminal.

[0287] Step 6:

[0288] The device will display a listing success message to the designer.

[0289] Design search and suggestions

[0290] Search processing

[0291] Step 1:

[0292] The user accesses the search screen and enters a search query (keywords or category).

[0293] Step 2:

[0294] The terminal transmits the entered search query to the server.

[0295] Step 3:

[0296] The server searches the database for relevant design work and filters the results.

[0297] Step 4:

[0298] The server sends the filtered search results to the device.

[0299] Step 5:

[0300] The device displays the search results to the user.

[0301] Proposal Processing

[0302] Step 1:

[0303] The server retrieves the user's past search history, purchase history, and browsing history from a database.

[0304] Step 2:

[0305] The server analyzes this data using AI to identify user preferences.

[0306] Step 3:

[0307] The server searches the database for design works that may suit the user and generates a list of recommended works.

[0308] Step 4:

[0309] The server sends a list of recommended works to the terminal.

[0310] Step 5:

[0311] The device displays recommended works to the user.

[0312] Emotion recognition and suggestions using an emotion engine

[0313] Emotion Recognition Processing

[0314] Step 1:

[0315] While users search and browse design works, the emotion engine uses cameras and sensors to detect the user's facial expressions and reactions.

[0316] Step 2:

[0317] The device transmits the detected emotion data to the server.

[0318] Step 3:

[0319] The server uses AI to analyze the emotional data received and identify the user's current emotional state.

[0320] Emotion-based suggestion generation

[0321] Step 1:

[0322] The server combines the user's preference trend data and emotional data previously acquired and re-searches for related design works from the database.

[0323] Step 2:

[0324] The server generates a list of recommended works based on the emotions.

[0325] Step 3:

[0326] The server sends a list of recommended works to the terminal.

[0327] Step 4:

[0328] The device displays emotionally-based recommendations to the user.

[0329] Purchases and negotiations

[0330] Purchase Request Processing

[0331] Step 1:

[0332] The user accesses the details page of the design work they wish to purchase and clicks the "Purchase Request" button.

[0333] Step 2:

[0334] The device sends the purchase request information (user information, work information) to the server.

[0335] Step 3:

[0336] The server notifies the designer of the received request and saves the request in the database.

[0337] Step 4:

[0338] The server provides an interface for the designer to approve or deny the request.

[0339] Step 5:

[0340] The designer approves or denies the request and sends the response to the server.

[0341] Step 6:

[0342] The server receives the response from the designer and notifies the user of the result.

[0343] Step 7:

[0344] The device displays the results of the request to the user.

[0345] Example 2

[0346] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0347] Conventional user-designer matching systems lacked personalized suggestions based on the user's preferences and emotions. This made it difficult for users to quickly find designs that matched their tastes and emotions, resulting in low satisfaction. Furthermore, communication between users and designers was sometimes insufficient during the purchasing process, reducing transaction efficiency.

[0348] The specification processing by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring user emotion data and transmitting it to the server, means for the server to analyze the user emotion data and reflect it in the generation of proposed works, and means for collecting the user's past search history, purchase history, browsing history, and emotion data and identifying the user's preference trends using AI based on this. This enables the user to receive proposals for optimal design works based on their emotions and preferences, and furthermore, the purchasing procedure between the user and the designer is carried out smoothly, improving the usability and satisfaction of the entire system.

[0349] "User" means an individual or organization that uses this system to search for and purchase design works.

[0350] "Designers" are individuals or organizations that use this system to upload and sell their design works.

[0351] "Emotional data" refers to information about emotions obtained from a user's reactions, facial expressions, voice, etc.

[0352] A "server" is a computer system responsible for receiving and processing information sent by users and designers.

[0353] A "database" is a system installed on a server for efficiently managing and searching information.

[0354] A "search query" is a keyword or phrase that a user enters when searching for design work.

[0355] "Metadata" is additional information about a design work, including title, description, tags, etc.

[0356] A "generative AI model" is an artificial intelligence model used to analyze a user's habits and preferences and suggest optimal design pieces.

[0357] "Purchase Request" means a request submitted by a User wishing to purchase a particular Design Product.

[0358] "Proposed works" are design works that the server recommends based on the user's history and emotional data.

[0359] "Upload" refers to the data transmission operation that a designer performs to register his or her design work in the system.

[0360] "Authentication" is the process of verifying the legitimacy of users and designers when they access a system.

[0361] "Viewing history" refers to historical information about design works and pages that a user has previously viewed on the system.

[0362] The present invention is a matching system for users and designers that combines an emotion engine. The specific configuration and processing of this system will be described in detail below.

[0363] First, a user accesses the system and enters personal information such as name, email address, and password on the new registration page. This is done using a device (such as the user's PC or smartphone), and the entered information is sent to the server via the HTTP protocol. The server then stores the received information in a database (for example, MySQL (registered trademark)). This ensures that the user's personal information is managed securely.

[0364] Next, when a designer uploads their design work to the system, they enter the image file and its metadata (title, description, tags, etc.). This information is temporarily stored on the device and checked for format and content. It is then sent to the server, where the image file is stored in file storage (e.g., AWS (registered trademark) S3) and the metadata is stored in a database.

[0365] When a user searches for a design work, they access the search screen and enter a search query. The device sends this search query to the server, which then searches and extracts relevant design works from the database. The server then collects the user's past search history, purchase history, and browsing history and performs AI analysis. For example, it uses machine learning models such as TensorFlow and PyTorch to identify the user's preferences.

[0366] The emotion engine captures the user's reactions and facial expressions through a camera and microphone, and sends the generated emotion data from the device to a server. The server combines this emotion data with past history data to generate optimal suggestions. This allows users to receive personalized suggestions based on their emotions and preferences.

[0367] When a user wants to purchase a specific design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, who can then choose to approve or reject it. When the server receives a response from the designer, it notifies the user of the result. If approved, further negotiations and the purchase process can proceed.

[0368] As a concrete example, consider a user searching for "modern designer house." The server processes this search query and searches the database for related design works. By combining data from AI analysis and an emotion engine, the server makes optimal suggestions based on the user's past history and reactions. For example, if a user expresses an "interest" in a particular design, similar designs will be suggested.

[0369] Prompt Sentence Examples

[0370] 1. Prompt to display recommended design works when searching for "modern designer homes":

[0371] A user is searching for "modern design pieces." Please recommend the best design pieces based on the data below.

[0372] Search Query: modern designer house

[0373] User's past search history: [e.g. "contemporary design", "simple modern"]

[0374] User purchase history: [e.g., "Scandinavian interior design," "Minimalist art"]

[0375] User sentiment data: [e.g., interest level for search query: high]

[0376] 2. Prompt for generating a design purchase request:

[0377] A user wants to purchase a specific design piece. Please generate a purchase request using the following user and piece information:

[0378] User information: Taro, Email address: taro@example.com

[0379] Work information: Title: Modern Designer's House, Designer: Hanako

[0380] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0381] System processing flow

[0382] Step 1: Sign up

[0383] input:

[0384] A user accesses the new registration page and enters personal information such as name, email address, and password.

[0385] Specific behavior:

[0386] The device (user's PC or smartphone) temporarily stores this input data and checks the format of the input.

[0387] Data processing and calculation:

[0388] The terminal performs format checks on the input data (e.g., checking the format of the email address, checking the strength of the password).

[0389] output:

[0390] Based on the check results, if appropriate, the data is sent to the server, otherwise an error message is displayed to the user.

[0391] Step 2: Send and store user information

[0392] input:

[0393] User personal information sent from the device (name, email address, password).

[0394] Specific behavior:

[0395] The device sends information to the server via an HTTP request, and the server validates the received data.

[0396] Data processing and calculation:

[0397] The server validates the incoming data (e.g. checks for duplicate email addresses) and converts it into a secure data format.

[0398] output:

[0399] If validation is successful, the server saves the information in the database (MySQL) and returns a registration success message to the terminal.

[0400] Step 3: Upload your design

[0401] input:

[0402] Metadata entered by the designer, such as image files, title, description, and tags for the work.

[0403] Specific behavior:

[0404] The device temporarily stores this information and checks its format and content. Image file format checks (e.g., JPEG, PNG) are also performed.

[0405] Data processing and calculation:

[0406] The device checks the consistency of the metadata and image file, and performs image processing such as resizing and compression as necessary.

[0407] output:

[0408] If the check is successful, the terminal transmits the information to the server.

[0409] Step 4: Send and save your design to the server

[0410] input:

[0411] Image files and metadata of design work sent from your device.

[0412] Specific behavior:

[0413] The server receives this data, uploads the image files to file storage (AWS S3), and stores the metadata in a database.

[0414] Data processing and calculation:

[0415] The server validates the metadata, generates a URL for saving to file storage, and saves it in the database.

[0416] output:

[0417] If the saving is successful, the server returns a message to the terminal indicating that the listing was successful and notifies the designer.

[0418] Step 5: Find design ideas

[0419] input:

[0420] The search query entered by the user on the search screen (e.g., "modern designer home").

[0421] Specific behavior:

[0422] The terminal transmits the input search query to the server.

[0423] Data processing and calculation:

[0424] Based on the received query, the server generates an SQL query and extracts relevant design works from the database.

[0425] output:

[0426] Based on the search results and past search, purchase, and browsing history, the server generates a JSON response and sends it back to the device, which then displays it to the user.

[0427] Step 6: Generate a proposal

[0428] input:

[0429] Search results and your past search history, purchase history, browsing history, and sentiment data.

[0430] Specific behavior:

[0431] The server inputs this data into an AI model (TensorFlow or PyTorch) for analysis. It also obtains reaction data from the emotion engine and reflects it in the analysis.

[0432] Data processing and calculation:

[0433] The AI ​​model identifies user preferences and generates optimal product suggestions, while also analyzing emotional data to calculate the user's interest level.

[0434] output:

[0435] The server generates the proposed results and sends them to the device, which then displays them to the user.

[0436] Step 7: Submitting a Purchase Request

[0437] input:

[0438] Request information (user information, work information) sent by the user by pressing the "Purchase Request" button.

[0439] Specific behavior:

[0440] The terminal transmits this information to the server.

[0441] Data processing and calculation:

[0442] The server validates the request information and forwards it to the designer with notification.

[0443] output:

[0444] The server notifies the designer of the request and waits for the designer's response.

[0445] Step 8: Designer response and user notification

[0446] input:

[0447] The designer has the choice to approve or reject the request.

[0448] Specific behavior:

[0449] The designer's device sends the selection results to the server, which receives them and takes appropriate action.

[0450] Data processing and calculation:

[0451] The server generates a result notification for the user based on the designer's response.

[0452] output:

[0453] The server notifies the user of the response result and, if approved, assists with further purchase procedures.

[0454] (Application example 2)

[0455] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0456] Conventional user-designer matching systems lack the ability to provide personalized suggestions that fully reflect a user's individual tastes and emotions. As a result, users spend a long time finding their ideal design, and designers have limited opportunities to offer their work to the right users. Furthermore, especially when providing immersive experiences such as virtual stores, a system that reflects user emotions in real time and makes design discovery easier and seamless is needed.

[0457] 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.

[0458] In this invention, the server includes: means for users to register personal information through various input forms; means for transmitting the registered information to the server and saving it in a database; means for verifying registered user information and performing authentication; means for designers to upload design works and input metadata about the works (e.g., title, description, tags, etc.); means for transmitting the design works and their metadata to the server and saving them in the database; means for users to input search queries and send them to the server; means for the server to search for related designs from the database and perform AI analysis to generate proposals based on the user's tastes and preferences; means for displaying the search results and proposed design works to the user; means for acquiring emotional data from the user's reactions and facial expressions using an emotion analysis device; means for transmitting the acquired emotional data to the server and combining it with AI analysis to provide personalized design proposals to the user; and means for users to issue purchase requests and notify designers of the requests. This enables personalized proposals in real time based on the user's emotions, making it easier for users to efficiently find their ideal designs and increasing designers' opportunities to provide their works to appropriate users.

[0459] "User" means an individual or corporation that uses the System to search for and purchase design works.

[0460] "Designer" means an individual or legal entity responsible for uploading design works to the system.

[0461] "Server" refers to a computer system that receives data sent by users and designers, and stores and manages the data in a database.

[0462] A "database" is a system connected to a server for systematically storing and managing user information and metadata of design works.

[0463] "Metadata" refers to additional information such as title, description, and tags associated with a design work.

[0464] An "emotion analysis device" is a device that captures and analyzes emotional data from a user's reactions and facial expressions.

[0465] "Emotion data" is user emotion information acquired by the emotion analysis device.

[0466] "AI analysis" is the process of using artificial intelligence technology to analyze users' tastes, preferences, and emotional data and generate suggestions.

[0467] "Personalized proposals" are proposals for customized design works based on the user's individual tastes, preferences, and emotional data.

[0468] A "Purchase Request" is a request by a User to express their intent to purchase a particular Design Work.

[0469] A "notification" is a message that conveys information from the server to the designer or user.

[0470] This system is a comprehensive platform that allows users to efficiently search and purchase design works and allows designers to deliver their works to the right customers. Specific embodiments are described below.

[0471] User Registration

[0472] First, the user accesses the system and enters personal information such as name, email address, and password on the new registration page. The terminal sends this information to the server, which stores the received information in a database. If registration is successful, the terminal displays a registration success message to the user.

[0473] Upload your design

[0474] Next, the designer uploads their design. The designer enters metadata such as the image file, title, description, and tags of the work and uploads it. The device temporarily saves this information, checks the format and content, and then sends it to the server. The server saves the received information in a database and returns a message to the device indicating that the save was successful, displaying a message to the designer indicating that the listing was successful.

[0475] Sentiment analysis and AI suggestions

[0476] When a user searches for a design work, they access the search screen and enter a search query. The device sends the entered search query to the server, which then searches for and extracts relevant design works from a database. The server then collects the user's past search history, purchase history, and browsing history and performs AI analysis. An emotion analyzer (such as OpenCV or Face API) obtains emotional data from the user's reactions and facial expressions and sends that data to the server. The server combines this data and uses a deep learning framework (such as TensorFlow or PyTorch) to generate optimal suggestions based on the user's preferences and tastes, which are then displayed to the user along with the search results.

[0477] Purchase Process

[0478] When a user wants to purchase a specific design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, and the designer responds in real time using Firebase Cloud Messaging. When the server receives a response from the designer (approval or rejection), it notifies the user of the result.

[0479] Specific examples

[0480] As a concrete example, when a user searches for "modern designer house," the server searches the database for related design works and uses AI analysis and an emotion engine to make optimal suggestions based on the user's past history and reactions. For example, if the emotion engine recognizes an "interest" in a design work that the user is looking at with interest, it will recommend designs similar to that work. Multiple design works are displayed to the user as search results. If the user likes one of them and submits a purchase request, the designer is notified, and the deal is concluded after the designer's approval.

[0481] Prompt Sentence Examples

[0482] "I'm looking for a modern designer home. I'm looking for a design similar to the urban interiors I've seen in the past. Also, please use sentiment analysis to suggest which design would be best for me."

[0483] The above is a concrete example of how the present invention can be implemented. Users can efficiently find their ideal design work through real-time suggestions based on their emotions, and designers can have the opportunity to provide their work to the right users.

[0484] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0485] Step 1:

[0486] The user enters personal information (name, email address, password, etc.) on the new registration page.

[0487] Input: The user enters personal information.

[0488] Data processing: The terminal sends these data to the server.

[0489] Output: The server stores the received information in a database and displays a registration success message on the terminal.

[0490] Step 2:

[0491] Designers upload their design work and enter the work's metadata (image file, title, description, tags, etc.).

[0492] Input: Designers input design work and metadata.

[0493] Data processing: The device temporarily stores this data and checks its format and content.

[0494] Output: Sent to server and saved in database. A message of successful saving is displayed in the designer.

[0495] Step 3:

[0496] A user enters a search query to search for design work.

[0497] Input: The user types a search query.

[0498] Data processing: The terminal sends the entered search query to the server, which then searches and extracts relevant design works from the database.

[0499] Output: The relevant design work is displayed to the user.

[0500] Step 4:

[0501] Using AI and sentiment analysis, suggestions are generated based on the user's tastes and preferences.

[0502] Input: Past search history, purchase history, browsing history, and emotional data obtained from reactions and facial expressions.

[0503] Data processing: The server analyzes the data using deep learning frameworks (TensorFlow, PyTorch) and generates personalized suggestions.

[0504] Output: A list of proposed design works is displayed to the user.

[0505] Step 5:

[0506] The user places a purchase request and notifies the designer of the request.

[0507] Input: User information, work information.

[0508] Data processing: The terminal sends the purchase request information to the server.

[0509] Output: The server notifies the designer of the request.

[0510] Step 6:

[0511] The designer responds to the purchase request.

[0512] Input: Approval or rejection response from the designer.

[0513] Data processing: The server receives the designer's response and notifies the user.

[0514] Output: The user is shown the approval or rejection result.

[0515] Step 7:

[0516] If the deal is successful, the user and designer will proceed with detailed negotiations.

[0517] Input: Opportunity details.

[0518] Data processing: Transaction-related information is stored on the server and updated and managed as necessary.

[0519] Output: A notification of the transaction completion is sent to both parties.

[0520] 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.

[0521] 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> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0522] 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.

[0523] [Second embodiment]

[0524] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0525] 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.

[0526] 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).

[0527] 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.

[0528] 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.

[0529] 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).

[0530] 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.

[0531] 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.

[0532] 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.

[0533] 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.

[0534] 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.

[0535] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0536] The present invention is a system for efficiently matching users and designers, and is implemented in the following manner.

[0537] First, the user accesses the system and enters personal information such as name, email address, and password on the new registration page. The terminal sends this information to the server, which stores the received information in a database. If registration is successful, the terminal displays a registration success message to the user.

[0538] Next, the designer uploads the image file, title, description, tags, and other metadata of the work to be exhibited. The device temporarily saves this information, checks the format and content, and then sends it to the server. The server saves the received information in a database and returns a message to the device indicating that the save was successful, displaying a message to the designer indicating that the exhibit was successful.

[0539] When a user searches for a design work, they access the search screen and enter a search query. The device sends the entered search query to the server, which then searches and extracts relevant design works from the database. The server then uses AI to analyze the user's past search history, purchase history, and browsing history to generate design work suggestions based on the user's preferences. The search results and suggested design works are sent to the device and displayed to the user.

[0540] When a user wants to purchase a specific design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, who responds with an interface that allows the user to choose whether to approve or reject the request. When the server receives a response from the designer, it notifies the user of the result. If approval is granted, further negotiations and the purchase process can proceed.

[0541] For example, when a user searches for "modern designer house," the server searches the database for related design works and uses AI analysis to make optimal suggestions based on past history. Multiple design works are displayed to the user as search results. If the user likes one of them and submits a purchase request, the designer is notified, and the deal is concluded after the designer's approval.

[0542] This system allows users to efficiently find their ideal design work and gives designers the opportunity to offer their work to the right users.

[0543] The processing flow will be explained below.

[0544] User Registration and Login

[0545] User registration process

[0546] Step 1:

[0547] The user accesses the registration screen and enters personal information such as name, email address, and password.

[0548] Step 2:

[0549] The terminal checks the information entered to see if there are any omissions or errors.

[0550] Step 3:

[0551] The device sends the verified information to the server.

[0552] Step 4:

[0553] The server receives the personal information sent and stores it in a database.

[0554] Step 5:

[0555] The server sends a save success message to the terminal.

[0556] Step 6:

[0557] The device displays a registration success message to the user.

[0558] Login process

[0559] Step 1:

[0560] The user accesses the login screen and enters their email address and password.

[0561] Step 2:

[0562] The device sends the entered email address and password to the server.

[0563] Step 3:

[0564] The server checks the user information against the information stored in its database.

[0565] Step 4:

[0566] The server sends the login success or failure status to the terminal.

[0567] Step 5:

[0568] The terminal displays a login success or login failure message to the user.

[0569] Submission of design works

[0570] Step 1:

[0571] The user (designer) accesses the work submission screen and enters metadata such as the work's image file, title, description, and tags.

[0572] Step 2:

[0573] The device temporarily stores the entered information and checks the file format and content.

[0574] Step 3:

[0575] The device sends the verified information to the server.

[0576] Step 4:

[0577] The server receives the transmitted information and stores it in a database.

[0578] Step 5:

[0579] The server sends a save success message to the terminal.

[0580] Step 6:

[0581] The device will display a listing success message to the designer.

[0582] Design search and suggestions

[0583] Search processing

[0584] Step 1:

[0585] The user accesses the search screen and enters a search query (keywords or category).

[0586] Step 2:

[0587] The terminal transmits the entered search query to the server.

[0588] Step 3:

[0589] The server searches the database for relevant designs and filters the results.

[0590] Step 4:

[0591] The server sends the filtered search results to the device.

[0592] Step 5:

[0593] The device displays the search results to the user.

[0594] Proposal Processing

[0595] Step 1:

[0596] The server retrieves the user's past search history, purchase history, and browsing history from a database.

[0597] Step 2:

[0598] The server analyzes this data using AI to identify user preferences.

[0599] Step 3:

[0600] The server searches the database for design works that may suit the user and generates a list of recommended works.

[0601] Step 4:

[0602] The server sends a list of recommended works to the terminal.

[0603] Step 5:

[0604] The device displays recommended works to the user.

[0605] Purchases and negotiations

[0606] Purchase Request Processing

[0607] Step 1:

[0608] The user accesses the details page of the design work they wish to purchase and clicks the "Purchase Request" button.

[0609] Step 2:

[0610] The device sends the purchase request information (user information, work information) to the server.

[0611] Step 3:

[0612] The server notifies the designer of the received request and saves the request in the database.

[0613] Step 4:

[0614] The server provides an interface for the designer to approve or deny the request.

[0615] Step 5:

[0616] The designer approves or denies the request and sends the response to the server.

[0617] Step 6:

[0618] The server receives the response from the designer and notifies the user of the result.

[0619] Step 7:

[0620] The device displays the results of the request to the user.

[0621] Example 1

[0622] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0623] The challenge is to efficiently match users with designers, enabling users to quickly and appropriately find the design works they are looking for, and enabling designers to effectively provide their work to interested users. The current system has difficulty accurately reflecting users' search intent and preferences, resulting in a long wait for users to find the work they are looking for. Designers also face the risk of missing sales opportunities, as they are uncertain whether their work will reach the right target audience.

[0624] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0625] In this invention, the server includes: means for users to register personal information through various input forms; means for transmitting the registered information to the server and saving it in a database; means for verifying registered user information and performing authentication; means for designers to upload design works and input metadata about the works (title, description, tags, etc.); means for transmitting the design works and their metadata to the server and saving them in the database; means for users to input search queries and send them to the server; means for the server to search for related designs from the database and generate suggestions based on the user's tastes and preferences using a generative AI model; means for users to issue purchase requests and notify designers of the requests; and means for receiving purchase approval or rejection from designers and notifying the user of the results. This allows users to efficiently find their ideal design works and gives designers the opportunity to offer their works to appropriate users.

[0626] "User" means any individual or entity that accesses the System to search, browse, and purchase Design Works.

[0627] "Designer" means an individual or entity that creates a design work and uploads it to the System.

[0628] "Server" means the central management system that receives, processes and stores information from Users and Designers.

[0629] "Database" refers to the collection of digital data managed by the server for storing and managing information submitted by Users and Designers.

[0630] "Personal information" refers to information that identifies an individual, such as name, email address, password, etc., that a user or designer registers in the system.

[0631] "Metadata" refers to additional information about a design work, such as title, description, and tags.

[0632] "Generative AI model" refers to an algorithm and the means to implement it that uses artificial intelligence to analyze a user's tastes and preferences and suggest optimal design works.

[0633] "Purchase Request" means a request by a User to indicate their intent to purchase a particular Design Work and notify a Designer of such intent.

[0634] "Authentication" refers to the process of verifying a user's or designer's registration information to ensure that the person has legitimate access rights.

[0635] "Proposal" refers to a design work selected based on the user's tastes and preferences as a result of analysis using a generative AI model.

[0636] "Notification" means a message or alert sent by the Server to provide specific information to a User or Designer.

[0637] The present invention is a system for efficiently matching users and designers, and is implemented using specific hardware and software. The system includes a series of processes for improving the experience for both users and designers. The details are described below.

[0638] First, a user accesses the system and registers. At this time, the user enters personal information such as name, email address, and password. The terminal sends this information to the server, which then stores the received information in a database. If the storage is successful, the server returns a registration success message to the terminal, which then displays this message to the user.

[0639] Next, when a designer wants to exhibit their design, they enter metadata such as the image file, title, description, and tags of the work. The device temporarily stores this information, checks the format and content, and then sends it to the server. The server stores the information in a database and returns a success message to the device, which then displays a successful exhibit message to the designer.

[0640] When a user searches for a design work, they access the search screen and enter a search query. The device sends the entered search query to the server, which then searches and extracts relevant design works from the database. The server then uses a generative AI model (e.g., TensorFlow, PyTorch) to analyze the user's past search history, purchase history, and browsing history to generate design work suggestions based on the user's preferences. The search results and suggested design works are sent to the device, which then displays them to the user.

[0641] When a user wants to purchase a particular design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, who responds with an interface that allows the user to choose whether to approve or reject the request. Once the server receives a response from the designer, it notifies the user of the result. If approved, the user can proceed with detailed negotiations and the purchase process.

[0642] For example, if a user searches for "modern designer house," the server searches the database for related design works and uses a generative AI model to make optimal suggestions based on past history. Multiple design works are displayed to the user as search results, and the user submits a purchase request for the work they like. The designer is notified, and if approved, the deal is concluded.

[0643] Examples of prompts for generative AI models include:

[0644] "Suggest design pieces that might interest you based on your past search and purchase history."

[0645] "Search for design work related to modern designer homes and see the best results."

[0646] This system allows users to efficiently find their ideal design work, and gives designers the opportunity to offer their work to the right users. Furthermore, by using a generative AI model, highly accurate suggestions that match the user's tastes and preferences can be realized.

[0647] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0648] Step 1:

[0649] The user accesses the new registration page. The user enters personal information such as name, email address, and password. This input data is acquired by the terminal and sent to the server. The server stores the received information in a database. If the storage is successful, the server generates a registration success message and sends it to the terminal. The terminal displays this message to the user.

[0650] Input: Personal information such as name, email address, and password

[0651] Output: Registration successful message

[0652] Step 2:

[0653] The designer accesses the work submission page and enters metadata such as the work's image file, title, description, and tags. The device temporarily saves this information and checks its format and content. After format and content checks are complete, the device sends the information to the server. The server saves the received information in a database. If the save is successful, the server generates a save success message and sends it to the device. The device displays this message to the designer.

[0654] Input: Image file, metadata such as title, description, tags etc.

[0655] Output: Listing successful message

[0656] Step 3:

[0657] The user accesses the search screen and enters a search query. The device sends this search query to the server, which searches and extracts relevant design works from the database. The server then uses a generative AI model to analyze the user's past search history, purchase history, and browsing history to generate suggestions based on the user's tastes and preferences. The generated search results and suggestions are sent from the server to the device, which then displays them to the user.

[0658] Input: Search queries, user's past search history, purchase history, browsing history

[0659] Output: Search results and proposed design work

[0660] Step 4:

[0661] When a user wants to purchase a specific design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, who can then choose to approve or reject it. The designer's response is sent to the server, which then notifies the user accordingly. If the request is approved, the user can proceed with further negotiations and the purchase process.

[0662] Input: Purchase request information (user information, work information)

[0663] Output: Notification of purchase request outcome (approval or rejection)

[0664] The combination of specific processes at each step allows for smooth communication between the user and the designer, and the use of generative AI models allows for highly accurate suggestions based on the user's preferences.

[0665] (Application example 1)

[0666] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0667] In previous user-designer matching systems, users had limited access to detailed information and purchasing options for specific designs in physical stores, making efficient matching difficult. Furthermore, optimal suggestions based on a user's past purchase history were often not effectively provided. This made it difficult for users to find designs that matched their tastes, and prevented designers from making the most of opportunities to offer their work to the right users.

[0668] 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.

[0669] In this invention, the server includes: means for a user to register personal information through various input forms; means for transmitting the registered information to the server and saving it in a database; means for verifying registered user information and performing authentication; means for a designer to upload a design work and input metadata (title, description, tags, etc.) related to the work; means for transmitting the design work and its metadata to the server and saving it in the database; means for a user to input a search query and send it to the server; means for the server to search for related designs from the database and perform AI analysis to generate suggestions based on the user's tastes and preferences; means for the user to display the search results and suggested design works to the user; means for the user to issue a purchase request and notify the designer of the request; means for the user to read a two-dimensional code related to a target item; and means for displaying metadata and purchase options for the target item based on the read two-dimensional code. This allows users to intuitively and efficiently obtain detailed information about design works and submit purchase requests in physical stores, and also enables AI to suggest optimal design works based on past history.

[0670] "User" means any individual or organization that accesses the System to search for and request the purchase of Design Works.

[0671] "Designer" means an individual or organization that uploads and provides design work to the system.

[0672] "Personal information" refers to information such as name, email address, and password that users or designers register through various input forms.

[0673] "Metadata" refers to supplemental information, such as titles, descriptions, and tags, associated with a design work that specifically describes the characteristics of the work.

[0674] A "two-dimensional code" is a code pattern similar to a QR code that stores information and allows quick data access by reading it.

[0675] "Purchase Request" means a request made by a User to purchase a particular Design Work, which is communicated to a Designer.

[0676] A "database" is a storage area within a system that systematically stores information about users and designers, design works, and their metadata, and enables searching and retrieval.

[0677] A "server" is a computer device that receives and processes information sent by users and designers, and provides various functions in cooperation with a database.

[0678] "AI analysis" is the process of using artificial intelligence technology to analyze a user's past search history, purchase history, and browsing history, and generate design suggestions based on the user's preferences.

[0679] A "search query" is a keyword or phrase entered by a user to search for design work.

[0680] This invention is a system for efficiently matching users and designers, and is intended for use in brick-and-mortar stores. The system is composed of multiple hardware and software components.

[0681] 1. User Registration and Authentication:

[0682] Users access the system and enter personal information such as their name, email address, and password through various input forms. This information is sent from the terminal to the server, which stores the received information in a database. The registered user information is verified and authentication is performed. Through this procedure, the user gains access to the system.

[0683] Hardware used: User device (smartphone or tablet)

[0684] Software used: Web browser, Flask (Python web framework)

[0685] 2. Upload your design:

[0686] Designers upload their design work to the system and enter metadata about the work (title, description, tags, etc.). This information is temporarily stored on the device and sent to the server after format and content checks. The server stores the received information in a database, and the designer is notified of a successful upload.

[0687] Hardware used: Designer's device (PC or tablet)

[0688] Software used: Web browser, Flask, SQLite3

[0689] 3. QR Code Scan:

[0690] Users scan QR codes associated with design pieces displayed in physical stores with their smartphones. The scanned QR code is sent to a server to display the item's metadata and purchasing options. The server retrieves the corresponding information from a database and sends it back to the user's device, where the user can view detailed information about the piece.

[0691] Hardware used: User device (smartphone)

[0692] Software used: QR code reader, Flask, SQLite3

[0693] 4. AI Recommendations:

[0694] The server collects the user's past search history, purchase history, and browsing history and performs AI analysis. An AI model (e.g., RandomForestClassifier) ​​uses this data to identify the user's preferences and generate optimal design proposals. These recommendations are sent to the user's device and displayed to the user.

[0695] Hardware used: Server

[0696] Software used: scikit-learn (Python machine learning library), Flask, SQLite3

[0697] Examples:

[0698] When a user searches for "modern design furniture" in a physical store, the server searches the database for related design works and uses AI analysis to make optimal suggestions based on past history. Multiple recommended design works are displayed on the user's smartphone, and they can submit a purchase request from the detail page of the work they like.

[0699] Example prompt sentence:

[0700] User ID: 12345

[0701] Previous browsing history: ["modern design", "simple furniture", "Scandinavian style"]

[0702] Purchase history: ["Simple chair", "Scandinavian-style table"]

[0703] Please suggest designs based on this history.

[0704] This invention allows users to intuitively and efficiently obtain detailed information about design items and submit purchase requests in a physical store, while also enabling AI to suggest optimal design items based on past history.

[0705] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0706] Step 1:

[0707] The user uses a device to enter personal information (such as name, email address, and password) through various input forms. The entered personal information is sent from the device to the server. The server stores the received information in a database. At this stage, the entered information is recorded in the database as is (data storage).

[0708] Input: Personal information (name, email address, password)

[0709] Output: User information stored in the database

[0710] Step 2:

[0711] The server compares the received personal information with the database and authenticates the user. If the comparison is correct, it sends a message to the device indicating successful registration. During this process, the user is authenticated by comparing the information with the information in the database (data comparison and authentication).

[0712] Input: User information stored in the database

[0713] Output: Registration successful message

[0714] Step 3:

[0715] Designers use their devices to upload their design work to the system. They enter metadata such as the work's image file, title, description, and tags, and the uploaded information is temporarily stored on the device. It is then checked for format and content before being sent to the server. The server stores the received information in a database and displays a message to the designer indicating that the upload was successful. This is where metadata is entered and saved (data entry, checking, and saving).

[0716] Input: Image file of design work, metadata (title, description, tags, etc.)

[0717] Output: Design information saved in the database, upload success message

[0718] Step 4:

[0719] A user scans a QR code with their smartphone in a physical store. The data from the scanned QR code is sent from the device to a server, which retrieves the metadata and purchase options for the item from a database. The retrieved information is sent back to the device and displayed to the user. In this step, the QR code is scanned, the database is searched, and the information is retrieved and displayed (data retrieval and display).

[0720] Input: QR code data

[0721] Output: Metadata and purchase options for the item

[0722] Step 5:

[0723] The user enters a search query and sends it from their device to the server. The server searches for relevant designs in the database and performs AI analysis to generate recommendations based on the user's preferences. The generated recommendations are sent to the device and displayed to the user. In this step, analysis and recommendation generation are performed using an AI model (data analysis and recommendations).

[0724] Input: Search query

[0725] Output: Search results and recommendations

[0726] Step 6:

[0727] When a user wants to purchase a particular design work, they press the "Purchase Request" button on the details page. The terminal sends the purchase request information (user information, work information) to the server. The server notifies the designer of the request, and the designer responds with an interface that allows the user to choose whether to accept or reject. When the server receives the response from the designer, it notifies the user of the result. In this step, the purchase request is issued, notified, and responded to and notified (request generation and processing).

[0728] Input: Purchase request information (user information, work information)

[0729] Output: Designer's response results

[0730] Step 7:

[0731] The server collects the user's past search history, purchase history, and browsing history, and performs AI analysis based on this. An AI model (e.g., RandomForestClassifier) ​​uses this data to identify the user's tastes and preferences and recommend the most suitable design pieces. This process involves analysis and recommendation generation using machine learning models.

[0732] Input: Past search history, purchase history, browsing history

[0733] Output: Proposal of optimal design work

[0734] For example, here is a prompt example for a user searching for "modern furniture design":

[0735] Example prompt sentence:

[0736] User ID: 12345

[0737] Previous browsing history: ["modern design", "simple furniture", "Scandinavian style"]

[0738] Purchase history: ["Simple chair", "Scandinavian-style table"]

[0739] Please suggest designs based on this history.

[0740] Through these steps, users can efficiently obtain detailed information about design works and submit purchase requests, while AI can suggest the most suitable design works based on past history.

[0741] 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.

[0742] The present invention is a matching system for users and designers that combines an emotion engine, and is implemented in the following steps.

[0743] First, the user accesses the system and enters personal information such as name, email address, and password on the new registration page. The terminal sends this information to the server, which stores the received information in a database. If registration is successful, the terminal displays a registration success message to the user.

[0744] Next, the designer uploads the image file, title, description, tags, and other metadata of the work to be exhibited. The device temporarily saves this information, checks the format and content, and then sends it to the server. The server saves the received information in a database and returns a message to the device indicating that the save was successful, displaying a message to the designer indicating that the exhibit was successful.

[0745] When a user searches for a design work, they access the search screen and enter a search query. The device sends the entered search query to the server, which then searches for and extracts relevant design works from a database. The server then analyzes the user's past search history, purchase history, and browsing history and performs an AI analysis. An emotion engine also obtains emotional data from the user's reactions and facial expressions and sends that data to the server. The server combines this data to generate design work suggestions based on the user's tastes and preferences, and displays the search results and suggested design works to the user.

[0746] When a user wants to purchase a specific design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, who responds with an interface that allows the user to choose whether to approve or reject the request. When the server receives a response from the designer, it notifies the user of the result. If approval is granted, further negotiations and the purchase process can proceed.

[0747] As a specific example, when a user searches for "modern designer house," the server searches the database for related design works, combines AI analysis with data obtained from the emotion engine, and makes optimal suggestions based on the user's past history and reactions. For example, if the emotion engine recognizes an "interest" in a design work that the user is looking at with interest, it will recommend designs similar to that work. Multiple design works are displayed to the user as search results. If the user likes one of them and submits a purchase request, the designer is notified, and the deal is concluded after the designer's approval.

[0748] This system allows users to intuitively and efficiently find their ideal design work, and gives designers the opportunity to deliver their work to the right users. By combining it with an emotion engine, personalized suggestions based on user emotions can be made, resulting in even higher satisfaction.

[0749] The processing flow will be explained below.

[0750] User Registration and Login

[0751] User registration process

[0752] Step 1:

[0753] The user accesses the registration screen and enters personal information such as name, email address, and password.

[0754] Step 2:

[0755] The terminal checks the information entered to see if there are any omissions or errors.

[0756] Step 3:

[0757] The device sends the verified information to the server.

[0758] Step 4:

[0759] The server receives the personal information sent and stores it in a database.

[0760] Step 5:

[0761] The server sends a save success message to the terminal.

[0762] Step 6:

[0763] The device displays a registration success message to the user.

[0764] Login process

[0765] Step 1:

[0766] The user accesses the login screen and enters their email address and password.

[0767] Step 2:

[0768] The device sends the entered email address and password to the server.

[0769] Step 3:

[0770] The server checks the user information against the information stored in its database.

[0771] Step 4:

[0772] The server sends the login success or failure status to the terminal.

[0773] Step 5:

[0774] The terminal displays a login success or login failure message to the user.

[0775] Submission of design works

[0776] Step 1:

[0777] The user (designer) accesses the work submission screen and enters metadata such as the work's image file, title, description, and tags.

[0778] Step 2:

[0779] The device temporarily stores the entered information and checks the file format and content.

[0780] Step 3:

[0781] The device sends the verified information to the server.

[0782] Step 4:

[0783] The server receives the transmitted information and stores it in a database.

[0784] Step 5:

[0785] The server sends a save success message to the terminal.

[0786] Step 6:

[0787] The device will display a listing success message to the designer.

[0788] Design search and suggestions

[0789] Search processing

[0790] Step 1:

[0791] The user accesses the search screen and enters a search query (keywords or category).

[0792] Step 2:

[0793] The terminal transmits the entered search query to the server.

[0794] Step 3:

[0795] The server searches the database for relevant design work and filters the results.

[0796] Step 4:

[0797] The server sends the filtered search results to the device.

[0798] Step 5:

[0799] The device displays the search results to the user.

[0800] Proposal Processing

[0801] Step 1:

[0802] The server retrieves the user's past search history, purchase history, and browsing history from a database.

[0803] Step 2:

[0804] The server analyzes this data using AI to identify user preferences.

[0805] Step 3:

[0806] The server searches the database for design works that may suit the user and generates a list of recommended works.

[0807] Step 4:

[0808] The server sends a list of recommended works to the terminal.

[0809] Step 5:

[0810] The device displays recommended works to the user.

[0811] Emotion recognition and suggestions using an emotion engine

[0812] Emotion Recognition Processing

[0813] Step 1:

[0814] While users search and browse design works, the emotion engine uses cameras and sensors to detect the user's facial expressions and reactions.

[0815] Step 2:

[0816] The device transmits the detected emotion data to the server.

[0817] Step 3:

[0818] The server uses AI to analyze the emotional data received and identify the user's current emotional state.

[0819] Emotion-based suggestion generation

[0820] Step 1:

[0821] The server combines the user's preference trend data and emotional data previously acquired and re-searches for related design works from the database.

[0822] Step 2:

[0823] The server generates a list of recommended works based on the emotions.

[0824] Step 3:

[0825] The server sends a list of recommended works to the terminal.

[0826] Step 4:

[0827] The device displays emotionally-based recommendations to the user.

[0828] Purchases and negotiations

[0829] Purchase Request Processing

[0830] Step 1:

[0831] The user accesses the details page of the design work they wish to purchase and clicks the "Purchase Request" button.

[0832] Step 2:

[0833] The device sends the purchase request information (user information, work information) to the server.

[0834] Step 3:

[0835] The server notifies the designer of the received request and saves the request in the database.

[0836] Step 4:

[0837] The server provides an interface for the designer to approve or deny the request.

[0838] Step 5:

[0839] The designer approves or denies the request and sends the response to the server.

[0840] Step 6:

[0841] The server receives the response from the designer and notifies the user of the result.

[0842] Step 7:

[0843] The device displays the results of the request to the user.

[0844] Example 2

[0845] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0846] Conventional user-designer matching systems lacked personalized suggestions based on the user's preferences and emotions. This made it difficult for users to quickly find designs that matched their tastes and emotions, resulting in low satisfaction. Furthermore, communication between users and designers was sometimes insufficient during the purchasing process, reducing transaction efficiency.

[0847] The specification processing by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring user emotion data and transmitting it to the server, means for the server to analyze the user emotion data and reflect it in the generation of proposed works, and means for collecting the user's past search history, purchase history, browsing history, and emotion data and identifying the user's preference trends using AI based on this. This enables the user to receive proposals for optimal design works based on their emotions and preferences, and furthermore, the purchasing procedure between the user and the designer is carried out smoothly, improving the usability and satisfaction of the entire system.

[0848] "User" means an individual or organization that uses this system to search for and purchase design works.

[0849] "Designers" are individuals or organizations that use this system to upload and sell their design works.

[0850] "Emotional data" refers to information about emotions obtained from a user's reactions, facial expressions, voice, etc.

[0851] A "server" is a computer system responsible for receiving and processing information sent by users and designers.

[0852] A "database" is a system installed on a server for efficiently managing and searching information.

[0853] A "search query" is a keyword or phrase that a user enters when searching for design work.

[0854] "Metadata" is additional information about a design work, including title, description, tags, etc.

[0855] A "generative AI model" is an artificial intelligence model used to analyze a user's habits and preferences and suggest optimal design pieces.

[0856] "Purchase Request" means a request submitted by a User wishing to purchase a particular Design Product.

[0857] "Proposed works" are design works that the server recommends based on the user's history and emotional data.

[0858] "Upload" refers to the data transmission operation that a designer performs to register his or her design work in the system.

[0859] "Authentication" is the process of verifying the legitimacy of users and designers when they access a system.

[0860] "Viewing history" refers to historical information about design works and pages that a user has previously viewed on the system.

[0861] The present invention is a matching system for users and designers that combines an emotion engine. The specific configuration and processing of this system will be described in detail below.

[0862] First, a user accesses the system and enters personal information such as their name, email address, and password on the new registration page. This is done using a device (such as the user's PC or smartphone), and the entered information is sent to the server via the HTTP protocol. The server then stores the received information in a database (e.g., MySQL). This ensures that the user's personal information is managed securely.

[0863] Next, when a designer uploads their design work to the system, they enter the image file and its metadata (title, description, tags, etc.). This information is temporarily stored on the device and checked for format and content. It is then sent to the server, where the image file is stored in file storage (e.g., AWS S3) and the metadata is stored in a database.

[0864] When a user searches for a design work, they access the search screen and enter a search query. The device sends this search query to the server, which then searches and extracts relevant design works from the database. The server then collects the user's past search history, purchase history, and browsing history and performs AI analysis. For example, it uses machine learning models such as TensorFlow and PyTorch to identify the user's preferences.

[0865] The emotion engine captures the user's reactions and facial expressions through a camera and microphone, and sends the generated emotion data from the device to a server. The server combines this emotion data with past history data to generate optimal suggestions. This allows users to receive personalized suggestions based on their emotions and preferences.

[0866] When a user wants to purchase a specific design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, who can then choose to approve or reject it. When the server receives a response from the designer, it notifies the user of the result. If approved, further negotiations and the purchase process can proceed.

[0867] As a concrete example, consider a user searching for "modern designer house." The server processes this search query and searches the database for related design works. By combining data from AI analysis and an emotion engine, the server makes optimal suggestions based on the user's past history and reactions. For example, if a user expresses an "interest" in a particular design, similar designs will be suggested.

[0868] Prompt Sentence Examples

[0869] 1. Prompt to display recommended design works when searching for "modern designer homes":

[0870] A user is searching for "modern design pieces." Please recommend the best design pieces based on the data below.

[0871] Search Query: modern designer house

[0872] User's past search history: [e.g. "contemporary design", "simple modern"]

[0873] User purchase history: [e.g., "Scandinavian interior design," "Minimalist art"]

[0874] User sentiment data: [e.g., interest level for search query: high]

[0875] 2. Prompt for generating a design purchase request:

[0876] A user wants to purchase a specific design piece. Please generate a purchase request using the following user and piece information:

[0877] User information: Taro, Email address: taro@example.com

[0878] Work information: Title: Modern Designer's House, Designer: Hanako

[0879] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0880] System processing flow

[0881] Step 1: Sign up

[0882] input:

[0883] A user accesses the new registration page and enters personal information such as name, email address, and password.

[0884] Specific behavior:

[0885] The device (user's PC or smartphone) temporarily stores this input data and checks the format of the input.

[0886] Data processing and calculation:

[0887] The terminal performs format checks on the input data (e.g., checking the format of the email address, checking the strength of the password).

[0888] output:

[0889] Based on the check results, if appropriate, the data is sent to the server, otherwise an error message is displayed to the user.

[0890] Step 2: Send and store user information

[0891] input:

[0892] User personal information sent from the device (name, email address, password).

[0893] Specific behavior:

[0894] The device sends information to the server via an HTTP request, and the server validates the received data.

[0895] Data processing and calculation:

[0896] The server validates the incoming data (e.g. checks for duplicate email addresses) and converts it into a secure data format.

[0897] output:

[0898] If validation is successful, the server saves the information in the database (MySQL) and returns a registration success message to the terminal.

[0899] Step 3: Upload your design

[0900] input:

[0901] Metadata entered by the designer, such as image files, title, description, and tags for the work.

[0902] Specific behavior:

[0903] The device temporarily stores this information and checks its format and content. Image file format checks (e.g., JPEG, PNG) are also performed.

[0904] Data processing and calculation:

[0905] The device checks the consistency of the metadata and image file, and performs image processing such as resizing and compression as necessary.

[0906] output:

[0907] If the check is successful, the terminal transmits the information to the server.

[0908] Step 4: Send and save your design to the server

[0909] input:

[0910] Image files and metadata of design work sent from your device.

[0911] Specific behavior:

[0912] The server receives this data, uploads the image files to file storage (AWS S3), and stores the metadata in a database.

[0913] Data processing and calculation:

[0914] The server validates the metadata, generates a URL for saving to file storage, and saves it in the database.

[0915] output:

[0916] If the saving is successful, the server returns a message to the terminal indicating that the listing was successful and notifies the designer.

[0917] Step 5: Find design ideas

[0918] input:

[0919] The search query entered by the user on the search screen (e.g., "modern designer home").

[0920] Specific behavior:

[0921] The terminal transmits the input search query to the server.

[0922] Data processing and calculation:

[0923] Based on the received query, the server generates an SQL query and extracts relevant design works from the database.

[0924] output:

[0925] Based on the search results and past search, purchase, and browsing history, the server generates a JSON response and sends it back to the device, which then displays it to the user.

[0926] Step 6: Generate a proposal

[0927] input:

[0928] Search results and your past search history, purchase history, browsing history, and sentiment data.

[0929] Specific behavior:

[0930] The server inputs this data into an AI model (TensorFlow or PyTorch) for analysis. It also obtains reaction data from the emotion engine and reflects it in the analysis.

[0931] Data processing and calculation:

[0932] The AI ​​model identifies user preferences and generates optimal product suggestions, while also analyzing emotional data to calculate the user's interest level.

[0933] output:

[0934] The server generates the proposed results and sends them to the device, which then displays them to the user.

[0935] Step 7: Submitting a Purchase Request

[0936] input:

[0937] Request information (user information, work information) sent by the user by pressing the "Purchase Request" button.

[0938] Specific behavior:

[0939] The terminal transmits this information to the server.

[0940] Data processing and calculation:

[0941] The server validates the request information and forwards it to the designer with notification.

[0942] output:

[0943] The server notifies the designer of the request and waits for the designer's response.

[0944] Step 8: Designer response and user notification

[0945] input:

[0946] The designer has the choice to approve or reject the request.

[0947] Specific behavior:

[0948] The designer's device sends the selection results to the server, which receives them and takes appropriate action.

[0949] Data processing and calculation:

[0950] The server generates a result notification for the user based on the designer's response.

[0951] output:

[0952] The server notifies the user of the response result and, if approved, assists with further purchase procedures.

[0953] (Application example 2)

[0954] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0955] Conventional user-designer matching systems lack the ability to provide personalized suggestions that fully reflect a user's individual tastes and emotions. As a result, users spend a long time finding their ideal design, and designers have limited opportunities to offer their work to the right users. Furthermore, especially when providing immersive experiences such as virtual stores, a system that reflects user emotions in real time and makes design discovery easier and seamless is needed.

[0956] 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.

[0957] In this invention, the server includes: means for users to register personal information through various input forms; means for transmitting the registered information to the server and saving it in a database; means for verifying registered user information and performing authentication; means for designers to upload design works and input metadata about the works (e.g., title, description, tags, etc.); means for transmitting the design works and their metadata to the server and saving them in the database; means for users to input search queries and send them to the server; means for the server to search for related designs from the database and perform AI analysis to generate proposals based on the user's tastes and preferences; means for displaying the search results and proposed design works to the user; means for acquiring emotional data from the user's reactions and facial expressions using an emotion analysis device; means for transmitting the acquired emotional data to the server and combining it with AI analysis to provide personalized design proposals to the user; and means for users to issue purchase requests and notify designers of the requests. This enables personalized proposals in real time based on the user's emotions, making it easier for users to efficiently find their ideal designs and increasing designers' opportunities to provide their works to appropriate users.

[0958] "User" means an individual or corporation that uses the System to search for and purchase design works.

[0959] "Designer" means an individual or legal entity responsible for uploading design works to the system.

[0960] "Server" refers to a computer system that receives data sent by users and designers, and stores and manages the data in a database.

[0961] A "database" is a system connected to a server for systematically storing and managing user information and metadata of design works.

[0962] "Metadata" refers to additional information such as title, description, and tags associated with a design work.

[0963] An "emotion analysis device" is a device that captures and analyzes emotional data from a user's reactions and facial expressions.

[0964] "Emotion data" is user emotion information acquired by the emotion analysis device.

[0965] "AI analysis" is the process of using artificial intelligence technology to analyze users' tastes, preferences, and emotional data and generate suggestions.

[0966] "Personalized proposals" are proposals for customized design works based on the user's individual tastes, preferences, and emotional data.

[0967] A "Purchase Request" is a request by a User to express their intent to purchase a particular Design Work.

[0968] A "notification" is a message that conveys information from the server to the designer or user.

[0969] This system is a comprehensive platform that allows users to efficiently search and purchase design works and allows designers to deliver their works to the right customers. Specific embodiments are described below.

[0970] User Registration

[0971] First, the user accesses the system and enters personal information such as name, email address, and password on the new registration page. The terminal sends this information to the server, which stores the received information in a database. If registration is successful, the terminal displays a registration success message to the user.

[0972] Upload your design

[0973] Next, the designer uploads their design. The designer enters metadata such as the image file, title, description, and tags of the work and uploads it. The device temporarily saves this information, checks the format and content, and then sends it to the server. The server saves the received information in a database and returns a message to the device indicating that the save was successful, displaying a message to the designer indicating that the listing was successful.

[0974] Sentiment analysis and AI suggestions

[0975] When a user searches for a design work, they access the search screen and enter a search query. The device sends the entered search query to the server, which then searches for and extracts relevant design works from a database. The server then collects the user's past search history, purchase history, and browsing history and performs AI analysis. An emotion analyzer (such as OpenCV or Face API) obtains emotional data from the user's reactions and facial expressions and sends that data to the server. The server combines this data and uses a deep learning framework (such as TensorFlow or PyTorch) to generate optimal suggestions based on the user's preferences and tastes, which are then displayed to the user along with the search results.

[0976] Purchase Process

[0977] When a user wants to purchase a specific design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, and the designer responds in real time using Firebase Cloud Messaging. When the server receives a response from the designer (approval or rejection), it notifies the user of the result.

[0978] Specific examples

[0979] As a concrete example, when a user searches for "modern designer house," the server searches the database for related design works and uses AI analysis and an emotion engine to make optimal suggestions based on the user's past history and reactions. For example, if the emotion engine recognizes an "interest" in a design work that the user is looking at with interest, it will recommend designs similar to that work. Multiple design works are displayed to the user as search results. If the user likes one of them and submits a purchase request, the designer is notified, and the deal is concluded after the designer's approval.

[0980] Prompt Sentence Examples

[0981] "I'm looking for a modern designer home. I'm looking for a design similar to the urban interiors I've seen in the past. Also, please use sentiment analysis to suggest which design would be best for me."

[0982] The above is a concrete example of how the present invention can be implemented. Users can efficiently find their ideal design work through real-time suggestions based on their emotions, and designers can have the opportunity to provide their work to the right users.

[0983] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0984] Step 1:

[0985] The user enters personal information (name, email address, password, etc.) on the new registration page.

[0986] Input: The user enters personal information.

[0987] Data processing: The terminal sends these data to the server.

[0988] Output: The server stores the received information in a database and displays a registration success message on the terminal.

[0989] Step 2:

[0990] Designers upload their design work and enter the work's metadata (image file, title, description, tags, etc.).

[0991] Input: Designers input design work and metadata.

[0992] Data processing: The device temporarily stores this data and checks its format and content.

[0993] Output: Sent to server and saved in database. A message of successful saving is displayed in the designer.

[0994] Step 3:

[0995] A user enters a search query to search for design work.

[0996] Input: The user types a search query.

[0997] Data processing: The terminal sends the entered search query to the server, which then searches and extracts relevant design works from the database.

[0998] Output: The relevant design work is displayed to the user.

[0999] Step 4:

[1000] Using AI and sentiment analysis, suggestions are generated based on the user's tastes and preferences.

[1001] Input: Past search history, purchase history, browsing history, and emotional data obtained from reactions and facial expressions.

[1002] Data processing: The server analyzes the data using deep learning frameworks (TensorFlow, PyTorch) and generates personalized suggestions.

[1003] Output: A list of proposed design works is displayed to the user.

[1004] Step 5:

[1005] The user places a purchase request and notifies the designer of the request.

[1006] Input: User information, work information.

[1007] Data processing: The terminal sends the purchase request information to the server.

[1008] Output: The server notifies the designer of the request.

[1009] Step 6:

[1010] The designer responds to the purchase request.

[1011] Input: Approval or rejection response from the designer.

[1012] Data processing: The server receives the designer's response and notifies the user.

[1013] Output: The user is shown the approval or rejection result.

[1014] Step 7:

[1015] If the deal is successful, the user and designer will proceed with detailed negotiations.

[1016] Input: Opportunity details.

[1017] Data processing: Transaction-related information is stored on the server and updated and managed as necessary.

[1018] Output: A notification of the transaction completion is sent to both parties.

[1019] 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.

[1020] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1021] 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.

[1022] [Third embodiment]

[1023] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1024] 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.

[1025] 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).

[1026] 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.

[1027] 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.

[1028] 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).

[1029] 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.

[1030] 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.

[1031] 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.

[1032] 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.

[1033] 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.

[1034] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1035] The present invention is a system for efficiently matching users and designers, and is implemented in the following manner.

[1036] First, the user accesses the system and enters personal information such as name, email address, and password on the new registration page. The terminal sends this information to the server, which stores the received information in a database. If registration is successful, the terminal displays a registration success message to the user.

[1037] Next, the designer uploads the image file, title, description, tags, and other metadata of the work to be exhibited. The device temporarily saves this information, checks the format and content, and then sends it to the server. The server saves the received information in a database and returns a message to the device indicating that the save was successful, displaying a message to the designer indicating that the exhibit was successful.

[1038] When a user searches for a design work, they access the search screen and enter a search query. The device sends the entered search query to the server, which then searches and extracts relevant design works from the database. The server then uses AI to analyze the user's past search history, purchase history, and browsing history to generate design work suggestions based on the user's preferences. The search results and suggested design works are sent to the device and displayed to the user.

[1039] When a user wants to purchase a specific design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, who responds with an interface that allows the user to choose whether to approve or reject the request. When the server receives a response from the designer, it notifies the user of the result. If approval is granted, further negotiations and the purchase process can proceed.

[1040] For example, when a user searches for "modern designer house," the server searches the database for related design works and uses AI analysis to make optimal suggestions based on past history. Multiple design works are displayed to the user as search results. If the user likes one of them and submits a purchase request, the designer is notified, and the deal is concluded after the designer's approval.

[1041] This system allows users to efficiently find their ideal design work and gives designers the opportunity to offer their work to the right users.

[1042] The processing flow will be explained below.

[1043] User Registration and Login

[1044] User registration process

[1045] Step 1:

[1046] The user accesses the registration screen and enters personal information such as name, email address, and password.

[1047] Step 2:

[1048] The terminal checks the information entered to see if there are any omissions or errors.

[1049] Step 3:

[1050] The device sends the verified information to the server.

[1051] Step 4:

[1052] The server receives the personal information sent and stores it in a database.

[1053] Step 5:

[1054] The server sends a save success message to the terminal.

[1055] Step 6:

[1056] The device displays a registration success message to the user.

[1057] Login process

[1058] Step 1:

[1059] The user accesses the login screen and enters their email address and password.

[1060] Step 2:

[1061] The device sends the entered email address and password to the server.

[1062] Step 3:

[1063] The server checks the user information against the information stored in its database.

[1064] Step 4:

[1065] The server sends the login success or failure status to the terminal.

[1066] Step 5:

[1067] The terminal displays a login success or login failure message to the user.

[1068] Submission of design works

[1069] Step 1:

[1070] The user (designer) accesses the work submission screen and enters metadata such as the work's image file, title, description, and tags.

[1071] Step 2:

[1072] The device temporarily stores the entered information and checks the file format and content.

[1073] Step 3:

[1074] The device sends the verified information to the server.

[1075] Step 4:

[1076] The server receives the transmitted information and stores it in a database.

[1077] Step 5:

[1078] The server sends a save success message to the terminal.

[1079] Step 6:

[1080] The device will display a listing success message to the designer.

[1081] Design search and suggestions

[1082] Search processing

[1083] Step 1:

[1084] The user accesses the search screen and enters a search query (keywords or category).

[1085] Step 2:

[1086] The terminal transmits the entered search query to the server.

[1087] Step 3:

[1088] The server searches the database for relevant designs and filters the results.

[1089] Step 4:

[1090] The server sends the filtered search results to the device.

[1091] Step 5:

[1092] The device displays the search results to the user.

[1093] Proposal Processing

[1094] Step 1:

[1095] The server retrieves the user's past search history, purchase history, and browsing history from a database.

[1096] Step 2:

[1097] The server analyzes this data using AI to identify user preferences.

[1098] Step 3:

[1099] The server searches the database for design works that may suit the user and generates a list of recommended works.

[1100] Step 4:

[1101] The server sends a list of recommended works to the terminal.

[1102] Step 5:

[1103] The device displays recommended works to the user.

[1104] Purchases and negotiations

[1105] Purchase Request Processing

[1106] Step 1:

[1107] The user accesses the details page of the design work they wish to purchase and clicks the "Purchase Request" button.

[1108] Step 2:

[1109] The device sends the purchase request information (user information, work information) to the server.

[1110] Step 3:

[1111] The server notifies the designer of the received request and saves the request in the database.

[1112] Step 4:

[1113] The server provides an interface for the designer to approve or deny the request.

[1114] Step 5:

[1115] The designer approves or denies the request and sends the response to the server.

[1116] Step 6:

[1117] The server receives the response from the designer and notifies the user of the result.

[1118] Step 7:

[1119] The device displays the results of the request to the user.

[1120] Example 1

[1121] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1122] The challenge is to efficiently match users with designers, enabling users to quickly and appropriately find the design works they are looking for, and enabling designers to effectively provide their work to interested users. The current system has difficulty accurately reflecting users' search intent and preferences, resulting in a long wait for users to find the work they are looking for. Designers also face the risk of missing sales opportunities, as they are uncertain whether their work will reach the right target audience.

[1123] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1124] In this invention, the server includes: means for users to register personal information through various input forms; means for transmitting the registered information to the server and saving it in a database; means for verifying registered user information and performing authentication; means for designers to upload design works and input metadata about the works (title, description, tags, etc.); means for transmitting the design works and their metadata to the server and saving them in the database; means for users to input search queries and send them to the server; means for the server to search for related designs from the database and generate suggestions based on the user's tastes and preferences using a generative AI model; means for users to issue purchase requests and notify designers of the requests; and means for receiving purchase approval or rejection from designers and notifying the user of the results. This allows users to efficiently find their ideal design works and gives designers the opportunity to offer their works to appropriate users.

[1125] "User" means any individual or entity that accesses the System to search, browse, and purchase Design Works.

[1126] "Designer" means an individual or entity that creates a design work and uploads it to the System.

[1127] "Server" means the central management system that receives, processes and stores information from Users and Designers.

[1128] "Database" refers to the collection of digital data managed by the server for storing and managing information submitted by Users and Designers.

[1129] "Personal information" refers to information that identifies an individual, such as name, email address, password, etc., that a user or designer registers in the system.

[1130] "Metadata" refers to additional information about a design work, such as title, description, and tags.

[1131] "Generative AI model" refers to an algorithm and the means to implement it that uses artificial intelligence to analyze a user's tastes and preferences and suggest optimal design works.

[1132] "Purchase Request" means a request by a User to indicate their intent to purchase a particular Design Work and notify a Designer of such intent.

[1133] "Authentication" refers to the process of verifying a user's or designer's registration information to ensure that the person has legitimate access rights.

[1134] "Proposal" refers to a design work selected based on the user's tastes and preferences as a result of analysis using a generative AI model.

[1135] "Notification" means a message or alert sent by the Server to provide specific information to a User or Designer.

[1136] The present invention is a system for efficiently matching users and designers, and is implemented using specific hardware and software. The system includes a series of processes for improving the experience for both users and designers. The details are described below.

[1137] First, a user accesses the system and registers. At this time, the user enters personal information such as name, email address, and password. The terminal sends this information to the server, which then stores the received information in a database. If the storage is successful, the server returns a registration success message to the terminal, which then displays this message to the user.

[1138] Next, when a designer wants to exhibit their design, they enter metadata such as the image file, title, description, and tags of the work. The device temporarily stores this information, checks the format and content, and then sends it to the server. The server stores the information in a database and returns a success message to the device, which then displays a successful exhibit message to the designer.

[1139] When a user searches for a design work, they access the search screen and enter a search query. The device sends the entered search query to the server, which then searches and extracts relevant design works from the database. The server then uses a generative AI model (e.g., TensorFlow, PyTorch) to analyze the user's past search history, purchase history, and browsing history to generate design work suggestions based on the user's preferences. The search results and suggested design works are sent to the device, which then displays them to the user.

[1140] When a user wants to purchase a particular design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, who responds with an interface that allows the user to choose whether to approve or reject the request. Once the server receives a response from the designer, it notifies the user of the result. If approved, the user can proceed with detailed negotiations and the purchase process.

[1141] For example, if a user searches for "modern designer house," the server searches the database for related design works and uses a generative AI model to make optimal suggestions based on past history. Multiple design works are displayed to the user as search results, and the user submits a purchase request for the work they like. The designer is notified, and if approved, the deal is concluded.

[1142] Examples of prompts for generative AI models include:

[1143] "Suggest design pieces that might interest you based on your past search and purchase history."

[1144] "Search for design work related to modern designer homes and see the best results."

[1145] This system allows users to efficiently find their ideal design work, and gives designers the opportunity to offer their work to the right users. Furthermore, by using a generative AI model, highly accurate suggestions that match the user's tastes and preferences can be realized.

[1146] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1147] Step 1:

[1148] The user accesses the new registration page. The user enters personal information such as name, email address, and password. This input data is acquired by the terminal and sent to the server. The server stores the received information in a database. If the storage is successful, the server generates a registration success message and sends it to the terminal. The terminal displays this message to the user.

[1149] Input: Personal information such as name, email address, and password

[1150] Output: Registration successful message

[1151] Step 2:

[1152] The designer accesses the work submission page and enters metadata such as the work's image file, title, description, and tags. The device temporarily saves this information and checks its format and content. After format and content checks are complete, the device sends the information to the server. The server saves the received information in a database. If the save is successful, the server generates a save success message and sends it to the device. The device displays this message to the designer.

[1153] Input: Image file, metadata such as title, description, tags etc.

[1154] Output: Listing successful message

[1155] Step 3:

[1156] The user accesses the search screen and enters a search query. The device sends this search query to the server, which searches and extracts relevant design works from the database. The server then uses a generative AI model to analyze the user's past search history, purchase history, and browsing history to generate suggestions based on the user's tastes and preferences. The generated search results and suggestions are sent from the server to the device, which then displays them to the user.

[1157] Input: Search queries, user's past search history, purchase history, browsing history

[1158] Output: Search results and proposed design work

[1159] Step 4:

[1160] When a user wants to purchase a specific design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, who can then choose to approve or reject it. The designer's response is sent to the server, which then notifies the user accordingly. If the request is approved, the user can proceed with further negotiations and the purchase process.

[1161] Input: Purchase request information (user information, work information)

[1162] Output: Notification of purchase request outcome (approval or rejection)

[1163] The combination of specific processes at each step allows for smooth communication between the user and the designer, and the use of generative AI models allows for highly accurate suggestions based on the user's preferences.

[1164] (Application example 1)

[1165] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1166] In previous user-designer matching systems, users had limited access to detailed information and purchasing options for specific designs in physical stores, making efficient matching difficult. Furthermore, optimal suggestions based on a user's past purchase history were often not effectively provided. This made it difficult for users to find designs that matched their tastes, and prevented designers from making the most of opportunities to offer their work to the right users.

[1167] 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.

[1168] In this invention, the server includes: means for a user to register personal information through various input forms; means for transmitting the registered information to the server and saving it in a database; means for verifying registered user information and performing authentication; means for a designer to upload a design work and input metadata (title, description, tags, etc.) related to the work; means for transmitting the design work and its metadata to the server and saving it in the database; means for a user to input a search query and send it to the server; means for the server to search for related designs from the database and perform AI analysis to generate suggestions based on the user's tastes and preferences; means for the user to display the search results and suggested design works to the user; means for the user to issue a purchase request and notify the designer of the request; means for the user to read a two-dimensional code related to a target item; and means for displaying metadata and purchase options for the target item based on the read two-dimensional code. This allows users to intuitively and efficiently obtain detailed information about design works and submit purchase requests in physical stores, and also enables AI to suggest optimal design works based on past history.

[1169] "User" means any individual or organization that accesses the System to search for and request the purchase of Design Works.

[1170] "Designer" means an individual or organization that uploads and provides design work to the system.

[1171] "Personal information" refers to information such as name, email address, and password that users or designers register through various input forms.

[1172] "Metadata" refers to supplemental information, such as titles, descriptions, and tags, associated with a design work that specifically describes the characteristics of the work.

[1173] A "two-dimensional code" is a code pattern similar to a QR code that stores information and allows quick data access by reading it.

[1174] "Purchase Request" means a request made by a User to purchase a particular Design Work, which is communicated to a Designer.

[1175] A "database" is a storage area within a system that systematically stores information about users and designers, design works, and their metadata, and enables searching and retrieval.

[1176] A "server" is a computer device that receives and processes information sent by users and designers, and provides various functions in cooperation with a database.

[1177] "AI analysis" is the process of using artificial intelligence technology to analyze a user's past search history, purchase history, and browsing history, and generate design suggestions based on the user's preferences.

[1178] A "search query" is a keyword or phrase entered by a user to search for design work.

[1179] This invention is a system for efficiently matching users and designers, and is intended for use in brick-and-mortar stores. The system is composed of multiple hardware and software components.

[1180] 1. User Registration and Authentication:

[1181] Users access the system and enter personal information such as their name, email address, and password through various input forms. This information is sent from the terminal to the server, which stores the received information in a database. The registered user information is verified and authentication is performed. Through this procedure, the user gains access to the system.

[1182] Hardware used: User device (smartphone or tablet)

[1183] Software used: Web browser, Flask (Python web framework)

[1184] 2. Upload your design:

[1185] Designers upload their design work to the system and enter metadata about the work (title, description, tags, etc.). This information is temporarily stored on the device and sent to the server after format and content checks. The server stores the received information in a database, and the designer is notified of a successful upload.

[1186] Hardware used: Designer's device (PC or tablet)

[1187] Software used: Web browser, Flask, SQLite3

[1188] 3. QR Code Scan:

[1189] Users scan QR codes associated with design pieces displayed in physical stores with their smartphones. The scanned QR code is sent to a server to display the item's metadata and purchasing options. The server retrieves the corresponding information from a database and sends it back to the user's device, where the user can view detailed information about the piece.

[1190] Hardware used: User device (smartphone)

[1191] Software used: QR code reader, Flask, SQLite3

[1192] 4. AI Recommendations:

[1193] The server collects the user's past search history, purchase history, and browsing history and performs AI analysis. An AI model (e.g., RandomForestClassifier) ​​uses this data to identify the user's preferences and generate optimal design proposals. These recommendations are sent to the user's device and displayed to the user.

[1194] Hardware used: Server

[1195] Software used: scikit-learn (Python machine learning library), Flask, SQLite3

[1196] Examples:

[1197] When a user searches for "modern design furniture" in a physical store, the server searches the database for related design works and uses AI analysis to make optimal suggestions based on past history. Multiple recommended design works are displayed on the user's smartphone, and they can submit a purchase request from the detail page of the work they like.

[1198] Example prompt sentence:

[1199] User ID: 12345

[1200] Previous browsing history: ["modern design", "simple furniture", "Scandinavian style"]

[1201] Purchase history: ["Simple chair", "Scandinavian-style table"]

[1202] Please suggest designs based on this history.

[1203] This invention allows users to intuitively and efficiently obtain detailed information about design items and submit purchase requests in a physical store, while also enabling AI to suggest optimal design items based on past history.

[1204] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1205] Step 1:

[1206] The user uses a device to enter personal information (such as name, email address, and password) through various input forms. The entered personal information is sent from the device to the server. The server stores the received information in a database. At this stage, the entered information is recorded in the database as is (data storage).

[1207] Input: Personal information (name, email address, password)

[1208] Output: User information stored in the database

[1209] Step 2:

[1210] The server compares the received personal information with the database and authenticates the user. If the comparison is correct, it sends a message to the device indicating successful registration. During this process, the user is authenticated by comparing the information with the information in the database (data comparison and authentication).

[1211] Input: User information stored in the database

[1212] Output: Registration successful message

[1213] Step 3:

[1214] Designers use their devices to upload their design work to the system. They enter metadata such as the work's image file, title, description, and tags, and the uploaded information is temporarily stored on the device. It is then checked for format and content before being sent to the server. The server stores the received information in a database and displays a message to the designer indicating that the upload was successful. This is where metadata is entered and saved (data entry, checking, and saving).

[1215] Input: Image file of design work, metadata (title, description, tags, etc.)

[1216] Output: Design information saved in the database, upload success message

[1217] Step 4:

[1218] A user scans a QR code with their smartphone in a physical store. The data from the scanned QR code is sent from the device to a server, which retrieves the metadata and purchase options for the item from a database. The retrieved information is sent back to the device and displayed to the user. In this step, the QR code is scanned, the database is searched, and the information is retrieved and displayed (data retrieval and display).

[1219] Input: QR code data

[1220] Output: Metadata and purchase options for the item

[1221] Step 5:

[1222] The user enters a search query and sends it from their device to the server. The server searches for relevant designs in the database and performs AI analysis to generate recommendations based on the user's preferences. The generated recommendations are sent to the device and displayed to the user. In this step, analysis and recommendation generation are performed using an AI model (data analysis and recommendations).

[1223] Input: Search query

[1224] Output: Search results and recommendations

[1225] Step 6:

[1226] When a user wants to purchase a particular design work, they press the "Purchase Request" button on the details page. The terminal sends the purchase request information (user information, work information) to the server. The server notifies the designer of the request, and the designer responds with an interface that allows the user to choose whether to accept or reject. When the server receives the response from the designer, it notifies the user of the result. In this step, the purchase request is issued, notified, and responded to and notified (request generation and processing).

[1227] Input: Purchase request information (user information, work information)

[1228] Output: Designer's response results

[1229] Step 7:

[1230] The server collects the user's past search history, purchase history, and browsing history, and performs AI analysis based on this. An AI model (e.g., RandomForestClassifier) ​​uses this data to identify the user's tastes and preferences and recommend the most suitable design pieces. This process involves analysis and recommendation generation using machine learning models.

[1231] Input: Past search history, purchase history, browsing history

[1232] Output: Proposal of optimal design work

[1233] For example, here is a prompt example for a user searching for "modern furniture design":

[1234] Example prompt sentence:

[1235] User ID: 12345

[1236] Previous browsing history: ["modern design", "simple furniture", "Scandinavian style"]

[1237] Purchase history: ["Simple chair", "Scandinavian style table"]

[1238] Please suggest designs based on this history.

[1239] Through these steps, users can efficiently obtain detailed information about design works and submit purchase requests, while AI can suggest the most suitable design works based on past history.

[1240] 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.

[1241] The present invention is a matching system for users and designers that combines an emotion engine, and is implemented in the following steps.

[1242] First, the user accesses the system and enters personal information such as name, email address, and password on the new registration page. The terminal sends this information to the server, which stores the received information in a database. If registration is successful, the terminal displays a registration success message to the user.

[1243] Next, the designer uploads the image file, title, description, tags, and other metadata of the work to be exhibited. The device temporarily saves this information, checks the format and content, and then sends it to the server. The server saves the received information in a database and returns a message to the device indicating that the save was successful, displaying a message to the designer indicating that the exhibit was successful.

[1244] When a user searches for a design work, they access the search screen and enter a search query. The device sends the entered search query to the server, which then searches for and extracts relevant design works from a database. The server then analyzes the user's past search history, purchase history, and browsing history and performs an AI analysis. An emotion engine also obtains emotional data from the user's reactions and facial expressions and sends that data to the server. The server combines this data to generate design work suggestions based on the user's tastes and preferences, and displays the search results and suggested design works to the user.

[1245] When a user wants to purchase a specific design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, who responds with an interface that allows the user to choose whether to approve or reject the request. When the server receives a response from the designer, it notifies the user of the result. If approval is granted, further negotiations and the purchase process can proceed.

[1246] As a specific example, when a user searches for "modern designer house," the server searches the database for related design works, combines AI analysis with data obtained from the emotion engine, and makes optimal suggestions based on the user's past history and reactions. For example, if the emotion engine recognizes an "interest" in a design work that the user is looking at with interest, it will recommend designs similar to that work. Multiple design works are displayed to the user as search results. If the user likes one of them and submits a purchase request, the designer is notified, and the deal is concluded after the designer's approval.

[1247] This system allows users to intuitively and efficiently find their ideal design work, and gives designers the opportunity to deliver their work to the right users. By combining it with an emotion engine, personalized suggestions based on user emotions can be made, resulting in even higher satisfaction.

[1248] The processing flow will be explained below.

[1249] User Registration and Login

[1250] User registration process

[1251] Step 1:

[1252] The user accesses the registration screen and enters personal information such as name, email address, and password.

[1253] Step 2:

[1254] The terminal checks the information entered to see if there are any omissions or errors.

[1255] Step 3:

[1256] The device sends the verified information to the server.

[1257] Step 4:

[1258] The server receives the personal information sent and stores it in a database.

[1259] Step 5:

[1260] The server sends a save success message to the terminal.

[1261] Step 6:

[1262] The device displays a registration success message to the user.

[1263] Login process

[1264] Step 1:

[1265] The user accesses the login screen and enters their email address and password.

[1266] Step 2:

[1267] The device sends the entered email address and password to the server.

[1268] Step 3:

[1269] The server checks the user information against the information stored in its database.

[1270] Step 4:

[1271] The server sends the login success or failure status to the terminal.

[1272] Step 5:

[1273] The terminal displays a login success or login failure message to the user.

[1274] Submission of design works

[1275] Step 1:

[1276] The user (designer) accesses the work submission screen and enters metadata such as the work's image file, title, description, and tags.

[1277] Step 2:

[1278] The device temporarily stores the entered information and checks the file format and content.

[1279] Step 3:

[1280] The device sends the verified information to the server.

[1281] Step 4:

[1282] The server receives the transmitted information and stores it in a database.

[1283] Step 5:

[1284] The server sends a save success message to the terminal.

[1285] Step 6:

[1286] The device will display a listing success message to the designer.

[1287] Design search and suggestions

[1288] Search processing

[1289] Step 1:

[1290] The user accesses the search screen and enters a search query (keywords or category).

[1291] Step 2:

[1292] The terminal transmits the entered search query to the server.

[1293] Step 3:

[1294] The server searches the database for relevant design work and filters the results.

[1295] Step 4:

[1296] The server sends the filtered search results to the device.

[1297] Step 5:

[1298] The device displays the search results to the user.

[1299] Proposal Processing

[1300] Step 1:

[1301] The server retrieves the user's past search history, purchase history, and browsing history from a database.

[1302] Step 2:

[1303] The server analyzes this data using AI to identify user preferences.

[1304] Step 3:

[1305] The server searches the database for design works that may suit the user and generates a list of recommended works.

[1306] Step 4:

[1307] The server sends a list of recommended works to the terminal.

[1308] Step 5:

[1309] The device displays recommended works to the user.

[1310] Emotion recognition and suggestions using an emotion engine

[1311] Emotion Recognition Processing

[1312] Step 1:

[1313] While users search and browse design works, the emotion engine uses cameras and sensors to detect the user's facial expressions and reactions.

[1314] Step 2:

[1315] The device transmits the detected emotion data to the server.

[1316] Step 3:

[1317] The server uses AI to analyze the emotional data received and identify the user's current emotional state.

[1318] Emotion-based suggestion generation

[1319] Step 1:

[1320] The server combines the user's preference trend data and emotional data previously acquired and re-searches for related design works from the database.

[1321] Step 2:

[1322] The server generates a list of recommended works based on the emotions.

[1323] Step 3:

[1324] The server sends a list of recommended works to the terminal.

[1325] Step 4:

[1326] The device displays emotionally-based recommendations to the user.

[1327] Purchases and negotiations

[1328] Purchase Request Processing

[1329] Step 1:

[1330] The user accesses the details page of the design work they wish to purchase and clicks the "Purchase Request" button.

[1331] Step 2:

[1332] The device sends the purchase request information (user information, work information) to the server.

[1333] Step 3:

[1334] The server notifies the designer of the received request and saves the request in the database.

[1335] Step 4:

[1336] The server provides an interface for the designer to approve or deny the request.

[1337] Step 5:

[1338] The designer approves or denies the request and sends the response to the server.

[1339] Step 6:

[1340] The server receives the response from the designer and notifies the user of the result.

[1341] Step 7:

[1342] The device displays the results of the request to the user.

[1343] Example 2

[1344] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1345] Conventional user-designer matching systems lacked personalized suggestions based on the user's preferences and emotions. This made it difficult for users to quickly find designs that matched their tastes and emotions, resulting in low satisfaction. Furthermore, communication between users and designers was sometimes insufficient during the purchasing process, reducing transaction efficiency.

[1346] The specification processing by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring user emotion data and transmitting it to the server, means for the server to analyze the user emotion data and reflect it in the generation of proposed works, and means for collecting the user's past search history, purchase history, browsing history, and emotion data and identifying the user's preference trends using AI based on this. This enables the user to receive proposals for optimal design works based on their emotions and preferences, and furthermore, the purchasing procedure between the user and the designer is carried out smoothly, improving the usability and satisfaction of the entire system.

[1347] "User" means an individual or organization that uses this system to search for and purchase design works.

[1348] "Designers" are individuals or organizations that use this system to upload and sell their design works.

[1349] "Emotional data" refers to information about emotions obtained from a user's reactions, facial expressions, voice, etc.

[1350] A "server" is a computer system responsible for receiving and processing information sent by users and designers.

[1351] A "database" is a system installed on a server for efficiently managing and searching information.

[1352] A "search query" is a keyword or phrase that a user enters when searching for design work.

[1353] "Metadata" is additional information about a design work, including title, description, tags, etc.

[1354] A "generative AI model" is an artificial intelligence model used to analyze a user's habits and preferences and suggest optimal design pieces.

[1355] "Purchase Request" means a request submitted by a User wishing to purchase a particular Design Product.

[1356] "Proposed works" are design works that the server recommends based on the user's history and emotional data.

[1357] "Upload" refers to the data transmission operation that a designer performs to register his or her design work in the system.

[1358] "Authentication" is the process of verifying the legitimacy of users and designers when they access a system.

[1359] "Viewing history" refers to historical information about design works and pages that a user has previously viewed on the system.

[1360] The present invention is a matching system for users and designers that combines an emotion engine. The specific configuration and processing of this system will be described in detail below.

[1361] First, a user accesses the system and enters personal information such as their name, email address, and password on the new registration page. This is done using a device (such as the user's PC or smartphone), and the entered information is sent to the server via the HTTP protocol. The server then stores the received information in a database (e.g., MySQL). This ensures that the user's personal information is managed securely.

[1362] Next, when a designer uploads their design work to the system, they enter the image file and its metadata (title, description, tags, etc.). This information is temporarily stored on the device and checked for format and content. It is then sent to the server, where the image file is stored in file storage (e.g., AWS S3) and the metadata is stored in a database.

[1363] When a user searches for a design work, they access the search screen and enter a search query. The device sends this search query to the server, which then searches and extracts relevant design works from the database. The server then collects the user's past search history, purchase history, and browsing history and performs AI analysis. For example, it uses machine learning models such as TensorFlow and PyTorch to identify the user's preferences.

[1364] The emotion engine captures the user's reactions and facial expressions through a camera and microphone, and sends the generated emotion data from the device to a server. The server combines this emotion data with past history data to generate optimal suggestions. This allows users to receive personalized suggestions based on their emotions and preferences.

[1365] When a user wants to purchase a specific design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, who can then choose to approve or reject it. When the server receives a response from the designer, it notifies the user of the result. If approved, further negotiations and the purchase process can proceed.

[1366] As a concrete example, consider a user searching for "modern designer house." The server processes this search query and searches the database for related design works. By combining data from AI analysis and an emotion engine, the server makes optimal suggestions based on the user's past history and reactions. For example, if a user expresses an "interest" in a particular design, similar designs will be suggested.

[1367] Prompt Sentence Examples

[1368] 1. Prompt to display recommended design works when searching for "modern designer homes":

[1369] A user is searching for "modern design pieces." Please recommend the best design pieces based on the data below.

[1370] Search Query: modern designer house

[1371] User's past search history: [e.g. "contemporary design", "simple modern"]

[1372] User purchase history: [e.g., "Scandinavian interior design," "Minimalist art"]

[1373] User sentiment data: [e.g., interest level for search query: high]

[1374] 2. Prompt for generating a design purchase request:

[1375] A user wants to purchase a specific design piece. Please generate a purchase request using the following user and piece information:

[1376] User information: Taro, Email address: taro@example.com

[1377] Work information: Title: Modern Designer's House, Designer: Hanako

[1378] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1379] System processing flow

[1380] Step 1: Sign up

[1381] input:

[1382] A user accesses the new registration page and enters personal information such as name, email address, and password.

[1383] Specific behavior:

[1384] The device (user's PC or smartphone) temporarily stores this input data and checks the format of the input.

[1385] Data processing and calculation:

[1386] The terminal performs format checks on the input data (e.g., checking the format of the email address, checking the strength of the password).

[1387] output:

[1388] Based on the check results, if appropriate, the data is sent to the server, otherwise an error message is displayed to the user.

[1389] Step 2: Send and store user information

[1390] input:

[1391] User personal information sent from the device (name, email address, password).

[1392] Specific behavior:

[1393] The device sends information to the server via an HTTP request, and the server validates the received data.

[1394] Data processing and calculation:

[1395] The server validates the incoming data (e.g. checks for duplicate email addresses) and converts it into a secure data format.

[1396] output:

[1397] If validation is successful, the server saves the information in the database (MySQL) and returns a registration success message to the terminal.

[1398] Step 3: Upload your design

[1399] input:

[1400] Metadata entered by the designer, such as image files, title, description, and tags for the work.

[1401] Specific behavior:

[1402] The device temporarily stores this information and checks its format and content. Image file format checks (e.g., JPEG, PNG) are also performed.

[1403] Data processing and calculation:

[1404] The device checks the consistency of the metadata and image file, and performs image processing such as resizing and compression as necessary.

[1405] output:

[1406] If the check is successful, the terminal transmits the information to the server.

[1407] Step 4: Send and save your design to the server

[1408] input:

[1409] Image files and metadata of design work sent from your device.

[1410] Specific behavior:

[1411] The server receives this data, uploads the image files to file storage (AWS S3), and stores the metadata in a database.

[1412] Data processing and calculation:

[1413] The server validates the metadata, generates a URL for saving to file storage, and saves it in the database.

[1414] output:

[1415] If the saving is successful, the server returns a message to the terminal indicating that the listing was successful and notifies the designer.

[1416] Step 5: Find design ideas

[1417] input:

[1418] The search query entered by the user on the search screen (e.g., "modern designer home").

[1419] Specific behavior:

[1420] The terminal transmits the input search query to the server.

[1421] Data processing and calculation:

[1422] Based on the received query, the server generates an SQL query and extracts relevant design works from the database.

[1423] output:

[1424] Based on the search results and past search, purchase, and browsing history, the server generates a JSON response and sends it back to the device, which then displays it to the user.

[1425] Step 6: Generate a proposal

[1426] input:

[1427] Search results and your past search history, purchase history, browsing history, and sentiment data.

[1428] Specific behavior:

[1429] The server inputs this data into an AI model (TensorFlow or PyTorch) for analysis. It also obtains reaction data from the emotion engine and reflects it in the analysis.

[1430] Data processing and calculation:

[1431] The AI ​​model identifies user preferences and generates optimal product suggestions, while also analyzing emotional data to calculate the user's interest level.

[1432] output:

[1433] The server generates the proposed results and sends them to the device, which then displays them to the user.

[1434] Step 7: Submitting a Purchase Request

[1435] input:

[1436] Request information (user information, work information) sent by the user by pressing the "Purchase Request" button.

[1437] Specific behavior:

[1438] The terminal transmits this information to the server.

[1439] Data processing and calculation:

[1440] The server validates the request information and forwards it to the designer with notification.

[1441] output:

[1442] The server notifies the designer of the request and waits for the designer's response.

[1443] Step 8: Designer response and user notification

[1444] input:

[1445] The designer has the choice to approve or reject the request.

[1446] Specific behavior:

[1447] The designer's device sends the selection results to the server, which receives them and takes appropriate action.

[1448] Data processing and calculation:

[1449] The server generates a result notification for the user based on the designer's response.

[1450] output:

[1451] The server notifies the user of the response result and, if approved, assists with further purchase procedures.

[1452] (Application example 2)

[1453] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1454] Conventional user-designer matching systems lack the ability to provide personalized suggestions that fully reflect a user's individual tastes and emotions. As a result, users spend a long time finding their ideal design, and designers have limited opportunities to offer their work to the right users. Furthermore, especially when providing immersive experiences such as virtual stores, a system that reflects user emotions in real time and makes design discovery easier and seamless is needed.

[1455] 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.

[1456] In this invention, the server includes: means for users to register personal information through various input forms; means for transmitting the registered information to the server and saving it in a database; means for verifying registered user information and performing authentication; means for designers to upload design works and input metadata about the works (e.g., title, description, tags, etc.); means for transmitting the design works and their metadata to the server and saving them in the database; means for users to input search queries and send them to the server; means for the server to search for related designs from the database and perform AI analysis to generate proposals based on the user's tastes and preferences; means for displaying the search results and proposed design works to the user; means for acquiring emotional data from the user's reactions and facial expressions using an emotion analysis device; means for transmitting the acquired emotional data to the server and combining it with AI analysis to provide personalized design proposals to the user; and means for users to issue purchase requests and notify designers of the requests. This enables personalized proposals in real time based on the user's emotions, making it easier for users to efficiently find their ideal designs and increasing designers' opportunities to provide their works to appropriate users.

[1457] "User" means an individual or corporation that uses the System to search for and purchase design works.

[1458] "Designer" means an individual or legal entity responsible for uploading design works to the system.

[1459] "Server" refers to a computer system that receives data sent by users and designers, and stores and manages the data in a database.

[1460] A "database" is a system connected to a server for systematically storing and managing user information and metadata of design works.

[1461] "Metadata" refers to additional information such as title, description, and tags associated with a design work.

[1462] An "emotion analysis device" is a device that captures and analyzes emotional data from a user's reactions and facial expressions.

[1463] "Emotion data" is user emotion information acquired by the emotion analysis device.

[1464] "AI analysis" is the process of using artificial intelligence technology to analyze users' tastes, preferences, and emotional data and generate suggestions.

[1465] "Personalized proposals" are proposals for customized design works based on the user's individual tastes, preferences, and emotional data.

[1466] A "Purchase Request" is a request by a User to express their intent to purchase a particular Design Work.

[1467] A "notification" is a message that conveys information from the server to the designer or user.

[1468] This system is a comprehensive platform that allows users to efficiently search and purchase design works and allows designers to deliver their works to the right customers. Specific embodiments are described below.

[1469] User Registration

[1470] First, the user accesses the system and enters personal information such as name, email address, and password on the new registration page. The terminal sends this information to the server, which stores the received information in a database. If registration is successful, the terminal displays a registration success message to the user.

[1471] Upload your design

[1472] Next, the designer uploads their design. The designer enters metadata such as the image file, title, description, and tags of the work and uploads it. The device temporarily saves this information, checks the format and content, and then sends it to the server. The server saves the received information in a database and returns a message to the device indicating that the save was successful, displaying a message to the designer indicating that the listing was successful.

[1473] Sentiment analysis and AI suggestions

[1474] When a user searches for a design work, they access the search screen and enter a search query. The device sends the entered search query to the server, which then searches for and extracts relevant design works from a database. The server then collects the user's past search history, purchase history, and browsing history and performs AI analysis. An emotion analyzer (such as OpenCV or Face API) obtains emotional data from the user's reactions and facial expressions and sends that data to the server. The server combines this data and uses a deep learning framework (such as TensorFlow or PyTorch) to generate optimal suggestions based on the user's preferences and tastes, which are then displayed to the user along with the search results.

[1475] Purchase Process

[1476] When a user wants to purchase a specific design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, and the designer responds in real time using Firebase Cloud Messaging. When the server receives a response from the designer (approval or rejection), it notifies the user of the result.

[1477] Specific examples

[1478] As a concrete example, when a user searches for "modern designer house," the server searches the database for related design works and uses AI analysis and an emotion engine to make optimal suggestions based on the user's past history and reactions. For example, if the emotion engine recognizes an "interest" in a design work that the user is looking at with interest, it will recommend designs similar to that work. Multiple design works are displayed to the user as search results. If the user likes one of them and submits a purchase request, the designer is notified, and the deal is concluded after the designer's approval.

[1479] Prompt Sentence Examples

[1480] "I'm looking for a modern designer home. I'm looking for a design similar to the urban interiors I've seen in the past. Also, please use sentiment analysis to suggest which design would be best for me."

[1481] The above is a concrete example of how the present invention can be implemented. Users can efficiently find their ideal design work through real-time suggestions based on their emotions, and designers can have the opportunity to provide their work to the right users.

[1482] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1483] Step 1:

[1484] The user enters personal information (name, email address, password, etc.) on the new registration page.

[1485] Input: The user enters personal information.

[1486] Data processing: The terminal sends these data to the server.

[1487] Output: The server stores the received information in a database and displays a registration success message on the terminal.

[1488] Step 2:

[1489] Designers upload their design work and enter the work's metadata (image file, title, description, tags, etc.).

[1490] Input: Designers input design work and metadata.

[1491] Data processing: The device temporarily stores this data and checks its format and content.

[1492] Output: Sent to server and saved in database. A message of successful saving is displayed in the designer.

[1493] Step 3:

[1494] A user enters a search query to search for design work.

[1495] Input: The user types a search query.

[1496] Data processing: The terminal sends the entered search query to the server, which then searches and extracts relevant design works from the database.

[1497] Output: The relevant design work is displayed to the user.

[1498] Step 4:

[1499] Using AI and sentiment analysis, suggestions are generated based on the user's tastes and preferences.

[1500] Input: Past search history, purchase history, browsing history, and emotional data obtained from reactions and facial expressions.

[1501] Data processing: The server analyzes the data using deep learning frameworks (TensorFlow, PyTorch) and generates personalized suggestions.

[1502] Output: A list of proposed design works is displayed to the user.

[1503] Step 5:

[1504] The user places a purchase request and notifies the designer of the request.

[1505] Input: User information, work information.

[1506] Data processing: The terminal sends the purchase request information to the server.

[1507] Output: The server notifies the designer of the request.

[1508] Step 6:

[1509] The designer responds to the purchase request.

[1510] Input: Approval or rejection response from the designer.

[1511] Data processing: The server receives the designer's response and notifies the user.

[1512] Output: The user is shown the approval or rejection result.

[1513] Step 7:

[1514] If the deal is successful, the user and designer will proceed with detailed negotiations.

[1515] Input: Opportunity details.

[1516] Data processing: Transaction-related information is stored on the server and updated and managed as necessary.

[1517] Output: A notification of the transaction completion is sent to both parties.

[1518] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1519] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1520] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1521] [Fourth embodiment]

[1522] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1523] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1524] 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).

[1525] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1526] 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.

[1527] 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).

[1528] 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.

[1529] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1530] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1531] 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.

[1532] 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.

[1533] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1534] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1535] The present invention is a system for efficiently matching users and designers, and is implemented in the following manner.

[1536] First, the user accesses the system and enters personal information such as name, email address, and password on the new registration page. The terminal sends this information to the server, which stores the received information in a database. If registration is successful, the terminal displays a registration success message to the user.

[1537] Next, the designer uploads the image file, title, description, tags, and other metadata of the work to be exhibited. The device temporarily saves this information, checks the format and content, and then sends it to the server. The server saves the received information in a database and returns a message to the device indicating that the save was successful, displaying a message to the designer indicating that the exhibit was successful.

[1538] When a user searches for a design work, they access the search screen and enter a search query. The device sends the entered search query to the server, which then searches and extracts relevant design works from the database. The server then uses AI to analyze the user's past search history, purchase history, and browsing history to generate design work suggestions based on the user's preferences. The search results and suggested design works are sent to the device and displayed to the user.

[1539] When a user wants to purchase a specific design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, who responds with an interface that allows the user to choose whether to approve or reject the request. When the server receives a response from the designer, it notifies the user of the result. If approval is granted, further negotiations and the purchase process can proceed.

[1540] For example, when a user searches for "modern designer house," the server searches the database for related design works and uses AI analysis to make optimal suggestions based on past history. Multiple design works are displayed to the user as search results. If the user likes one of them and submits a purchase request, the designer is notified, and the deal is concluded after the designer's approval.

[1541] This system allows users to efficiently find their ideal design work and gives designers the opportunity to offer their work to the right users.

[1542] The processing flow will be explained below.

[1543] User Registration and Login

[1544] User registration process

[1545] Step 1:

[1546] The user accesses the registration screen and enters personal information such as name, email address, and password.

[1547] Step 2:

[1548] The terminal checks the information entered to see if there are any omissions or errors.

[1549] Step 3:

[1550] The device sends the verified information to the server.

[1551] Step 4:

[1552] The server receives the personal information sent and stores it in a database.

[1553] Step 5:

[1554] The server sends a save success message to the terminal.

[1555] Step 6:

[1556] The device displays a registration success message to the user.

[1557] Login process

[1558] Step 1:

[1559] The user accesses the login screen and enters their email address and password.

[1560] Step 2:

[1561] The device sends the entered email address and password to the server.

[1562] Step 3:

[1563] The server checks the user information against the information stored in its database.

[1564] Step 4:

[1565] The server sends the login success or failure status to the terminal.

[1566] Step 5:

[1567] The terminal displays a login success or login failure message to the user.

[1568] Submission of design works

[1569] Step 1:

[1570] The user (designer) accesses the work submission screen and enters metadata such as the work's image file, title, description, and tags.

[1571] Step 2:

[1572] The device temporarily stores the entered information and checks the file format and content.

[1573] Step 3:

[1574] The device sends the verified information to the server.

[1575] Step 4:

[1576] The server receives the transmitted information and stores it in a database.

[1577] Step 5:

[1578] The server sends a save success message to the terminal.

[1579] Step 6:

[1580] The device will display a listing success message to the designer.

[1581] Design search and suggestions

[1582] Search processing

[1583] Step 1:

[1584] The user accesses the search screen and enters a search query (keywords or category).

[1585] Step 2:

[1586] The terminal transmits the entered search query to the server.

[1587] Step 3:

[1588] The server searches the database for relevant designs and filters the results.

[1589] Step 4:

[1590] The server sends the filtered search results to the device.

[1591] Step 5:

[1592] The device displays the search results to the user.

[1593] Proposal Processing

[1594] Step 1:

[1595] The server retrieves the user's past search history, purchase history, and browsing history from a database.

[1596] Step 2:

[1597] The server analyzes this data using AI to identify user preferences.

[1598] Step 3:

[1599] The server searches the database for design works that may suit the user and generates a list of recommended works.

[1600] Step 4:

[1601] The server sends a list of recommended works to the terminal.

[1602] Step 5:

[1603] The device displays recommended works to the user.

[1604] Purchases and negotiations

[1605] Purchase Request Processing

[1606] Step 1:

[1607] The user accesses the details page of the design work they wish to purchase and clicks the "Purchase Request" button.

[1608] Step 2:

[1609] The device sends the purchase request information (user information, work information) to the server.

[1610] Step 3:

[1611] The server notifies the designer of the received request and saves the request in the database.

[1612] Step 4:

[1613] The server provides an interface for the designer to approve or deny the request.

[1614] Step 5:

[1615] The designer approves or denies the request and sends the response to the server.

[1616] Step 6:

[1617] The server receives the response from the designer and notifies the user of the result.

[1618] Step 7:

[1619] The device displays the results of the request to the user.

[1620] Example 1

[1621] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1622] The challenge is to efficiently match users with designers, enabling users to quickly and appropriately find the design works they are looking for, and enabling designers to effectively provide their work to interested users. The current system has difficulty accurately reflecting users' search intent and preferences, resulting in a long wait for users to find the work they are looking for. Designers also face the risk of missing sales opportunities, as they are uncertain whether their work will reach the right target audience.

[1623] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1624] In this invention, the server includes: means for users to register personal information through various input forms; means for transmitting the registered information to the server and saving it in a database; means for verifying registered user information and performing authentication; means for designers to upload design works and input metadata about the works (title, description, tags, etc.); means for transmitting the design works and their metadata to the server and saving them in the database; means for users to input search queries and send them to the server; means for the server to search for related designs from the database and generate suggestions based on the user's tastes and preferences using a generative AI model; means for users to issue purchase requests and notify designers of the requests; and means for receiving purchase approval or rejection from designers and notifying the user of the results. This allows users to efficiently find their ideal design works and gives designers the opportunity to offer their works to appropriate users.

[1625] "User" means any individual or entity that accesses the System to search, browse, and purchase Design Works.

[1626] "Designer" means an individual or entity that creates a design work and uploads it to the System.

[1627] "Server" means the central management system that receives, processes and stores information from Users and Designers.

[1628] "Database" refers to the collection of digital data managed by the server for storing and managing information submitted by Users and Designers.

[1629] "Personal information" refers to information that identifies an individual, such as name, email address, password, etc., that a user or designer registers in the system.

[1630] "Metadata" refers to additional information about a design work, such as title, description, and tags.

[1631] "Generative AI model" refers to an algorithm and the means to implement it that uses artificial intelligence to analyze a user's tastes and preferences and suggest optimal design works.

[1632] "Purchase Request" means a request by a User to indicate their intent to purchase a particular Design Work and notify a Designer of such intent.

[1633] "Authentication" refers to the process of verifying a user's or designer's registration information to ensure that the person has legitimate access rights.

[1634] "Proposal" refers to a design work selected based on the user's tastes and preferences as a result of analysis using a generative AI model.

[1635] "Notification" means a message or alert sent by the Server to provide specific information to a User or Designer.

[1636] The present invention is a system for efficiently matching users and designers, and is implemented using specific hardware and software. The system includes a series of processes for improving the experience for both users and designers. The details are described below.

[1637] First, a user accesses the system and registers. At this time, the user enters personal information such as name, email address, and password. The terminal sends this information to the server, which then stores the received information in a database. If the storage is successful, the server returns a registration success message to the terminal, which then displays this message to the user.

[1638] Next, when a designer wants to exhibit their design, they enter metadata such as the image file, title, description, and tags of the work. The device temporarily stores this information, checks the format and content, and then sends it to the server. The server stores the information in a database and returns a success message to the device, which then displays a successful exhibit message to the designer.

[1639] When a user searches for a design work, they access the search screen and enter a search query. The device sends the entered search query to the server, which then searches and extracts relevant design works from the database. The server then uses a generative AI model (e.g., TensorFlow, PyTorch) to analyze the user's past search history, purchase history, and browsing history to generate design work suggestions based on the user's preferences. The search results and suggested design works are sent to the device, which then displays them to the user.

[1640] When a user wants to purchase a particular design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, who responds with an interface that allows the user to choose whether to approve or reject the request. Once the server receives a response from the designer, it notifies the user of the result. If approved, the user can proceed with detailed negotiations and the purchase process.

[1641] For example, if a user searches for "modern designer house," the server searches the database for related design works and uses a generative AI model to make optimal suggestions based on past history. Multiple design works are displayed to the user as search results, and the user submits a purchase request for the work they like. The designer is notified, and if approved, the deal is concluded.

[1642] Examples of prompts for generative AI models include:

[1643] "Suggest design pieces that might interest you based on your past search and purchase history."

[1644] "Search for design work related to modern designer homes and see the best results."

[1645] This system allows users to efficiently find their ideal design work, and gives designers the opportunity to offer their work to the right users. Furthermore, by using a generative AI model, highly accurate suggestions that match the user's tastes and preferences can be realized.

[1646] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1647] Step 1:

[1648] The user accesses the new registration page. The user enters personal information such as name, email address, and password. This input data is acquired by the terminal and sent to the server. The server stores the received information in a database. If the storage is successful, the server generates a registration success message and sends it to the terminal. The terminal displays this message to the user.

[1649] Input: Personal information such as name, email address, and password

[1650] Output: Registration successful message

[1651] Step 2:

[1652] The designer accesses the work submission page and enters metadata such as the work's image file, title, description, and tags. The device temporarily saves this information and checks its format and content. After format and content checks are complete, the device sends the information to the server. The server saves the received information in a database. If the save is successful, the server generates a save success message and sends it to the device. The device displays this message to the designer.

[1653] Input: Image file, metadata such as title, description, tags etc.

[1654] Output: Listing successful message

[1655] Step 3:

[1656] The user accesses the search screen and enters a search query. The device sends this search query to the server, which searches and extracts relevant design works from the database. The server then uses a generative AI model to analyze the user's past search history, purchase history, and browsing history to generate suggestions based on the user's tastes and preferences. The generated search results and suggestions are sent from the server to the device, which then displays them to the user.

[1657] Input: Search queries, user's past search history, purchase history, browsing history

[1658] Output: Search results and proposed design work

[1659] Step 4:

[1660] When a user wants to purchase a specific design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, who can then choose to approve or reject it. The designer's response is sent to the server, which then notifies the user accordingly. If the request is approved, the user can proceed with further negotiations and the purchase process.

[1661] Input: Purchase request information (user information, work information)

[1662] Output: Notification of purchase request outcome (approval or rejection)

[1663] The combination of specific processes at each step allows for smooth communication between the user and the designer, and the use of generative AI models allows for highly accurate suggestions based on the user's preferences.

[1664] (Application example 1)

[1665] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1666] In previous user-designer matching systems, users had limited access to detailed information and purchasing options for specific designs in physical stores, making efficient matching difficult. Furthermore, optimal suggestions based on a user's past purchase history were often not effectively provided. This made it difficult for users to find designs that matched their tastes, and prevented designers from making the most of opportunities to offer their work to the right users.

[1667] 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.

[1668] In this invention, the server includes: means for a user to register personal information through various input forms; means for transmitting the registered information to the server and saving it in a database; means for verifying registered user information and performing authentication; means for a designer to upload a design work and input metadata (title, description, tags, etc.) related to the work; means for transmitting the design work and its metadata to the server and saving it in the database; means for a user to input a search query and send it to the server; means for the server to search for related designs from the database and perform AI analysis to generate suggestions based on the user's tastes and preferences; means for the user to display the search results and suggested design works to the user; means for the user to issue a purchase request and notify the designer of the request; means for the user to read a two-dimensional code related to a target item; and means for displaying metadata and purchase options for the target item based on the read two-dimensional code. This allows users to intuitively and efficiently obtain detailed information about design works and submit purchase requests in physical stores, and also enables AI to suggest optimal design works based on past history.

[1669] "User" means any individual or organization that accesses the System to search for and request the purchase of Design Works.

[1670] "Designer" means an individual or organization that uploads and provides design work to the system.

[1671] "Personal information" refers to information such as name, email address, and password that users or designers register through various input forms.

[1672] "Metadata" refers to supplemental information, such as titles, descriptions, and tags, associated with a design work that specifically describes the characteristics of the work.

[1673] A "two-dimensional code" is a code pattern similar to a QR code that stores information and allows quick data access by reading it.

[1674] "Purchase Request" means a request made by a User to purchase a particular Design Work, which is communicated to a Designer.

[1675] A "database" is a storage area within a system that systematically stores information about users and designers, design works, and their metadata, and enables searching and retrieval.

[1676] A "server" is a computer device that receives and processes information sent by users and designers, and provides various functions in cooperation with a database.

[1677] "AI analysis" is the process of using artificial intelligence technology to analyze a user's past search history, purchase history, and browsing history, and generate design suggestions based on the user's preferences.

[1678] A "search query" is a keyword or phrase entered by a user to search for design work.

[1679] This invention is a system for efficiently matching users and designers, and is intended for use in brick-and-mortar stores. The system is composed of multiple hardware and software components.

[1680] 1. User Registration and Authentication:

[1681] Users access the system and enter personal information such as their name, email address, and password through various input forms. This information is sent from the terminal to the server, which stores the received information in a database. The registered user information is verified and authentication is performed. Through this procedure, the user gains access to the system.

[1682] Hardware used: User device (smartphone or tablet)

[1683] Software used: Web browser, Flask (Python web framework)

[1684] 2. Upload your design:

[1685] Designers upload their design work to the system and enter metadata about the work (title, description, tags, etc.). This information is temporarily stored on the device and sent to the server after format and content checks. The server stores the received information in a database, and the designer is notified of a successful upload.

[1686] Hardware used: Designer's device (PC or tablet)

[1687] Software used: Web browser, Flask, SQLite3

[1688] 3. QR Code Scan:

[1689] Users scan QR codes associated with design pieces displayed in physical stores with their smartphones. The scanned QR code is sent to a server to display the item's metadata and purchasing options. The server retrieves the corresponding information from a database and sends it back to the user's device, where the user can view detailed information about the piece.

[1690] Hardware used: User device (smartphone)

[1691] Software used: QR code reader, Flask, SQLite3

[1692] 4. AI Recommendations:

[1693] The server collects the user's past search history, purchase history, and browsing history and performs AI analysis. An AI model (e.g., RandomForestClassifier) ​​uses this data to identify the user's preferences and generate optimal design proposals. These recommendations are sent to the user's device and displayed to the user.

[1694] Hardware used: Server

[1695] Software used: scikit-learn (Python machine learning library), Flask, SQLite3

[1696] Examples:

[1697] When a user searches for "modern design furniture" in a physical store, the server searches the database for related design works and uses AI analysis to make optimal suggestions based on past history. Multiple recommended design works are displayed on the user's smartphone, and they can submit a purchase request from the detail page of the work they like.

[1698] Example prompt sentence:

[1699] User ID: 12345

[1700] Previous browsing history: ["modern design", "simple furniture", "Scandinavian style"]

[1701] Purchase history: ["Simple chair", "Scandinavian-style table"]

[1702] Please suggest designs based on this history.

[1703] This invention allows users to intuitively and efficiently obtain detailed information about design items and submit purchase requests in a physical store, while also enabling AI to suggest optimal design items based on past history.

[1704] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1705] Step 1:

[1706] The user uses a device to enter personal information (such as name, email address, and password) through various input forms. The entered personal information is sent from the device to the server. The server stores the received information in a database. At this stage, the entered information is recorded in the database as is (data storage).

[1707] Input: Personal information (name, email address, password)

[1708] Output: User information stored in the database

[1709] Step 2:

[1710] The server compares the received personal information with the database and authenticates the user. If the comparison is correct, it sends a message to the device indicating successful registration. During this process, the user is authenticated by comparing the information with the information in the database (data comparison and authentication).

[1711] Input: User information stored in the database

[1712] Output: Registration successful message

[1713] Step 3:

[1714] Designers use their devices to upload their design work to the system. They enter metadata such as the work's image file, title, description, and tags, and the uploaded information is temporarily stored on the device. It is then checked for format and content before being sent to the server. The server stores the received information in a database and displays a message to the designer indicating that the upload was successful. This is where metadata is entered and saved (data entry, checking, and saving).

[1715] Input: Image file of design work, metadata (title, description, tags, etc.)

[1716] Output: Design information saved in the database, upload success message

[1717] Step 4:

[1718] A user scans a QR code with their smartphone in a physical store. The data from the scanned QR code is sent from the device to a server, which retrieves the metadata and purchase options for the item from a database. The retrieved information is sent back to the device and displayed to the user. In this step, the QR code is scanned, the database is searched, and the information is retrieved and displayed (data retrieval and display).

[1719] Input: QR code data

[1720] Output: Metadata and purchase options for the item

[1721] Step 5:

[1722] The user enters a search query and sends it from their device to the server. The server searches for relevant designs in the database and performs AI analysis to generate recommendations based on the user's preferences. The generated recommendations are sent to the device and displayed to the user. In this step, analysis and recommendation generation are performed using an AI model (data analysis and recommendations).

[1723] Input: Search query

[1724] Output: Search results and recommendations

[1725] Step 6:

[1726] When a user wants to purchase a particular design work, they press the "Purchase Request" button on the details page. The terminal sends the purchase request information (user information, work information) to the server. The server notifies the designer of the request, and the designer responds with an interface that allows the user to choose whether to accept or reject. When the server receives the response from the designer, it notifies the user of the result. In this step, the purchase request is issued, notified, and responded to and notified (request generation and processing).

[1727] Input: Purchase request information (user information, work information)

[1728] Output: Designer's response results

[1729] Step 7:

[1730] The server collects the user's past search history, purchase history, and browsing history, and performs AI analysis based on this. An AI model (e.g., RandomForestClassifier) ​​uses this data to identify the user's tastes and preferences and recommend the most suitable design pieces. This process involves analysis and recommendation generation using machine learning models.

[1731] Input: Past search history, purchase history, browsing history

[1732] Output: Proposal of optimal design work

[1733] For example, here is a prompt example for a user searching for "modern furniture design":

[1734] Example prompt sentence:

[1735] User ID: 12345

[1736] Previous browsing history: ["modern design", "simple furniture", "Scandinavian style"]

[1737] Purchase history: ["Simple chair", "Scandinavian-style table"]

[1738] Please suggest designs based on this history.

[1739] Through these steps, users can efficiently obtain detailed information about design works and submit purchase requests, while AI can suggest the most suitable design works based on past history.

[1740] 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.

[1741] The present invention is a matching system for users and designers that combines an emotion engine, and is implemented in the following steps.

[1742] First, the user accesses the system and enters personal information such as name, email address, and password on the new registration page. The terminal sends this information to the server, which stores the received information in a database. If registration is successful, the terminal displays a registration success message to the user.

[1743] Next, the designer uploads the image file, title, description, tags, and other metadata of the work to be exhibited. The device temporarily saves this information, checks the format and content, and then sends it to the server. The server saves the received information in a database and returns a message to the device indicating that the save was successful, displaying a message to the designer indicating that the exhibit was successful.

[1744] When a user searches for a design work, they access the search screen and enter a search query. The device sends the entered search query to the server, which then searches for and extracts relevant design works from a database. The server then analyzes the user's past search history, purchase history, and browsing history and performs an AI analysis. An emotion engine also obtains emotional data from the user's reactions and facial expressions and sends that data to the server. The server combines this data to generate design work suggestions based on the user's tastes and preferences, and displays the search results and suggested design works to the user.

[1745] When a user wants to purchase a specific design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, who responds with an interface that allows the user to choose whether to approve or reject the request. When the server receives a response from the designer, it notifies the user of the result. If approval is granted, further negotiations and the purchase process can proceed.

[1746] As a specific example, when a user searches for "modern designer house," the server searches the database for related design works, combines AI analysis with data obtained from the emotion engine, and makes optimal suggestions based on the user's past history and reactions. For example, if the emotion engine recognizes an "interest" in a design work that the user is looking at with interest, it will recommend designs similar to that work. Multiple design works are displayed to the user as search results. If the user likes one of them and submits a purchase request, the designer is notified, and the deal is concluded after the designer's approval.

[1747] This system allows users to intuitively and efficiently find their ideal design work, and gives designers the opportunity to deliver their work to the right users. By combining it with an emotion engine, personalized suggestions based on user emotions can be made, resulting in even higher satisfaction.

[1748] The processing flow will be explained below.

[1749] User Registration and Login

[1750] User registration process

[1751] Step 1:

[1752] The user accesses the registration screen and enters personal information such as name, email address, and password.

[1753] Step 2:

[1754] The terminal checks the information entered to see if there are any omissions or errors.

[1755] Step 3:

[1756] The device sends the verified information to the server.

[1757] Step 4:

[1758] The server receives the personal information sent and stores it in a database.

[1759] Step 5:

[1760] The server sends a save success message to the terminal.

[1761] Step 6:

[1762] The device displays a registration success message to the user.

[1763] Login process

[1764] Step 1:

[1765] The user accesses the login screen and enters their email address and password.

[1766] Step 2:

[1767] The device sends the entered email address and password to the server.

[1768] Step 3:

[1769] The server checks the user information against the information stored in its database.

[1770] Step 4:

[1771] The server sends the login success or failure status to the terminal.

[1772] Step 5:

[1773] The terminal displays a login success or login failure message to the user.

[1774] Submission of design works

[1775] Step 1:

[1776] The user (designer) accesses the work submission screen and enters metadata such as the work's image file, title, description, and tags.

[1777] Step 2:

[1778] The device temporarily stores the entered information and checks the file format and content.

[1779] Step 3:

[1780] The device sends the verified information to the server.

[1781] Step 4:

[1782] The server receives the transmitted information and stores it in a database.

[1783] Step 5:

[1784] The server sends a save success message to the terminal.

[1785] Step 6:

[1786] The device will display a listing success message to the designer.

[1787] Design search and suggestions

[1788] Search processing

[1789] Step 1:

[1790] The user accesses the search screen and enters a search query (keywords or category).

[1791] Step 2:

[1792] The terminal transmits the entered search query to the server.

[1793] Step 3:

[1794] The server searches the database for relevant design work and filters the results.

[1795] Step 4:

[1796] The server sends the filtered search results to the device.

[1797] Step 5:

[1798] The device displays the search results to the user.

[1799] Proposal Processing

[1800] Step 1:

[1801] The server retrieves the user's past search history, purchase history, and browsing history from a database.

[1802] Step 2:

[1803] The server analyzes this data using AI to identify user preferences.

[1804] Step 3:

[1805] The server searches the database for design works that may suit the user and generates a list of recommended works.

[1806] Step 4:

[1807] The server sends a list of recommended works to the terminal.

[1808] Step 5:

[1809] The device displays recommended works to the user.

[1810] Emotion recognition and suggestions using an emotion engine

[1811] Emotion Recognition Processing

[1812] Step 1:

[1813] While users search and browse design works, the emotion engine uses cameras and sensors to detect the user's facial expressions and reactions.

[1814] Step 2:

[1815] The device transmits the detected emotion data to the server.

[1816] Step 3:

[1817] The server uses AI to analyze the emotional data received and identify the user's current emotional state.

[1818] Emotion-based suggestion generation

[1819] Step 1:

[1820] The server combines the user's preference trend data and emotional data previously acquired and re-searches for related design works from the database.

[1821] Step 2:

[1822] The server generates a list of recommended works based on the emotions.

[1823] Step 3:

[1824] The server sends a list of recommended works to the terminal.

[1825] Step 4:

[1826] The device displays emotionally-based recommendations to the user.

[1827] Purchases and negotiations

[1828] Purchase Request Processing

[1829] Step 1:

[1830] The user accesses the details page of the design work they wish to purchase and clicks the "Purchase Request" button.

[1831] Step 2:

[1832] The device sends the purchase request information (user information, work information) to the server.

[1833] Step 3:

[1834] The server notifies the designer of the received request and saves the request in the database.

[1835] Step 4:

[1836] The server provides an interface for the designer to approve or deny the request.

[1837] Step 5:

[1838] The designer approves or denies the request and sends the response to the server.

[1839] Step 6:

[1840] The server receives the response from the designer and notifies the user of the result.

[1841] Step 7:

[1842] The device displays the results of the request to the user.

[1843] Example 2

[1844] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1845] Conventional user-designer matching systems lacked personalized suggestions based on the user's preferences and emotions. This made it difficult for users to quickly find designs that matched their tastes and emotions, resulting in low satisfaction. Furthermore, communication between users and designers was sometimes insufficient during the purchasing process, reducing transaction efficiency.

[1846] The specification processing by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring user emotion data and transmitting it to the server, means for the server to analyze the user emotion data and reflect it in the generation of proposed works, and means for collecting the user's past search history, purchase history, browsing history, and emotion data and identifying the user's preference trends using AI based on this. This enables the user to receive proposals for optimal design works based on their emotions and preferences, and furthermore, the purchasing procedure between the user and the designer is carried out smoothly, improving the usability and satisfaction of the entire system.

[1847] "User" means an individual or organization that uses this system to search for and purchase design works.

[1848] "Designers" are individuals or organizations that use this system to upload and sell their design works.

[1849] "Emotional data" refers to information about emotions obtained from a user's reactions, facial expressions, voice, etc.

[1850] A "server" is a computer system responsible for receiving and processing information sent by users and designers.

[1851] A "database" is a system installed on a server for efficiently managing and searching information.

[1852] A "search query" is a keyword or phrase that a user enters when searching for design work.

[1853] "Metadata" is additional information about a design work, including title, description, tags, etc.

[1854] A "generative AI model" is an artificial intelligence model used to analyze a user's habits and preferences and suggest optimal design pieces.

[1855] "Purchase Request" means a request submitted by a User wishing to purchase a particular Design Product.

[1856] "Proposed works" are design works that the server recommends based on the user's history and emotional data.

[1857] "Upload" refers to the data transmission operation that a designer performs to register his or her design work in the system.

[1858] "Authentication" is the process of verifying the legitimacy of users and designers when they access a system.

[1859] "Viewing history" refers to historical information about design works and pages that a user has previously viewed on the system.

[1860] The present invention is a matching system for users and designers that combines an emotion engine. The specific configuration and processing of this system will be described in detail below.

[1861] First, a user accesses the system and enters personal information such as their name, email address, and password on the new registration page. This is done using a device (such as the user's PC or smartphone), and the entered information is sent to the server via the HTTP protocol. The server then stores the received information in a database (e.g., MySQL). This ensures that the user's personal information is managed securely.

[1862] Next, when a designer uploads their design work to the system, they enter the image file and its metadata (title, description, tags, etc.). This information is temporarily stored on the device and checked for format and content. It is then sent to the server, where the image file is stored in file storage (e.g., AWS S3) and the metadata is stored in a database.

[1863] When a user searches for a design work, they access the search screen and enter a search query. The device sends this search query to the server, which then searches and extracts relevant design works from the database. The server then collects the user's past search history, purchase history, and browsing history and performs AI analysis. For example, it uses machine learning models such as TensorFlow and PyTorch to identify the user's preferences.

[1864] The emotion engine captures the user's reactions and facial expressions through a camera and microphone, and sends the generated emotion data from the device to a server. The server combines this emotion data with past history data to generate optimal suggestions. This allows users to receive personalized suggestions based on their emotions and preferences.

[1865] When a user wants to purchase a specific design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, who can then choose to approve or reject it. When the server receives a response from the designer, it notifies the user of the result. If approved, further negotiations and the purchase process can proceed.

[1866] As a concrete example, consider a user searching for "modern designer house." The server processes this search query and searches the database for related design works. By combining data from AI analysis and an emotion engine, the server makes optimal suggestions based on the user's past history and reactions. For example, if a user expresses an "interest" in a particular design, similar designs will be suggested.

[1867] Prompt Sentence Examples

[1868] 1. Prompt to display recommended design works when searching for "modern designer homes":

[1869] A user is searching for "modern design pieces." Please recommend the best design pieces based on the data below.

[1870] Search Query: modern designer house

[1871] User's past search history: [e.g. "contemporary design", "simple modern"]

[1872] User purchase history: [e.g., "Scandinavian interior design," "Minimalist art"]

[1873] User sentiment data: [e.g., interest level for search query: high]

[1874] 2. Prompt for generating a design purchase request:

[1875] A user wants to purchase a specific design piece. Please generate a purchase request using the following user and piece information:

[1876] User information: Taro, Email address: taro@example.com

[1877] Work information: Title: Modern Designer's House, Designer: Hanako

[1878] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1879] System processing flow

[1880] Step 1: Sign up

[1881] input:

[1882] A user accesses the new registration page and enters personal information such as name, email address, and password.

[1883] Specific behavior:

[1884] The device (user's PC or smartphone) temporarily stores this input data and checks the format of the input.

[1885] Data processing and calculation:

[1886] The terminal performs format checks on the input data (e.g., checking the format of the email address, checking the strength of the password).

[1887] output:

[1888] Based on the check results, if appropriate, the data is sent to the server, otherwise an error message is displayed to the user.

[1889] Step 2: Send and store user information

[1890] input:

[1891] User personal information sent from the device (name, email address, password).

[1892] Specific behavior:

[1893] The device sends information to the server via an HTTP request, and the server validates the received data.

[1894] Data processing and calculation:

[1895] The server validates the incoming data (e.g. checks for duplicate email addresses) and converts it into a secure data format.

[1896] output:

[1897] If validation is successful, the server saves the information in the database (MySQL) and returns a registration success message to the terminal.

[1898] Step 3: Upload your design

[1899] input:

[1900] Metadata entered by the designer, such as image files, title, description, and tags for the work.

[1901] Specific behavior:

[1902] The device temporarily stores this information and checks its format and content. Image file format checks (e.g., JPEG, PNG) are also performed.

[1903] Data processing and calculation:

[1904] The device checks the consistency of the metadata and image file, and performs image processing such as resizing and compression as necessary.

[1905] output:

[1906] If the check is successful, the terminal transmits the information to the server.

[1907] Step 4: Send and save your design to the server

[1908] input:

[1909] Image files and metadata of design work sent from your device.

[1910] Specific behavior:

[1911] The server receives this data, uploads the image files to file storage (AWS S3), and stores the metadata in a database.

[1912] Data processing and calculation:

[1913] The server validates the metadata, generates a URL for saving to file storage, and saves it in the database.

[1914] output:

[1915] If the saving is successful, the server returns a message to the terminal indicating that the listing was successful and notifies the designer.

[1916] Step 5: Find design ideas

[1917] input:

[1918] The search query entered by the user on the search screen (e.g., "modern designer home").

[1919] Specific behavior:

[1920] The terminal transmits the input search query to the server.

[1921] Data processing and calculation:

[1922] Based on the received query, the server generates an SQL query and extracts relevant design works from the database.

[1923] output:

[1924] Based on the search results and past search, purchase, and browsing history, the server generates a JSON response and sends it back to the device, which then displays it to the user.

[1925] Step 6: Generate a proposal

[1926] input:

[1927] Search results and your past search history, purchase history, browsing history, and sentiment data.

[1928] Specific behavior:

[1929] The server inputs this data into an AI model (TensorFlow or PyTorch) for analysis. It also obtains reaction data from the emotion engine and reflects it in the analysis.

[1930] Data processing and calculation:

[1931] The AI ​​model identifies user preferences and generates optimal product suggestions, while also analyzing emotional data to calculate the user's interest level.

[1932] output:

[1933] The server generates the proposed results and sends them to the device, which then displays them to the user.

[1934] Step 7: Submitting a Purchase Request

[1935] input:

[1936] Request information (user information, work information) sent by the user by pressing the "Purchase Request" button.

[1937] Specific behavior:

[1938] The terminal transmits this information to the server.

[1939] Data processing and calculation:

[1940] The server validates the request information and forwards it to the designer with notification.

[1941] output:

[1942] The server notifies the designer of the request and waits for the designer's response.

[1943] Step 8: Designer response and user notification

[1944] input:

[1945] The designer has the choice to approve or reject the request.

[1946] Specific behavior:

[1947] The designer's device sends the selection results to the server, which receives them and takes appropriate action.

[1948] Data processing and calculation:

[1949] The server generates a result notification for the user based on the designer's response.

[1950] output:

[1951] The server notifies the user of the response result and, if approved, assists with further purchase procedures.

[1952] (Application example 2)

[1953] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1954] Conventional user-designer matching systems lack the ability to provide personalized suggestions that fully reflect a user's individual tastes and emotions. As a result, users spend a long time finding their ideal design, and designers have limited opportunities to offer their work to the right users. Furthermore, especially when providing immersive experiences such as virtual stores, a system that reflects user emotions in real time and makes design discovery easier and seamless is needed.

[1955] 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.

[1956] In this invention, the server includes: means for users to register personal information through various input forms; means for transmitting the registered information to the server and saving it in a database; means for verifying registered user information and performing authentication; means for designers to upload design works and input metadata about the works (e.g., title, description, tags, etc.); means for transmitting the design works and their metadata to the server and saving them in the database; means for users to input search queries and send them to the server; means for the server to search for related designs from the database and perform AI analysis to generate proposals based on the user's tastes and preferences; means for displaying the search results and proposed design works to the user; means for acquiring emotional data from the user's reactions and facial expressions using an emotion analysis device; means for transmitting the acquired emotional data to the server and combining it with AI analysis to provide personalized design proposals to the user; and means for users to issue purchase requests and notify designers of the requests. This enables personalized proposals in real time based on the user's emotions, making it easier for users to efficiently find their ideal designs and increasing designers' opportunities to provide their works to appropriate users.

[1957] "User" means an individual or corporation that uses the System to search for and purchase design works.

[1958] "Designer" means an individual or legal entity responsible for uploading design works to the system.

[1959] "Server" refers to a computer system that receives data sent by users and designers, and stores and manages the data in a database.

[1960] A "database" is a system connected to a server for systematically storing and managing user information and metadata of design works.

[1961] "Metadata" refers to additional information such as title, description, and tags associated with a design work.

[1962] An "emotion analysis device" is a device that captures and analyzes emotional data from a user's reactions and facial expressions.

[1963] "Emotion data" is user emotion information acquired by the emotion analysis device.

[1964] "AI analysis" is the process of using artificial intelligence technology to analyze users' tastes, preferences, and emotional data and generate suggestions.

[1965] "Personalized proposals" are proposals for customized design works based on the user's individual tastes, preferences, and emotional data.

[1966] A "Purchase Request" is a request by a User to express their intent to purchase a particular Design Work.

[1967] A "notification" is a message that conveys information from the server to the designer or user.

[1968] This system is a comprehensive platform that allows users to efficiently search and purchase design works and allows designers to deliver their works to the right customers. Specific embodiments are described below.

[1969] User Registration

[1970] First, the user accesses the system and enters personal information such as name, email address, and password on the new registration page. The terminal sends this information to the server, which stores the received information in a database. If registration is successful, the terminal displays a registration success message to the user.

[1971] Upload your design

[1972] Next, the designer uploads their design. The designer enters metadata such as the image file, title, description, and tags of the work and uploads it. The device temporarily saves this information, checks the format and content, and then sends it to the server. The server saves the received information in a database and returns a message to the device indicating that the save was successful, displaying a message to the designer indicating that the listing was successful.

[1973] Sentiment analysis and AI suggestions

[1974] When a user searches for a design work, they access the search screen and enter a search query. The device sends the entered search query to the server, which then searches for and extracts relevant design works from a database. The server then collects the user's past search history, purchase history, and browsing history and performs AI analysis. An emotion analyzer (such as OpenCV or Face API) obtains emotional data from the user's reactions and facial expressions and sends that data to the server. The server combines this data and uses a deep learning framework (such as TensorFlow or PyTorch) to generate optimal suggestions based on the user's preferences and tastes, which are then displayed to the user along with the search results.

[1975] Purchase Process

[1976] When a user wants to purchase a specific design piece, they press the "Purchase Request" button on the details page. The device sends the purchase request information (user information, piece information) to the server. The server notifies the designer of the request, and the designer responds in real time using Firebase Cloud Messaging. When the server receives a response from the designer (approval or rejection), it notifies the user of the result.

[1977] Specific examples

[1978] As a concrete example, when a user searches for "modern designer house," the server searches the database for related design works and uses AI analysis and an emotion engine to make optimal suggestions based on the user's past history and reactions. For example, if the emotion engine recognizes an "interest" in a design work that the user is looking at with interest, it will recommend designs similar to that work. Multiple design works are displayed to the user as search results. If the user likes one of them and submits a purchase request, the designer is notified, and the deal is concluded after the designer's approval.

[1979] Prompt Sentence Examples

[1980] "I'm looking for a modern designer home. I'm looking for a design similar to the urban interiors I've seen in the past. Also, please use sentiment analysis to suggest which design would be best for me."

[1981] The above is a concrete example of how the present invention can be implemented. Users can efficiently find their ideal design work through real-time suggestions based on their emotions, and designers can have the opportunity to provide their work to the right users.

[1982] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1983] Step 1:

[1984] The user enters personal information (name, email address, password, etc.) on the new registration page.

[1985] Input: The user enters personal information.

[1986] Data processing: The terminal sends these data to the server.

[1987] Output: The server stores the received information in a database and displays a registration success message on the terminal.

[1988] Step 2:

[1989] Designers upload their design work and enter the work's metadata (image file, title, description, tags, etc.).

[1990] Input: Designers input design work and metadata.

[1991] Data processing: The device temporarily stores this data and checks its format and content.

[1992] Output: Sent to server and saved in database. A message of successful saving is displayed in the designer.

[1993] Step 3:

[1994] A user enters a search query to search for design work.

[1995] Input: The user types a search query.

[1996] Data processing: The terminal sends the entered search query to the server, which then searches and extracts relevant design works from the database.

[1997] Output: The relevant design work is displayed to the user.

[1998] Step 4:

[1999] Using AI and sentiment analysis, suggestions are generated based on the user's tastes and preferences.

[2000] Input: Past search history, purchase history, browsing history, and emotional data obtained from reactions and facial expressions.

[2001] Data processing: The server analyzes the data using deep learning frameworks (TensorFlow, PyTorch) and generates personalized suggestions.

[2002] Output: A list of proposed design works is displayed to the user.

[2003] Step 5:

[2004] The user places a purchase request and notifies the designer of the request.

[2005] Input: User information, work information.

[2006] Data processing: The terminal sends the purchase request information to the server.

[2007] Output: The server notifies the designer of the request.

[2008] Step 6:

[2009] The designer responds to the purchase request.

[2010] Input: Approval or rejection response from the designer.

[2011] Data processing: The server receives the designer's response and notifies the user.

[2012] Output: The user is shown the approval or rejection result.

[2013] Step 7:

[2014] If the deal is successful, the user and designer will proceed with detailed negotiations.

[2015] Input: Opportunity details.

[2016] Data processing: Transaction-related information is stored on the server and updated and managed as necessary.

[2017] Output: A notification of the transaction completion is sent to both parties.

[2018] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2019] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2020] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2021] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2022] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2023] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2024] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2025] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2026] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2027] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2028] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2029] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2030] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2031] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2032] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2033] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2034] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2035] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2036] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2037] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2038] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2039] The following is further disclosed regarding the above embodiment.

[2040] (Claim 1)

[2041] A means for users to register personal information through various input forms,

[2042] A means for transmitting the registered information to a server and storing it in a database;

[2043] A means for verifying registered user information and performing authentication;

[2044] A means for designers to upload their design work and enter metadata about that work (such as title, description, tags, etc.);

[2045] a means for transmitting the design work and its metadata to a server and storing it in a database;

[2046] A means by which a user enters a search query and transmits it to a server;

[2047] The server searches for related designs in the database, analyzes them using AI, and generates suggestions based on the user's tastes and preferences.

[2048] a means for displaying search results and suggested design works to the user;

[2049] A system that includes a means for users to submit purchase requests and notify designers of those requests.

[2050] (Claim 2)

[2051] The system according to claim 1, further comprising a step in which the server collects the user's past search history, purchase history, and browsing history, and identifies the user's preference trends using AI based on this.

[2052] (Claim 3)

[2053] 2. The system of claim 1, wherein the server comprises means for receiving purchase approval or rejection from the designer and notifying the user of the result.

[2054] "Example 1"

[2055] (Claim 1)

[2056] A means for users to register personal information through various input forms,

[2057] A means for transmitting the registered information to a server and storing it in a database;

[2058] A means for verifying registered user information and performing authentication;

[2059] A means for designers to upload their design work and enter metadata about that work (such as title, description, tags, etc.);

[2060] a means for transmitting the design work and its metadata to a server and storing it in a database;

[2061] A means by which a user enters a search query and transmits it to a server;

[2062] The server searches the database for relevant designs and uses a generative AI model to generate suggestions based on the user's preferences;

[2063] a means for displaying search results and suggested design works to the user;

[2064] A means for the User to issue a purchase request and notify the Designer of that request;

[2065] A means to receive purchase approval or rejection from the Designer and notify the User of the result;

[2066] A system including:

[2067] (Claim 2)

[2068] The system of claim 1 further comprises a step in which the server collects the user's past search history, purchase history, and browsing history, and based on this, identifies the user's preference trends using a generative AI model.

[2069] (Claim 3)

[2070] 2. The system of claim 1, wherein the server comprises means for receiving purchase approval or rejection from the designer and notifying the user of the result.

[2071] "Application Example 1"

[2072] (Claim 1)

[2073] A means for users to register personal information through various input forms,

[2074] A means for transmitting the registered information to a server and storing it in a database;

[2075] A means for verifying registered user information and performing authentication;

[2076] A means for designers to upload their design work and enter metadata about that work (e.g., title, description, tags, etc.);

[2077] a means for transmitting the design work and its metadata to a server and storing it in a database;

[2078] A means by which a user enters a search query and transmits it to a server;

[2079] The server searches for related designs in the database, analyzes them using AI, and generates suggestions based on the user's tastes and preferences.

[2080] a means for displaying search results and suggested design works to the user;

[2081] a means for users to issue purchase requests and notify the designer of such requests;

[2082] A means for a user to read a two-dimensional code associated with the item;

[2083] means for displaying metadata and purchase options for the target item based on the read two-dimensional code;

[2084] A system including:

[2085] (Claim 2)

[2086] The system according to claim 1, further comprising a step in which the server collects the user's past search history, purchase history, and browsing history, and identifies the user's preference trends using AI based on this.

[2087] (Claim 3)

[2088] 2. The system according to claim 1, wherein the server comprises means for receiving purchase approval or rejection from the designer and notifying the user of the result.

[2089] "Example 2: Combining Emotion Engines"

[2090] (Claim 1)

[2091] A means for users to register personal information through various input forms,

[2092] A means for transmitting the registered information to a server and storing it in a database;

[2093] A means for verifying registered user information and performing authentication;

[2094] A means for designers to upload their design work and enter metadata about that work (such as title, description, tags, etc.);

[2095] a means for transmitting the design work and its metadata to a server and storing it in a database;

[2096] A means by which a user enters a search query and transmits it to a server;

[2097] The server searches for related designs in the database, analyzes them using AI, and generates suggestions based on the user's tastes and preferences.

[2098] a means for displaying search results and suggested design works to the user;

[2099] A means for the User to issue a purchase request and notify the Designer of that request;

[2100] A means for acquiring user emotion data and transmitting it to a server;

[2101] A system that includes a means for the server to analyze the user's emotional data and reflect this in the generation of proposed works.

[2102] (Claim 2)

[2103] The system according to claim 1, further comprising a step in which the server collects the user's past search history, purchase history, browsing history and emotional data, and identifies the user's preference trends using AI based on this data.

[2104] (Claim 3)

[2105] 2. The system of claim 1, wherein the server comprises means for receiving purchase approval or rejection from the designer and notifying the user of the result.

[2106] "Application example 2 when combining emotion engines"

[2107] (Claim 1)

[2108] A means for users to register personal information through various input forms,

[2109] A means for transmitting the registered information to a server and storing it in a database;

[2110] A means for verifying registered user information and performing authentication;

[2111] A means for designers to upload their design work and enter metadata about that work (such as title, description, tags, etc.);

[2112] a means for transmitting the design work and its metadata to a server and storing it in a database;

[2113] A means by which a user enters a search query and transmits it to a server;

[2114] The server searches for related designs in the database, analyzes them using AI, and generates suggestions based on the user's tastes and preferences.

[2115] a means for displaying search results and suggested design works to the user;

[2116] A means for acquiring emotional data from a user's reactions and facial expressions using an emotion analyzer;

[2117] The acquired emotional data is sent to a server and combined with AI analysis to provide personalized design suggestions to users.

[2118] A system that includes a means for users to submit purchase requests and notify designers of those requests.

[2119] (Claim 2)

[2120] The system according to claim 1, further comprising a step in which the server collects the user's past search history, purchase history, browsing history and emotional data, and identifies the user's preference trends using AI based on this data.

[2121] (Claim 3)

[2122] 2. The system of claim 1, wherein the server comprises means for receiving purchase approval or rejection from the designer and notifying the user of the result. [Explanation of symbols]

[2123] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for users to register personal information through various input forms, A means for transmitting the registered information to a server and storing it in a database; A means for verifying registered user information and performing authentication; a means for designers to upload design work and enter metadata about that work; a means for transmitting the design work and its metadata to a server and storing it in a database; A means by which a user enters a search query and transmits it to a server; The server searches for related designs in the database, analyzes them using AI, and generates suggestions based on the user's tastes and preferences. a means for displaying search results and suggested design works to the user; and a means for a user to issue a purchase request and notify the designer of the request.

2. The system according to claim 1, further comprising a step in which the server collects the user's past search history, purchase history, and browsing history, and identifies the user's preference trends using AI based on this.

3. 2. The system of claim 1, wherein the server comprises means for receiving purchase approval or rejection from the designer and notifying the user of the result.

Images