system

Abstract

Provide a system. A means for a user to input keywords and multiple conditions; A means for transmitting input data from the terminal to a server; a means by which the server receives the data and searches the database; A means for the server to generate candidates and return them to the terminal; The system includes a means for the terminal to display the results to the user.

Description

[Technical Field]

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

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

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

[0004] In conventional online shopping, users had to manually search and select from a huge list of products to find the outfit they wanted, which required a lot of time and effort. Furthermore, there was a lack of an efficient way to search and display only the products that met the user's desired criteria. This resulted in a poor user experience and discouraged purchases. [Means for solving the problem]

[0005] The present invention solves the above problems by providing a system in which a user inputs keywords and multiple conditions, and a server searches a database based on the input to generate and provide optimal product candidates. Specifically, the system includes the following means, enabling users to efficiently find the outfits they desire.

[0006] 1. A means for users to enter keywords and multiple criteria.

[0007] 2. A means by which the terminal transmits input data to the server.

[0008] 3. The means by which the server receives data and searches the database.

[0009] 4. A means by which the server generates candidates and sends them back to the terminal.

[0010] 5. The means by which the device displays the results to the user.

[0011] This will enable users to find the outfits they want quickly and efficiently, improving the online shopping user experience.

[0012] "User" refers to a consumer who uses the System to shop online.

[0013] "Keywords" refer to search words or phrases that users enter to identify the style or product they desire.

[0014] "Conditions" refer to the budget, color, style, and other options that users specify to filter search results.

[0015] "Terminal" refers to electronic devices operated by users, such as personal computers, smartphones, and tablets.

[0016] "Server" refers to the central system that receives and processes data sent from user terminals and searches the database.

[0017] "Database" refers to a computer system that holds product information, inventory information, and associated metadata.

[0018] "SQL query" refers to a standardized query language for performing search, insert, update, and delete operations on a database.

[0019] "HTML Content" refers to the markup language that organizes the text, images, and other information displayed to users on a web page.

[0020] "Coordination suggestions" refer to relevant products and combinations generated by the server based on keywords and conditions entered by the user. [Brief explanation of the drawings]

[0021] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0022] 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.

[0023] First, the terms used in the following description will be explained.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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."

[0029] [First embodiment]

[0030] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0031] 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.

[0032] 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).

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] 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."

[0042] In order to implement the present invention, cooperation between the user, the terminal, and the server is important. The specific mechanism of the invention is as follows.

[0043] User operations

[0044] Users first access an online shopping site and enter keywords related to the outfit they are looking for in a designated input field. They also select criteria such as budget, color, and style from checkboxes and drop-down menus. This process aggregates information that conveys the user's intentions and preferences to the system.

[0045] Terminal handling

[0046] The device retrieves the keywords entered by the user and the conditions selected. The retrieved data is converted into JSON format and sent to the server. The data is sent to the server using an HTTP POST request. At this stage, the information entered by the user is preserved and passed to the server.

[0047] Server receives and searches data

[0048] The server receives the request sent from the device. It parses the received JSON data and extracts filter criteria such as keywords, budget, color, and style. The server then uses these criteria to construct an SQL query to search for matching items in the database. The SQL query is executed against the database, which contains product information, inventory information, and associated metadata.

[0049] Generating and submitting search results

[0050] Based on the data returned as search results, the server generates coordination candidates. For each item, it creates detailed information that matches the user's search criteria and builds a candidate list. The constructed candidate list is then converted back to JSON format and sent back to the device.

[0051] Displaying results on a terminal

[0052] The device receives the JSON data returned from the server, analyzes it, and dynamically generates HTML content to display to the user. This allows the user to view a list of products and outfit suggestions that match the search criteria.

[0053] Specific examples

[0054] For example, if a user enters the keyword "casual," a budget of 5,000 yen, color "blue," and style "simple," the system will operate as follows:

[0055] 1. The user enters conditions such as "casual, budget 5,000 yen, blue, simple."

[0056] 2. The device converts this data into JSON format and sends it to the server.

[0057] 3. The server receives the request and searches the database for the corresponding item.

[0058] 4. The server generates coordination candidates based on the search results and returns them to the device.

[0059] 5. The device will display the returned list of options, allowing the user to browse through them and select the items they like.

[0060] In this way, the present invention allows users to find their desired outfits efficiently in a short time, improving the user experience.

[0061] The processing flow will be explained below.

[0062] Step 1:

[0063] A user visits an online shopping site, enters keywords related to the style they are looking for in a designated input field, and selects criteria such as budget, color, style, etc. from checkboxes and drop-down menus. Once this input is complete, the user clicks the "Search" button.

[0064] Step 2:

[0065] The device receives the keywords and selected conditions entered by the user, and converts the data into JSON format.

[0066] Step 3:

[0067] The device prepares an HTTP POST request with the generated JSON data as its content. The HTTP request includes the keywords and conditions entered by the user. Once ready, the request is sent to the server.

[0068] Step 4:

[0069] The server receives the HTTP POST request from the device, parses the JSON data from the request, and extracts filter conditions such as keywords, budget, color, and style.

[0070] Step 5:

[0071] The server constructs an SQL query for searching the database based on the extracted filter conditions, and the constructed SQL query is for obtaining the corresponding product information.

[0072] Step 6:

[0073] The server executes the constructed SQL query against the database, which returns items that match the specified criteria.

[0074] Step 7:

[0075] The server generates outfit suggestions that match the user's criteria based on the search results returned from the database, and the generated list of suggestions is converted back into JSON format.

[0076] Step 8:

[0077] The server prepares an HTTP response containing the generated JSON data, and when ready, sends the HTTP response to the terminal.

[0078] Step 9:

[0079] The device receives the HTTP response sent from the server, parses the JSON data from the response, and dynamically generates HTML content to display the results to the user.

[0080] Step 10:

[0081] Users can view a list of possible outfits displayed on their device, select the items they want, and access the details page to complete the purchase.

[0082] Example 1

[0083] 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."

[0084] Currently, there are systems that allow users to efficiently search for and coordinate products that suit their preferences, but these systems have problems such as being complex and difficult to use, or the search results do not meet the user's expectations.The purpose of this invention is to provide a system that can quickly and easily present optimal coordination candidates based on the user's intentions.

[0085] 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.

[0086] In this invention, the server includes means for analyzing received data and extracting filter conditions, means for searching a database based on the filter conditions, and means for generating outfit candidates based on the search results, thereby enabling the efficient generation and provision of products and outfit candidates that are optimal for the keywords and conditions entered by the user.

[0087] "User" refers to a person who uses the system to search for and coordinate products.

[0088] "Keywords" refer to specific words or phrases that users enter when searching for products or outfits.

[0089] "Conditions" are multiple options that users specify when coordinating outfits or searching for products, and include budget, color, style, etc.

[0090] "Terminal" refers to the electronic device that a user actually uses to access the system, including a personal computer or smartphone.

[0091] A "server" refers to a central computer that processes data and manages databases for a system.

[0092] The "JSON format" is a data exchange format for expressing data in a structured text-based format.

[0093] An "HTTP POST request" is a protocol for a client to send data to a server, and is used to add data to a specific resource.

[0094] "Filter conditions" are specific conditions necessary for a search that are extracted from the data received and analyzed by the server.

[0095] "Database" refers to an integrated data storage system that stores product information, inventory information, metadata, etc.

[0096] "SQL query" means a statement written in Structured Query Language for manipulating a database.

[0097] "Coordination candidates" refer to combinations of multiple recommended items generated by the server based on conditions entered by the user.

[0098] "HTML content" refers to data written in a markup language that constitutes the display content of a web page.

[0099] "Dynamically generated" refers to generating or changing data in real time as the program is executed.

[0100] The detailed description necessary to practice the present invention is provided below.

[0101] User operations

[0102] First, users access an online shopping site. The site provides an input field for entering keywords related to the outfit they are looking for. There are also check boxes and drop-down menus for setting conditions such as budget, color, and style. For example, users can enter the keyword "casual" and conditions such as "budget 5,000 yen," "blue," and "simple."

[0103] Terminal handling

[0104] The device receives keywords and multiple conditions entered by the user. This data is converted to JSON format using a script such as JavaScript®. The device then sends this JSON data to the server using an HTTP POST request. Examples of technologies used include a web browser, a mobile application, or JavaScript.

[0105] Data reception and analysis by the server

[0106] The server receives the HTTP POST request sent from the device, parses the received JSON data, and extracts filter conditions such as keywords ("casual"), budget ("5,000 yen"), color ("blue"), and style ("simple"). Backend technologies such as Python and Node.js are used for this analysis.

[0107] Database search by server

[0108] The server generates an SQL query based on the extracted filter conditions and searches the database. For example, using a database management system such as MySQL, the following SQL query can be constructed:

[0109] sql

[0110] SELECT FROM products WHERE category = 'casual' AND price <= 5000 AND color = 'blue' AND style = 'simple';

[0111] The query searches for matching product information, inventory information, and metadata.

[0112] Server generates and sends search results

[0113] The server generates outfit suggestions that match the user's search criteria based on the results retrieved from the database, adds detailed information about each item (product name, price, color, style, stock status, etc.), converts it into JSON format, and sends it back to the device.

[0114] Displaying results on a terminal

[0115] The device receives the JSON data returned from the server. The received data is parsed using JavaScript and dynamically generates HTML content. For example, the following product information is displayed:

[0116] html

[0117]

[0118] <h2> Blue Casual Shirt< / h2>

[0119] Price: 4,000 yen

[0120] Color: Blue

[0121] Style: Casual

[0122] In stock: 10

[0123]

[0124]

[0125] <h2> Blue Jeans< / h2>

[0126] Price: 3500 yen

[0127] Color: Blue

[0128] Style: Simple

[0129] In stock: 5

[0130]

[0131] Users can choose their favorite items from the displayed items.

[0132] Examples of concrete examples and prompts

[0133] For example, if a user enters criteria such as "casual, budget 5000 yen, blue, simple", the system will act as follows:

[0134] 1. The user enters conditions such as "casual, budget 5,000 yen, blue, simple."

[0135] 2. The device converts this data into JSON format and sends it to the server using an HTTP POST request.

[0136] 3. The server receives the request and searches the database based on the criteria.

[0137] 4. The server generates coordination candidates based on the search results, converts them into JSON format, and returns them to the device.

[0138] 5. The device parses the JSON data and dynamically generates and displays HTML content.

[0139] An example of an input prompt for a generative AI model would be:

[0140] The user has entered conditions such as "casual, budget 5000 yen, blue, simple." Please search for outfit candidates that match these conditions and return the results.

[0141] In this way, the present invention allows the user to find a desired outfit efficiently in a short time, improving the user experience.

[0142] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0143] System program processing flow

[0144] Step 1:

[0145] A user accesses an online shopping site and enters keywords and multiple conditions (e.g., "casual," "budget 5,000 yen," "blue," "simple"). This aggregates the search conditions. The inputs include keywords, budget, color, and style, and are passed to the device.

[0146] Step 2:

[0147] The device retrieves the data (keywords and conditions) entered by the user. Specifically, it collects form data using a script such as JavaScript. The collected data is structured as follows:

[0148] json

[0149] {

[0150] "keyword": "casual",

[0151] "budget": 5000,

[0152] "color": "blue",

[0153] "style": "simple"

[0154] }

[0155] This acquired data is passed to the terminal as input and then converted to JSON format.

[0156] Step 3:

[0157] The data acquired by the device is converted to JSON format. The JavaScript JSON.stringify method is used for the data conversion. The converted data is output in the following format:

[0158] json

[0159] {

[0160] "keyword": "casual",

[0161] "budget": 5000,

[0162] "color": "blue",

[0163] "style": "simple"

[0164] }

[0165] The converted data is passed to the terminal as input for the HTTP POST request.

[0166] Step 4:

[0167] The device sends JSON data to the server using an HTTP POST request. Specifically, the request is sent using the fetch API or XMLHttpRequest. The input of this step is the converted JSON data, and the output is sent to the server.

[0168] Step 5:

[0169] The server receives an HTTP POST request sent from the device. The received data is in JSON format, and the server parses it. Specifically, it parses the JSON data using a parsing library in Python or Node.js. The input to this step is the JSON data received via the HTTP request, and the parsed filter conditions are output.

[0170] Step 6:

[0171] The server generates an SQL query based on the analyzed filter conditions and searches the database. Specifically, it generates the following query using SQL:

[0172] sql

[0173] SELECT FROM products WHERE category = 'casual' AND price <= 5000 AND color = 'blue' AND style = 'simple';

[0174] It takes filter conditions as input and produces search results retrieved from a database as output.

[0175] Step 7:

[0176] The server retrieves search results from the database and converts the outfit suggestions that match the user's criteria into JSON format. Specifically, it uses Python or Node.js to serialize the structured data into JSON format. The following JSON data is generated as output:

[0177] json

[0178] [

[0179] {

[0180] "product_name": "Blue Casual Shirt",

[0181] "price": 4000,

[0182] "color": "blue",

[0183] "style": "casual",

[0184] "stock": 10

[0185] },

[0186] {

[0187] "product_name": "Blue Jeans",

[0188] "price": 3500,

[0189] "color": "blue",

[0190] "style": "simple",

[0191] "stock": 5

[0192] }

[0193] ]

[0194] The input to this step is a database search result, and the output is transformed JSON data.

[0195] Step 8:

[0196] The server returns the generated JSON data to the terminal as an HTTP response. Specifically, it sets the JSON data in the body of the HTTP response and sends it to the client. The input to this step is the generated JSON data, and it is sent to the terminal as the output.

[0197] Step 9:

[0198] The device receives and parses the JSON data returned from the server. Specifically, it parses the data using the JavaScript JSON.parse method. The received data is input, and the parsed data is output.

[0199] Step 10:

[0200] Dynamically generate HTML content based on the data analyzed by the device. Specifically, JavaScript is used to manipulate the DOM and generate the following HTML:

[0201] html

[0202]

[0203] <h2> Blue Casual Shirt< / h2>

[0204] Price: 4,000 yen

[0205] Color: Blue

[0206] Style: Casual

[0207] In stock: 10

[0208]

[0209]

[0210] <h2> Blue Jeans< / h2>

[0211] Price: 3500 yen

[0212] Color: Blue

[0213] Style: Simple

[0214] In stock: 5

[0215]

[0216] This allows users to visually see search results, with parsed JSON data as input and generated HTML content as output.

[0217] (Application example 1)

[0218] 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."

[0219] Conventional online shopping sites make it difficult for users to quickly find the outfits they want, and are unable to provide optimal suggestions for each individual user. Furthermore, they lack features to improve the user experience, such as voice input and social media sharing. There is a need for a system that can solve these problems and enable users to efficiently find the outfits they want.

[0220] 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.

[0221] In this invention, the server includes means for individually proposing optimal outfits based on past search history and purchase history, means for specifying conditions through voice input, and means for sharing selected outfits on social networking services. This allows users to receive optimal suggestions based on their own preferences and past behavior, allows them to specify conditions more easily through voice input, and further enhances the social experience value by sharing selected items on SNS.

[0222] "User" refers to a person who uses the system to search for outfit suggestions.

[0223] "Keywords" refer to words or phrases related to the outfit the user desires.

[0224] "Conditions" refer to factors such as budget, color, and style that users specify to narrow down their outfits.

[0225] "Terminal" refers to a device, such as a smartphone or computer, that a user uses to access the system.

[0226] The term "server" refers to a remote computer system that receives data sent by a user, searches a database, and generates and returns coordinate candidates.

[0227] "Database" refers to a collection of information that stores product information and metadata.

[0228] An "SQL query" is a query statement used to retrieve specific information from a database.

[0229] "HTML content" refers to content written in a markup language used to define the structure of a web page.

[0230] "Past search history" refers to a record of searches a user has previously conducted.

[0231] "Purchase history" refers to a record of products a user has purchased to date.

[0232] "Voice input" refers to the function that allows the user to specify conditions by voice through a microphone.

[0233] "Social networking service" refers to a platform, such as Facebook or Twitter, that enables users to interact with other users online.

[0234] This invention relates to a system that provides outfit suggestions based on keywords and multiple conditions specified by a user. Specifically, this system includes means for a user to input keywords and conditions such as budget, color, and style, means for a terminal to transmit the input data to a server, means for the server to receive the data and search a database, means for the server to generate suggestions and return them to the terminal, means for the terminal to display the results to the user, means for individually proposing optimal outfits based on past search history and purchase history, means for specifying conditions through voice input, and means for sharing selected outfits on a social networking service.

[0235] Hardware and Software Use

[0236] The server uses server software (e.g., Python Flask) to communicate with the database server and execute SQL queries. The database uses SQLite to store product information and metadata. The terminal uses HTML / CSS / JavaScript to provide a user interface, receives input from the user, converts it into JSON format, and sends it to the server.

[0237] Data processing and calculation

[0238] 1. The user enters keywords and conditions using the terminal.

[0239] Example: "Casual, budget 5000 yen, blue, simple"

[0240] 2. The device converts the input data into JSON format and sends an HTTP POST request to the server.

[0241] 3. The server parses the received JSON data and extracts conditions such as keywords, budget, color, and style.

[0242] 4. The server generates an SQL query based on the extracted conditions and searches for the corresponding product information in the database.

[0243] 5. The server generates coordination candidates based on the search results and returns them to the device in JSON format.

[0244] 6. The device parses the received JSON data and dynamically generates HTML content to display to the user.

[0245] Specific examples

[0246] If a user enters the keyword "casual," a budget of 5,000 yen, color "blue," and style "simple," the results will be as follows.

[0247] 1. The user enters criteria such as "casual, budget 5,000 yen, blue, simple."

[0248] 2. The device converts this data into JSON format and sends it to the server.

[0249] 3. The server receives the request and searches the database for matching products based on the criteria.

[0250] 4. The server generates coordination candidates based on the search results and returns them to the device.

[0251] 5. The device displays the returned candidate list as dynamic HTML content, allowing the user to browse through them and select the items they like.

[0252] An example of a prompt sentence using a generative AI model is, "The user is looking for a simple, casual, blue outfit within a budget of 5,000 yen. Please search the database for matching products and create a list." This allows the server to suggest products that meet the criteria.

[0253] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0254] Step 1:

[0255] The user enters keywords and conditions.

[0256] Input: Keywords (e.g., "casual"), budget (e.g., 5,000 yen), color (e.g., "blue"), style (e.g., "simple")

[0257] Output: User input data

[0258] What it does: The user enters conditions using input fields, checkboxes, drop-down menus, or even voice input. The device captures this data.

[0259] Step 2:

[0260] The terminal converts the input data into JSON format and sends it to the server via an HTTP POST request.

[0261] Input: User-entered data

[0262] Output: JSON format data

[0263] Specific operation: The terminal converts the user's input data into JSON format and sends it to the server using an HTTP POST request. Converting into JSON format improves data integrity and transmission efficiency.

[0264] Step 3:

[0265] The server receives the JSON data and parses the conditions.

[0266] Input: JSON format data

[0267] Output: Conditions (keywords, budget, color, style)

[0268] How it works: The server receives an HTTP request and parses the received JSON data to extract conditions such as keywords, budget, color, style, etc. This is done using the Python json library.

[0269] Step 4:

[0270] The server generates an SQL query based on the criteria and searches the database.

[0271] Input: Conditions (keywords, budget, color, style)

[0272] Output: Matching product information

[0273] Specific operation: The server generates an SQL query based on the extracted conditions and searches the SQLite database. The generated SQL query is executed using an ORM such as SQLAlchemy, which retrieves product information that matches the conditions.

[0274] Step 5:

[0275] The server generates coordination suggestions based on the search results and returns them to the device in JSON format.

[0276] Input: Relevant product information

[0277] Output: Coordinate candidates (JSON format)

[0278] Specific operation: The server creates outfit suggestions based on the search results and converts them back into JSON format. The generated JSON data is sent back to the device as an HTTP response. In this process, past search and purchase history is also taken into consideration.

[0279] Step 6:

[0280] The device parses the returned JSON data, dynamically generates HTML content, and displays it to the user.

[0281] Input: Coordinate candidates (JSON format)

[0282] Output: Dynamically generated HTML content

[0283] How it works: The device parses the JSON data received from the server and dynamically displays outfit suggestions using HTML / CSS / JavaScript. Users can browse the results and select their favorite items. Features include suggestions based on past search and purchase history, voice input for specifying search criteria, and the ability to share on social media.

[0284] 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.

[0285] To implement the present invention, cooperation between the user, the terminal, and the server is important. Furthermore, the present invention also incorporates an emotion engine for recognizing the user's emotions. The specific mechanism of the invention is as follows.

[0286] User operations

[0287] Users access an online shopping site, enter keywords related to the outfit they are looking for in designated input fields, and select criteria such as budget, color, and style from checkboxes and drop-down menus. This aggregates information that conveys the user's intentions and preferences to the system.

[0288] Terminal handling

[0289] The device acquires the keywords entered by the user and the conditions selected. The acquired data is converted into JSON format. The device also has a built-in emotion engine that recognizes the user's emotions, recognizing emotions from the user's facial expressions and voice in real time. This emotion data is also included in the JSON format.

[0290] Sending data to the server

[0291] The device prepares an HTTP POST request with the generated JSON data, including the keywords and conditions entered by the user and the recognized emotion data, and then sends the request to the server.

[0292] Server receives and searches data

[0293] The server receives an HTTP POST request from the device. It parses the received JSON data and extracts filter criteria such as keywords, budget, color, and style, as well as user sentiment data. The server then uses these criteria to construct an SQL query to search for matching items in the database. The SQL query is executed against the database, which contains product information, inventory information, and associated metadata.

[0294] Generating and submitting search results

[0295] Based on the data returned as search results, the server generates outfit candidates that match the user's criteria and emotional data. For example, if the user expresses the emotion "fun," the server will prioritize items in colors and styles that match that emotion. The generated candidate list is then converted back to JSON format and sent back to the device.

[0296] Displaying results on a terminal

[0297] The device receives the HTTP response sent from the server, analyzes the JSON data from the response, and dynamically generates HTML content to display the results to the user. This allows the user to view a list of products and outfit suggestions that match the search criteria and their current emotions.

[0298] Specific examples

[0299] For example, if a user selects the keyword "casual," a budget of 5,000 yen, the color "blue," the style "simple," and also indicates the emotion "fun," the system will operate as follows:

[0300] 1. The user enters conditions such as "casual, budget 5,000 yen, blue, simple."

[0301] 2. The emotion engine recognizes the emotion "fun" from the user's facial expression.

[0302] 3. The device converts this data into JSON format and sends it to the server.

[0303] 4. The server receives the request and searches the database for the corresponding item.

[0304] 5. Based on the search results, the server generates coordination candidates that correspond to the user's emotions and returns them to the device.

[0305] 6. The device will display the returned list of options, allowing the user to browse through them and select the items they like.

[0306] In this way, the present invention allows users to efficiently find outfits that suit their emotions, improving the user experience of online shopping.

[0307] The processing flow will be explained below.

[0308] Step 1:

[0309] A user accesses an online shopping site, enters keywords related to the outfit they are looking for in a designated input field, and selects criteria such as budget, color, and style from checkboxes and drop-down menus. Once this input is complete, the user clicks the "Search" button.

[0310] Step 2:

[0311] The device acquires the keywords entered by the user and the conditions selected. The acquired data is converted into JSON format. The device also has a built-in emotion engine that recognizes the user's emotions, recognizing emotions from the user's facial expressions and voice in real time. This emotion data is also included in the JSON format.

[0312] Step 3:

[0313] The device prepares an HTTP POST request with the generated JSON data as its content. The HTTP request includes the keywords and conditions entered by the user, as well as the recognized emotion data. Once ready, the request is sent to the server.

[0314] Step 4:

[0315] The server receives the HTTP POST request from the device, parses the JSON data from the request, and extracts filter conditions such as keywords, budget, color, and style, as well as user sentiment data.

[0316] Step 5:

[0317] The server constructs an SQL query to search the database based on the extracted filter conditions and emotion data, and the constructed SQL query is used to obtain the relevant product information.

[0318] Step 6:

[0319] The server executes the constructed SQL query against the database, which returns items that match the specified criteria.

[0320] Step 7:

[0321] The server generates outfit suggestions that match the user's criteria and emotional data based on the search results returned from the database. For example, if the user expresses the emotion "fun," it will prioritize items in colors and styles that match that emotion. The generated candidate list is then converted back into JSON format.

[0322] Step 8:

[0323] The server prepares an HTTP response containing the generated JSON data, and when ready, sends the HTTP response to the terminal.

[0324] Step 9:

[0325] The device receives the HTTP response sent from the server, parses the JSON data from the response, and dynamically generates HTML content to display the results to the user.

[0326] Step 10:

[0327] Users can view a list of possible outfits displayed on their device, select the items they want, and access the details page to complete the purchase.

[0328] Specific examples

[0329] For example, if a user selects the keyword "casual," a budget of 5,000 yen, the color "blue," the style "simple," and also indicates the emotion "fun," the system will operate as follows:

[0330] 1. The user enters conditions such as "casual, budget 5,000 yen, blue, simple."

[0331] 2. The emotion engine recognizes the emotion "fun" from the user's facial expression.

[0332] 3. The device converts this data into JSON format and sends it to the server.

[0333] 4. The server receives the request and searches the database for the corresponding item.

[0334] 5. Based on the search results, the server generates coordination candidates that correspond to the user's emotions and returns them to the device.

[0335] 6. The device will display the returned list of options, allowing the user to browse through them and select the items they like.

[0336] In this way, the present invention allows users to efficiently find outfits that suit their emotions, improving the user experience of online shopping.

[0337] Example 2

[0338] 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."

[0339] Conventional online shopping systems only provide search results based on user input criteria and are unable to display results that reflect the user's real-time emotional state, resulting in a limited user experience and preventing more advanced personalization to improve user satisfaction.

[0340] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0341] In this invention, the server includes means for recognizing emotions from a user's facial expressions and voice in real time using an emotion engine, means for transmitting JSON-formatted data including input data and recognized emotion data to the server, means for the server to receive the data, generate and execute an SQL query for searching a database, and means for generating candidates based on the user's input conditions and emotion data and returning them to the terminal, thereby making it possible to provide personalized search results that reflect the user's real-time emotions.

[0342] "User" means an individual or organization that uses the online shopping site to search for and purchase products.

[0343] A "keyword" is a word or phrase that a user enters as a search condition for a product.

[0344] "Conditions" are information in addition to keywords that narrow down search results, and include budget, color, style, etc.

[0345] A "terminal" is a device operated by a user, such as a computer, smartphone, or tablet.

[0346] "Data" refers to information including keywords and conditions entered by the user, as well as recognized emotional information.

[0347] "Emotion data" is emotional information obtained from the user's facial expressions and voice recognized in real time by the emotion engine.

[0348] The "JSON format" is a lightweight data exchange format for expressing data structures.

[0349] A "server" is a central computer system that receives requests from users and performs processes such as database searches and candidate generation.

[0350] An "SQL query" is a standardized query language for searching and manipulating data in a relational database.

[0351] "Candidates" is a list of product suggestions generated by the server based on the user's input conditions and emotion data.

[0352] "HTML content" refers to a document format for configuring the display content of a web page, and is data that is dynamically generated for displaying the results.

[0353] In order to implement the present invention, cooperation between users, terminals, and servers is essential. How each of these components functions will be described in detail below.

[0354] User operations

[0355] A user first visits an online shopping site, where they enter keywords related to the outfit they are looking for, and then select criteria such as budget, color, and style using checkboxes and drop-down menus. This information plays a key role in identifying the products they are looking for.

[0356] Terminal handling

[0357] The terminal is a device for acquiring keywords and conditions entered by the user. The acquired data is converted into JSON format. Furthermore, the terminal is equipped with an emotion engine (e.g., Microsoft® Azure® Emotion API or Google® Cloud Vision API) for recognizing the user's emotions, and recognizes emotions from the user's facial expressions and voice in real time. This emotion data is also included in the JSON format.

[0358] Sending data to the server

[0359] The device prepares an HTTP POST request with the generated JSON data, including the keywords and conditions entered by the user and the recognized emotion data, and then sends the HTTP request to the server.

[0360] Server receives and searches data

[0361] The server receives the HTTP POST request sent from the device. It parses the received JSON data and extracts filter criteria such as keywords, budget, color, and style, as well as user sentiment data. The server then constructs an SQL query to search the database based on these criteria. The SQL query is executed against the database, which contains product information, inventory information, and associated metadata.

[0362] Generating and submitting search results

[0363] The server generates outfit suggestions that match the user's criteria and emotional data based on the search results. For example, if the user expresses the emotion "fun," the server will prioritize items in colors and styles that match that emotion. The generated candidate list is then converted back to JSON format and sent back to the device.

[0364] Displaying results on a terminal

[0365] The device receives the HTTP response sent from the server, analyzes the JSON data from the response, and dynamically generates HTML content to display the results to the user. This allows the user to view a list of products and outfit suggestions that match the search criteria and their current emotions.

[0366] Specific examples

[0367] For example, if a user selects the keyword "casual," a budget of 5,000 yen, the color "blue," the style "simple," and also indicates the emotion "fun," the system will operate as follows:

[0368] 1. The user enters conditions such as "casual, budget 5,000 yen, blue, simple."

[0369] 2. The emotion engine recognizes the emotion "fun" from the user's facial expression.

[0370] 3. The device converts this data into JSON format and sends it to the server.

[0371] 4. The server receives the request and searches the database for the corresponding item.

[0372] 5. Based on the search results, the server generates coordination candidates that correspond to the user's emotions and returns them to the device.

[0373] 6. The device will display the returned list of options, allowing the user to browse through them and select the items they like.

[0374] Example prompts for generative AI models

[0375] "If a user visits an online shopping site and enters criteria such as 'casual,' 'budget: 5000 yen,' 'color: blue,' and 'style: simple,' and the emotion engine also recognizes the emotion 'fun,' what would happen?"

[0376] In this way, the system of the present invention realizes product search and display that reflects the user's real-time emotions, allowing users to efficiently find outfits that match their emotions and improving the user experience of online shopping.

[0377] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0378] Program processing flow

[0379] Step 1:

[0380] Users access online shopping sites and input and select criteria such as keywords, budget, color, and style to search for outfits. The data input here includes keywords (e.g., "casual"), budget (e.g., "5,000 yen"), color (e.g., "blue"), and style (e.g., "simple").

[0381] Input: Keywords, Budget, Color, Style

[0382] Output: The conditions entered by the user

[0383] Step 2:

[0384] The device receives the keywords and conditions entered by the user, converts this data into JSON format, and uses an emotion engine to recognize emotions from the user's facial expressions and voice in real time, and includes this emotion data in the JSON data. The emotion engine can use, for example, the Microsoft Azure Emotion API or the Google Cloud Vision API.

[0385] Input: User-entered conditions, facial expressions, and voice

[0386] Output: Data converted to JSON format (e.g., {"keyword": "casual", "budget": 5000, "color": "blue", "style": "simple", "emotion": "fun"})

[0387] Step 3:

[0388] The device prepares an HTTP POST request containing the generated JSON data and sends it to the server, which may include header information and an authentication token.

[0389] Input: User criteria and sentiment data in JSON format

[0390] Output: HTTP POST request sent to the server

[0391] Step 4:

[0392] The server receives the HTTP POST request sent from the device and parses the JSON data, extracting keywords, budget, color, style, and sentiment data.

[0393] Input: The received HTTP POST request

[0394] Output: Extracted keywords, budget, color, style, and sentiment data

[0395] Step 5:

[0396] The server generates and executes an SQL query based on the extracted data, such as: SELECT FROM items WHERE style="simple" AND color="blue" AND price <= 5000 AND emotion="fun", to search for matching items in the database.

[0397] Input: Extracted keywords, budget, color, style, sentiment data

[0398] Output: Search results from the database (using SQL queries)

[0399] Step 6:

[0400] The server generates outfit suggestions that match the user's criteria and emotional data based on the search results. The search results are then converted back to JSON format and sent back to the device.

[0401] Input: Search results from the database

[0402] Output: A list of outfit options converted to JSON format (e.g., [{"item": "Blue T-shirt", "price": 3000, "style": "Simple"}])

[0403] Step 7:

[0404] The device parses the HTTP response received from the server, extracts the JSON data, dynamically generates HTML content based on this data, and displays the results to the user.

[0405] Input: Received HTTP response

[0406] Output: Dynamically generated HTML content

[0407] summary

[0408] This process allows users to receive personalized search results based on real-time sentiment, improving the user experience.

[0409] (Application example 2)

[0410] 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."

[0411] Conventional online shopping systems have the problem of limiting the user experience because they do not take into account the emotions or moods of users when they search for products by entering keywords or conditions. Another issue is that it takes time and effort for users to find products and outfits that match their emotions.

[0412] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for searching a database, means for generating candidates and returning them to the terminal, means for converting data including emotion data into JSON format and sending it to the server, and means for analyzing the emotion data and reflecting it in candidate generation. This makes it possible to suggest products based on the user's emotions.

[0413] "User" refers to a person who uses the system to search for and purchase products.

[0414] "Keywords" refers to words or phrases that users enter to specifically express their search intent.

[0415] "Conditions" refer to specific requirements such as budget, color, style, etc. that users specify along with keywords.

[0416] "Device" refers to an electronic device, such as a computer, smartphone, or tablet, that a User uses to access the System.

[0417] "Server" refers to a central management system that receives data sent from the terminal, searches a database, and returns the results to the terminal.

[0418] A "database" refers to a collection of digital information that stores product information, inventory information, and related metadata.

[0419] "Search" refers to the act of retrieving information from a database based on specified conditions.

[0420] "JSON format" is an abbreviation for JavaScript Object Notation, and refers to a lightweight data exchange format for expressing data in an easily structurable form.

[0421] An "HTTP POST request" refers to a request format that uses the HTTP protocol for a client to send data to a server.

[0422] "Emotion engine" refers to a software module that recognizes and analyzes user emotions in real time.

[0423] "Suggestions" refers to a list of products and outfits suggested based on the conditions and emotions entered by the user.

[0424] "HTML content" refers to information written in a markup language that makes up a web page.

[0425] To implement this invention, cooperation between the user, the terminal, and the server is essential. The user first accesses the online shopping system and enters keywords related to the product they are looking for, as well as conditions such as budget, color, and style, into the input fields on the screen. This communicates the user's intentions and wishes to the system.

[0426] The device receives the keywords and conditions entered by the user and converts this data into JSON format. Furthermore, the device is equipped with an emotion engine that analyzes the user's facial expressions and voice in real time to recognize their emotions. This emotion data is also included in the JSON format. A specific emotion engine that can be used is DeepFace.

[0427] The device sends the generated JSON data to the server as an HTTP POST request. The server receives this request and analyzes the data. The analyzed data includes keywords, conditions, and emotional data. The server searches the database based on this data and generates candidates for relevant products and outfits.

[0428] Specifically, if a user inputs criteria such as "casual," "budget 5,000 yen," "blue," and "simple," and the emotion engine recognizes the emotion "fun" from the user's facial expression, the device converts this data into JSON format and sends it to the server. The server receives the data and searches for matching items in its database. At this time, it also takes the emotional data into consideration and prioritizes items with colors and designs that match the emotion of "fun."

[0429] The server then converts the selected product information back into JSON format and sends it back to the device. The device then receives this data, dynamically generates HTML content, and displays the results to the user, allowing the user to easily find products and outfits that match their emotions.

[0430] Examples of prompt sentences include the following:

[0431] "I'm looking for casual fashion items. My budget is under 5,000 yen, the color is blue, and the style is simple. I'm in a fun mood right now, so please suggest products that fit that."

[0432] "I like the color blue and would like to wear something casual and simple. I'm in a fun mood, so please find an outfit that matches that feeling."

[0433] In this way, it becomes possible to suggest products that take the user's emotions into account, improving the online shopping user experience.

[0434] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0435] Step 1:

[0436] A user accesses an online shopping system and enters keywords and multiple criteria (budget, color, style, etc.).

[0437] Input: Keywords, Budget, Color, Style

[0438] Output: A data set containing the user's intent and desires

[0439] Step 2:

[0440] The device receives data entered by the user and converts it into JSON format. It also uses an emotion engine to recognize emotions from the user's facial expressions and voice in real time.

[0441] Input: User input data, user facial expressions and voice

[0442] Output: JSON format data containing keywords, conditions, and sentiment

[0443] Step 3:

[0444] The device sends the generated JSON data to the server as an HTTP POST request.

[0445] Input: JSON format data

[0446] Output: HTTP POST request to the server

[0447] Step 4:

[0448] The server receives the HTTP POST request sent from the device and parses the JSON data, extracting keywords, conditions, and sentiment data.

[0449] Input: HTTP POST request (JSON format data)

[0450] Output: Parsed data with keywords, terms, and sentiment

[0451] Step 5:

[0452] The server searches the database based on the analyzed data and generates relevant products and outfit suggestions, prioritizing the search results by taking into account the emotional data.

[0453] Input: Parsed data

[0454] Output: Candidate product list

[0455] Step 6:

[0456] The server converts the generated candidate product list back into JSON format and sends it back to the terminal.

[0457] Input: candidate product list

[0458] Output: JSON format candidate product list

[0459] Step 7:

[0460] The terminal parses the JSON data received from the server, dynamically generates HTML content, and displays the results to the user.

[0461] Input: JSON format candidate product list received from the server

[0462] Output: Product list displayed in HTML format

[0463] An example of a specific prompt sentence is, "I'm looking for a casual fashion item. My budget is under 5,000 yen, the color is blue, and the style is simple. I'm in a happy mood right now, so please suggest a product that suits that."

[0464] 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.

[0465] 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.

[0466] 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.

[0467] [Second embodiment]

[0468] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0469] 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.

[0470] 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).

[0471] 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.

[0472] 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.

[0473] 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).

[0474] 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. 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.

[0475] 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.

[0476] 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.

[0477] 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.

[0478] 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.

[0479] 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."

[0480] In order to implement the present invention, cooperation between the user, the terminal, and the server is important. The specific mechanism of the invention is as follows.

[0481] User operations

[0482] Users first access an online shopping site and enter keywords related to the outfit they are looking for in a designated input field. They also select criteria such as budget, color, and style from checkboxes and drop-down menus. This process aggregates information that conveys the user's intentions and preferences to the system.

[0483] Terminal handling

[0484] The device retrieves the keywords entered by the user and the conditions selected. The retrieved data is converted into JSON format and sent to the server. The data is sent to the server using an HTTP POST request. At this stage, the information entered by the user is preserved and passed to the server.

[0485] Server receives and searches data

[0486] The server receives the request sent from the device. It parses the received JSON data and extracts filter criteria such as keywords, budget, color, and style. The server then uses these criteria to construct an SQL query to search for matching items in the database. The SQL query is executed against the database, which contains product information, inventory information, and associated metadata.

[0487] Generating and submitting search results

[0488] Based on the data returned as search results, the server generates coordination candidates. For each item, it creates detailed information that matches the user's search criteria and builds a candidate list. The constructed candidate list is then converted back to JSON format and sent back to the device.

[0489] Displaying results on a terminal

[0490] The device receives the JSON data returned from the server, analyzes it, and dynamically generates HTML content to display to the user. This allows the user to view a list of products and outfit suggestions that match the search criteria.

[0491] Specific examples

[0492] For example, if a user enters the keyword "casual," a budget of 5,000 yen, color "blue," and style "simple," the system will operate as follows:

[0493] 1. The user enters conditions such as "casual, budget 5,000 yen, blue, simple."

[0494] 2. The device converts this data into JSON format and sends it to the server.

[0495] 3. The server receives the request and searches the database for the corresponding item.

[0496] 4. The server generates coordination candidates based on the search results and returns them to the device.

[0497] 5. The device will display the returned list of options, allowing the user to browse through them and select the items they like.

[0498] In this way, the present invention allows users to find their desired outfits efficiently in a short time, improving the user experience.

[0499] The processing flow will be explained below.

[0500] Step 1:

[0501] A user visits an online shopping site, enters keywords related to the style they are looking for in a designated input field, and selects criteria such as budget, color, style, etc. from checkboxes and drop-down menus. Once this input is complete, the user clicks the "Search" button.

[0502] Step 2:

[0503] The device receives the keywords and selected conditions entered by the user, and converts the data into JSON format.

[0504] Step 3:

[0505] The device prepares an HTTP POST request with the generated JSON data as its content. The HTTP request includes the keywords and conditions entered by the user. Once ready, the request is sent to the server.

[0506] Step 4:

[0507] The server receives the HTTP POST request from the device, parses the JSON data from the request, and extracts filter conditions such as keywords, budget, color, and style.

[0508] Step 5:

[0509] The server constructs an SQL query for searching the database based on the extracted filter conditions, and the constructed SQL query is for obtaining the corresponding product information.

[0510] Step 6:

[0511] The server executes the constructed SQL query against the database, which returns items that match the specified criteria.

[0512] Step 7:

[0513] The server generates outfit suggestions that match the user's criteria based on the search results returned from the database, and the generated list of suggestions is converted back into JSON format.

[0514] Step 8:

[0515] The server prepares an HTTP response containing the generated JSON data, and when ready, sends the HTTP response to the terminal.

[0516] Step 9:

[0517] The device receives the HTTP response sent from the server, parses the JSON data from the response, and dynamically generates HTML content to display the results to the user.

[0518] Step 10:

[0519] Users can view a list of possible outfits displayed on their device, select the items they want, and access the details page to complete the purchase.

[0520] Example 1

[0521] 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."

[0522] Currently, there are systems that allow users to efficiently search for and coordinate products that suit their preferences, but these systems have problems such as being complex and difficult to use, or the search results do not meet the user's expectations.The purpose of this invention is to provide a system that can quickly and easily present optimal coordination candidates based on the user's intentions.

[0523] 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.

[0524] In this invention, the server includes means for analyzing received data and extracting filter conditions, means for searching a database based on the filter conditions, and means for generating outfit candidates based on the search results, thereby enabling the efficient generation and provision of products and outfit candidates that are optimal for the keywords and conditions entered by the user.

[0525] "User" refers to a person who uses the system to search for and coordinate products.

[0526] "Keywords" refer to specific words or phrases that users enter when searching for products or outfits.

[0527] "Conditions" are multiple options that users specify when coordinating outfits or searching for products, and include budget, color, style, etc.

[0528] "Terminal" refers to the electronic device that a user actually uses to access the system, including a personal computer or smartphone.

[0529] A "server" refers to a central computer that processes data and manages databases for a system.

[0530] The "JSON format" is a data exchange format for expressing data in a structured text-based format.

[0531] An "HTTP POST request" is a protocol for a client to send data to a server, and is used to add data to a specific resource.

[0532] "Filter conditions" are specific conditions necessary for a search that are extracted from the data received and analyzed by the server.

[0533] "Database" refers to an integrated data storage system that stores product information, inventory information, metadata, etc.

[0534] "SQL query" means a statement written in Structured Query Language for manipulating a database.

[0535] "Coordination candidates" refer to combinations of multiple recommended items generated by the server based on conditions entered by the user.

[0536] "HTML content" refers to data written in a markup language that constitutes the display content of a web page.

[0537] "Dynamically generated" refers to generating or changing data in real time as the program is executed.

[0538] The detailed description necessary to practice the present invention is provided below.

[0539] User operations

[0540] First, users access an online shopping site. The site provides an input field for entering keywords related to the outfit they are looking for. There are also check boxes and drop-down menus for setting conditions such as budget, color, and style. For example, users can enter the keyword "casual" and conditions such as "budget 5,000 yen," "blue," and "simple."

[0541] Terminal handling

[0542] The device receives keywords and multiple conditions entered by the user. This data is converted to JSON format using a script such as JavaScript. The device then sends this JSON data to the server using an HTTP POST request. The technology used can be, for example, a web browser, a mobile application, or JavaScript.

[0543] Data reception and analysis by the server

[0544] The server receives the HTTP POST request sent from the device, parses the received JSON data, and extracts filter conditions such as keywords ("casual"), budget ("5,000 yen"), color ("blue"), and style ("simple"). Backend technologies such as Python and Node.js are used for this analysis.

[0545] Database search by server

[0546] The server generates an SQL query based on the extracted filter conditions and searches the database. For example, using a database management system such as MySQL, you can construct an SQL query like this:

[0547] sql

[0548] SELECT FROM products WHERE category = 'casual' AND price <= 5000 AND color = 'blue' AND style = 'simple';

[0549] The query searches for matching product information, inventory information, and metadata.

[0550] Server generates and sends search results

[0551] The server generates outfit suggestions that match the user's search criteria based on the results retrieved from the database, adds detailed information about each item (product name, price, color, style, stock status, etc.), converts it into JSON format, and sends it back to the device.

[0552] Displaying results on a terminal

[0553] The device receives the JSON data returned from the server. The received data is parsed using JavaScript and dynamically generates HTML content. For example, the following product information is displayed:

[0554] html

[0555]

[0556] <h2> Blue Casual Shirt< / h2>

[0557] Price: 4,000 yen

[0558] Color: Blue

[0559] Style: Casual

[0560] In stock: 10

[0561]

[0562]

[0563] <h2> Blue Jeans< / h2>

[0564] Price: 3500 yen

[0565] Color: Blue

[0566] Style: Simple

[0567] In stock: 5

[0568]

[0569] Users can choose their favorite items from the displayed items.

[0570] Examples of concrete examples and prompts

[0571] For example, if a user enters criteria such as "casual, budget 5000 yen, blue, simple", the system will act as follows:

[0572] 1. The user enters conditions such as "casual, budget 5,000 yen, blue, simple."

[0573] 2. The device converts this data into JSON format and sends it to the server using an HTTP POST request.

[0574] 3. The server receives the request and searches the database based on the criteria.

[0575] 4. The server generates coordination candidates based on the search results, converts them into JSON format, and returns them to the device.

[0576] 5. The device parses the JSON data and dynamically generates and displays HTML content.

[0577] An example of an input prompt for a generative AI model would be:

[0578] The user has entered conditions such as "casual, budget 5000 yen, blue, simple." Please search for outfit candidates that match these conditions and return the results.

[0579] In this way, the present invention allows the user to find a desired outfit efficiently in a short time, improving the user experience.

[0580] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0581] System program processing flow

[0582] Step 1:

[0583] A user accesses an online shopping site and enters keywords and multiple conditions (e.g., "casual," "budget 5,000 yen," "blue," "simple"). This aggregates the search conditions. The inputs include keywords, budget, color, and style, and are passed to the device.

[0584] Step 2:

[0585] The device retrieves the data (keywords and conditions) entered by the user. Specifically, it collects form data using a script such as JavaScript. The collected data is structured as follows:

[0586] json

[0587] {

[0588] "keyword": "casual",

[0589] "budget": 5000,

[0590] "color": "blue",

[0591] "style": "simple"

[0592] }

[0593] This acquired data is passed to the terminal as input and then converted to JSON format.

[0594] Step 3:

[0595] The data acquired by the device is converted to JSON format. The JavaScript JSON.stringify method is used for the data conversion. The converted data is output in the following format:

[0596] json

[0597] {

[0598] "keyword": "casual",

[0599] "budget": 5000,

[0600] "color": "blue",

[0601] "style": "simple"

[0602] }

[0603] The converted data is passed to the terminal as input for the HTTP POST request.

[0604] Step 4:

[0605] The device sends JSON data to the server using an HTTP POST request. Specifically, the request is sent using the fetch API or XMLHttpRequest. The input of this step is the converted JSON data, and the output is sent to the server.

[0606] Step 5:

[0607] The server receives an HTTP POST request sent from the device. The received data is in JSON format, and the server parses it. Specifically, it parses the JSON data using a parsing library in Python or Node.js. The input to this step is the JSON data received via the HTTP request, and the parsed filter conditions are output.

[0608] Step 6:

[0609] The server generates an SQL query based on the analyzed filter conditions and searches the database. Specifically, it generates the following query using SQL:

[0610] sql

[0611] SELECT FROM products WHERE category = 'casual' AND price <= 5000 AND color = 'blue' AND style = 'simple';

[0612] It takes filter conditions as input and produces search results retrieved from a database as output.

[0613] Step 7:

[0614] The server retrieves search results from the database and converts the outfit suggestions that match the user's criteria into JSON format. Specifically, it uses Python or Node.js to serialize the structured data into JSON format. The following JSON data is generated as output:

[0615] json

[0616] [

[0617] {

[0618] "product_name": "Blue Casual Shirt",

[0619] "price": 4000,

[0620] "color": "blue",

[0621] "style": "casual",

[0622] "stock": 10

[0623] },

[0624] {

[0625] "product_name": "Blue Jeans",

[0626] "price": 3500,

[0627] "color": "blue",

[0628] "style": "simple",

[0629] "stock": 5

[0630] }

[0631] ]

[0632] The input to this step is a database search result, and the output is transformed JSON data.

[0633] Step 8:

[0634] The server returns the generated JSON data to the terminal as an HTTP response. Specifically, it sets the JSON data in the body of the HTTP response and sends it to the client. The input to this step is the generated JSON data, and it is sent to the terminal as the output.

[0635] Step 9:

[0636] The device receives and parses the JSON data returned from the server. Specifically, it parses the data using the JavaScript JSON.parse method. The received data is input, and the parsed data is output.

[0637] Step 10:

[0638] Dynamically generate HTML content based on the data analyzed by the device. Specifically, JavaScript is used to manipulate the DOM and generate the following HTML:

[0639] html

[0640]

[0641] <h2> Blue Casual Shirt< / h2>

[0642] Price: 4,000 yen

[0643] Color: Blue

[0644] Style: Casual

[0645] In stock: 10

[0646]

[0647]

[0648] <h2> Blue Jeans< / h2>

[0649] Price: 3500 yen

[0650] Color: Blue

[0651] Style: Simple

[0652] In stock: 5

[0653]

[0654] This allows users to visually see search results, with parsed JSON data as input and generated HTML content as output.

[0655] (Application example 1)

[0656] 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."

[0657] Conventional online shopping sites make it difficult for users to quickly find the outfits they want, and are unable to provide optimal suggestions for each individual user. Furthermore, they lack features to improve the user experience, such as voice input and social media sharing. There is a need for a system that can solve these problems and enable users to efficiently find the outfits they want.

[0658] 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.

[0659] In this invention, the server includes means for individually proposing optimal outfits based on past search history and purchase history, means for specifying conditions through voice input, and means for sharing selected outfits on social networking services. This allows users to receive optimal suggestions based on their own preferences and past behavior, allows them to specify conditions more easily through voice input, and further enhances the social experience value by sharing selected items on SNS.

[0660] "User" refers to a person who uses the system to search for outfit suggestions.

[0661] "Keywords" refer to words or phrases related to the outfit the user desires.

[0662] "Conditions" refer to factors such as budget, color, and style that users specify to narrow down their outfits.

[0663] "Terminal" refers to a device, such as a smartphone or computer, that a user uses to access the system.

[0664] The term "server" refers to a remote computer system that receives data sent by a user, searches a database, and generates and returns coordinate candidates.

[0665] "Database" refers to a collection of information that stores product information and metadata.

[0666] An "SQL query" is a query statement used to retrieve specific information from a database.

[0667] "HTML content" refers to content written in a markup language used to define the structure of a web page.

[0668] "Past search history" refers to a record of searches a user has previously conducted.

[0669] "Purchase history" refers to a record of products a user has purchased to date.

[0670] "Voice input" refers to the function that allows the user to specify conditions by voice through a microphone.

[0671] "Social networking service" refers to a platform, such as Facebook or Twitter, that enables users to interact with other users online.

[0672] This invention relates to a system that provides outfit suggestions based on keywords and multiple conditions specified by a user. Specifically, this system includes means for a user to input keywords and conditions such as budget, color, and style, means for a terminal to transmit the input data to a server, means for the server to receive the data and search a database, means for the server to generate suggestions and return them to the terminal, means for the terminal to display the results to the user, means for individually proposing optimal outfits based on past search history and purchase history, means for specifying conditions through voice input, and means for sharing selected outfits on a social networking service.

[0673] Hardware and Software Use

[0674] The server uses server software (e.g., Python Flask) to communicate with the database server and execute SQL queries. The database uses SQLite to store product information and metadata. The terminal uses HTML / CSS / JavaScript to provide a user interface, receives input from the user, converts it into JSON format, and sends it to the server.

[0675] Data processing and calculation

[0676] 1. The user enters keywords and conditions using the terminal.

[0677] Example: "Casual, budget 5000 yen, blue, simple"

[0678] 2. The device converts the input data into JSON format and sends an HTTP POST request to the server.

[0679] 3. The server parses the received JSON data and extracts conditions such as keywords, budget, color, and style.

[0680] 4. The server generates an SQL query based on the extracted conditions and searches for the corresponding product information in the database.

[0681] 5. The server generates coordination candidates based on the search results and returns them to the device in JSON format.

[0682] 6. The device parses the received JSON data and dynamically generates HTML content to display to the user.

[0683] Specific examples

[0684] If a user enters the keyword "casual," a budget of 5,000 yen, color "blue," and style "simple," the results will be as follows.

[0685] 1. The user enters criteria such as "casual, budget 5,000 yen, blue, simple."

[0686] 2. The device converts this data into JSON format and sends it to the server.

[0687] 3. The server receives the request and searches the database for matching products based on the criteria.

[0688] 4. The server generates coordination candidates based on the search results and returns them to the device.

[0689] 5. The device displays the returned candidate list as dynamic HTML content, allowing the user to browse through them and select the items they like.

[0690] An example of a prompt sentence using a generative AI model is, "The user is looking for a simple, casual, blue outfit within a budget of 5,000 yen. Please search the database for matching products and create a list." This allows the server to suggest products that meet the criteria.

[0691] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0692] Step 1:

[0693] The user enters keywords and conditions.

[0694] Input: Keywords (e.g., "casual"), budget (e.g., 5,000 yen), color (e.g., "blue"), style (e.g., "simple")

[0695] Output: User input data

[0696] What it does: The user enters conditions using input fields, checkboxes, drop-down menus, or even voice input. The device captures this data.

[0697] Step 2:

[0698] The terminal converts the input data into JSON format and sends it to the server via an HTTP POST request.

[0699] Input: User-entered data

[0700] Output: JSON format data

[0701] Specific operation: The terminal converts the user's input data into JSON format and sends it to the server using an HTTP POST request. Converting into JSON format improves data integrity and transmission efficiency.

[0702] Step 3:

[0703] The server receives the JSON data and parses the conditions.

[0704] Input: JSON format data

[0705] Output: Conditions (keywords, budget, color, style)

[0706] How it works: The server receives an HTTP request and parses the received JSON data to extract conditions such as keywords, budget, color, style, etc. This is done using the Python json library.

[0707] Step 4:

[0708] The server generates an SQL query based on the criteria and searches the database.

[0709] Input: Conditions (keywords, budget, color, style)

[0710] Output: Matching product information

[0711] Specific operation: The server generates an SQL query based on the extracted conditions and searches the SQLite database. The generated SQL query is executed using an ORM such as SQLAlchemy, which retrieves product information that matches the conditions.

[0712] Step 5:

[0713] The server generates coordination suggestions based on the search results and returns them to the device in JSON format.

[0714] Input: Relevant product information

[0715] Output: Coordinate candidates (JSON format)

[0716] Specific operation: The server creates outfit suggestions based on the search results and converts them back into JSON format. The generated JSON data is sent back to the device as an HTTP response. In this process, past search and purchase history is also taken into consideration.

[0717] Step 6:

[0718] The device parses the returned JSON data, dynamically generates HTML content, and displays it to the user.

[0719] Input: Coordinate candidates (JSON format)

[0720] Output: Dynamically generated HTML content

[0721] How it works: The device parses the JSON data received from the server and dynamically displays outfit suggestions using HTML / CSS / JavaScript. Users can browse the results and select their favorite items. Features include suggestions based on past search and purchase history, voice input for specifying search criteria, and the ability to share on social media.

[0722] 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.

[0723] To implement the present invention, cooperation between the user, the terminal, and the server is important. Furthermore, the present invention also incorporates an emotion engine for recognizing the user's emotions. The specific mechanism of the invention is as follows.

[0724] User operations

[0725] Users access an online shopping site, enter keywords related to the outfit they are looking for in designated input fields, and select criteria such as budget, color, and style from checkboxes and drop-down menus. This aggregates information that conveys the user's intentions and preferences to the system.

[0726] Terminal handling

[0727] The device acquires the keywords entered by the user and the conditions selected. The acquired data is converted into JSON format. The device also has a built-in emotion engine that recognizes the user's emotions, recognizing emotions from the user's facial expressions and voice in real time. This emotion data is also included in the JSON format.

[0728] Sending data to the server

[0729] The device prepares an HTTP POST request with the generated JSON data, including the keywords and conditions entered by the user and the recognized emotion data, and then sends the request to the server.

[0730] Server receives and searches data

[0731] The server receives an HTTP POST request from the device. It parses the received JSON data and extracts filter criteria such as keywords, budget, color, and style, as well as user sentiment data. The server then uses these criteria to construct an SQL query to search for matching items in the database. The SQL query is executed against the database, which contains product information, inventory information, and associated metadata.

[0732] Generating and submitting search results

[0733] Based on the data returned as search results, the server generates outfit candidates that match the user's criteria and emotional data. For example, if the user expresses the emotion "fun," the server will prioritize items in colors and styles that match that emotion. The generated candidate list is then converted back to JSON format and sent back to the device.

[0734] Displaying results on a terminal

[0735] The device receives the HTTP response sent from the server, analyzes the JSON data from the response, and dynamically generates HTML content to display the results to the user. This allows the user to view a list of products and outfit suggestions that match the search criteria and their current emotions.

[0736] Specific examples

[0737] For example, if a user selects the keyword "casual," a budget of 5,000 yen, the color "blue," the style "simple," and also indicates the emotion "fun," the system will operate as follows:

[0738] 1. The user enters conditions such as "casual, budget 5,000 yen, blue, simple."

[0739] 2. The emotion engine recognizes the emotion "fun" from the user's facial expression.

[0740] 3. The device converts this data into JSON format and sends it to the server.

[0741] 4. The server receives the request and searches the database for the corresponding item.

[0742] 5. Based on the search results, the server generates coordination candidates that correspond to the user's emotions and returns them to the device.

[0743] 6. The device will display the returned list of options, allowing the user to browse through them and select the items they like.

[0744] In this way, the present invention allows users to efficiently find outfits that suit their emotions, improving the user experience of online shopping.

[0745] The processing flow will be explained below.

[0746] Step 1:

[0747] A user accesses an online shopping site, enters keywords related to the outfit they are looking for in a designated input field, and selects criteria such as budget, color, and style from checkboxes and drop-down menus. Once this input is complete, the user clicks the "Search" button.

[0748] Step 2:

[0749] The device acquires the keywords entered by the user and the conditions selected. The acquired data is converted into JSON format. The device also has a built-in emotion engine that recognizes the user's emotions, recognizing emotions from the user's facial expressions and voice in real time. This emotion data is also included in the JSON format.

[0750] Step 3:

[0751] The device prepares an HTTP POST request with the generated JSON data as its content. The HTTP request includes the keywords and conditions entered by the user, as well as the recognized emotion data. Once ready, the request is sent to the server.

[0752] Step 4:

[0753] The server receives the HTTP POST request from the device, parses the JSON data from the request, and extracts filter conditions such as keywords, budget, color, and style, as well as user sentiment data.

[0754] Step 5:

[0755] The server constructs an SQL query to search the database based on the extracted filter conditions and emotion data, and the constructed SQL query is used to obtain the relevant product information.

[0756] Step 6:

[0757] The server executes the constructed SQL query against the database, which returns items that match the specified criteria.

[0758] Step 7:

[0759] The server generates outfit suggestions that match the user's criteria and emotional data based on the search results returned from the database. For example, if the user expresses the emotion "fun," it will prioritize items in colors and styles that match that emotion. The generated candidate list is then converted back into JSON format.

[0760] Step 8:

[0761] The server prepares an HTTP response containing the generated JSON data, and when ready, sends the HTTP response to the terminal.

[0762] Step 9:

[0763] The device receives the HTTP response sent from the server, parses the JSON data from the response, and dynamically generates HTML content to display the results to the user.

[0764] Step 10:

[0765] Users can view a list of possible outfits displayed on their device, select the items they want, and access the details page to complete the purchase.

[0766] Specific examples

[0767] For example, if a user selects the keyword "casual," a budget of 5,000 yen, the color "blue," the style "simple," and also indicates the emotion "fun," the system will operate as follows:

[0768] 1. The user enters conditions such as "casual, budget 5,000 yen, blue, simple."

[0769] 2. The emotion engine recognizes the emotion "fun" from the user's facial expression.

[0770] 3. The device converts this data into JSON format and sends it to the server.

[0771] 4. The server receives the request and searches the database for the corresponding item.

[0772] 5. Based on the search results, the server generates coordination candidates that correspond to the user's emotions and returns them to the device.

[0773] 6. The device will display the returned list of options, allowing the user to browse through them and select the items they like.

[0774] In this way, the present invention allows users to efficiently find outfits that suit their emotions, improving the user experience of online shopping.

[0775] Example 2

[0776] 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."

[0777] Conventional online shopping systems only provide search results based on user input criteria and are unable to display results that reflect the user's real-time emotional state, resulting in a limited user experience and preventing more advanced personalization to improve user satisfaction.

[0778] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0779] In this invention, the server includes means for recognizing emotions from a user's facial expressions and voice in real time using an emotion engine, means for transmitting JSON-formatted data including input data and recognized emotion data to the server, means for the server to receive the data, generate and execute an SQL query for searching a database, and means for generating candidates based on the user's input conditions and emotion data and returning them to the terminal, thereby making it possible to provide personalized search results that reflect the user's real-time emotions.

[0780] "User" means an individual or organization that uses the online shopping site to search for and purchase products.

[0781] A "keyword" is a word or phrase that a user enters as a search condition for a product.

[0782] "Conditions" are information in addition to keywords that narrow down search results, and include budget, color, style, etc.

[0783] A "terminal" is a device operated by a user, such as a computer, smartphone, or tablet.

[0784] "Data" refers to information including keywords and conditions entered by the user, as well as recognized emotional information.

[0785] "Emotion data" is emotional information obtained from the user's facial expressions and voice recognized in real time by the emotion engine.

[0786] The "JSON format" is a lightweight data exchange format for expressing data structures.

[0787] A "server" is a central computer system that receives requests from users and performs processes such as database searches and candidate generation.

[0788] An "SQL query" is a standardized query language for searching and manipulating data in a relational database.

[0789] "Candidates" is a list of product suggestions generated by the server based on the user's input conditions and emotion data.

[0790] "HTML content" refers to a document format for configuring the display content of a web page, and is data that is dynamically generated for displaying the results.

[0791] In order to implement the present invention, cooperation between users, terminals, and servers is essential. How each of these components functions will be described in detail below.

[0792] User operations

[0793] A user first visits an online shopping site, where they enter keywords related to the outfit they are looking for, and then select criteria such as budget, color, and style using checkboxes and drop-down menus. This information plays a key role in identifying the products they are looking for.

[0794] Terminal handling

[0795] The terminal is a device for acquiring keywords and conditions entered by the user. The acquired data is converted into JSON format. Furthermore, the terminal is equipped with an emotion engine (e.g., Microsoft Azure Emotion API or Google Cloud Vision API) for recognizing the user's emotions, and recognizes emotions from the user's facial expressions and voice in real time. This emotion data is also included in the JSON format.

[0796] Sending data to the server

[0797] The device prepares an HTTP POST request with the generated JSON data, including the keywords and conditions entered by the user and the recognized emotion data, and then sends the HTTP request to the server.

[0798] Server receives and searches data

[0799] The server receives the HTTP POST request sent from the device. It parses the received JSON data and extracts filter criteria such as keywords, budget, color, and style, as well as user sentiment data. The server then constructs an SQL query to search the database based on these criteria. The SQL query is executed against the database, which contains product information, inventory information, and associated metadata.

[0800] Generating and submitting search results

[0801] The server generates outfit suggestions that match the user's criteria and emotional data based on the search results. For example, if the user expresses the emotion "fun," the server will prioritize items in colors and styles that match that emotion. The generated candidate list is then converted back to JSON format and sent back to the device.

[0802] Displaying results on a terminal

[0803] The device receives the HTTP response sent from the server, analyzes the JSON data from the response, and dynamically generates HTML content to display the results to the user. This allows the user to view a list of products and outfit suggestions that match the search criteria and their current emotions.

[0804] Specific examples

[0805] For example, if a user selects the keyword "casual," a budget of 5,000 yen, the color "blue," the style "simple," and also indicates the emotion "fun," the system will operate as follows:

[0806] 1. The user enters conditions such as "casual, budget 5,000 yen, blue, simple."

[0807] 2. The emotion engine recognizes the emotion "fun" from the user's facial expression.

[0808] 3. The device converts this data into JSON format and sends it to the server.

[0809] 4. The server receives the request and searches the database for the corresponding item.

[0810] 5. Based on the search results, the server generates coordination candidates that correspond to the user's emotions and returns them to the device.

[0811] 6. The device will display the returned list of options, allowing the user to browse through them and select the items they like.

[0812] Example prompts for generative AI models

[0813] "If a user visits an online shopping site and enters criteria such as 'casual,' 'budget: 5000 yen,' 'color: blue,' and 'style: simple,' and the emotion engine also recognizes the emotion 'fun,' what would happen?"

[0814] In this way, the system of the present invention realizes product search and display that reflects the user's real-time emotions, allowing users to efficiently find outfits that match their emotions and improving the user experience of online shopping.

[0815] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0816] Program processing flow

[0817] Step 1:

[0818] Users access online shopping sites and input and select criteria such as keywords, budget, color, and style to search for outfits. The data input here includes keywords (e.g., "casual"), budget (e.g., "5,000 yen"), color (e.g., "blue"), and style (e.g., "simple").

[0819] Input: Keywords, Budget, Color, Style

[0820] Output: The conditions entered by the user

[0821] Step 2:

[0822] The device receives the keywords and conditions entered by the user, converts this data into JSON format, and uses an emotion engine to recognize emotions from the user's facial expressions and voice in real time, and includes this emotion data in the JSON data. The emotion engine can use, for example, the Microsoft Azure Emotion API or the Google Cloud Vision API.

[0823] Input: User-entered conditions, facial expressions, and voice

[0824] Output: Data converted to JSON format (e.g., {"keyword": "casual", "budget": 5000, "color": "blue", "style": "simple", "emotion": "fun"})

[0825] Step 3:

[0826] The device prepares an HTTP POST request containing the generated JSON data and sends it to the server, which may include header information and an authentication token.

[0827] Input: User criteria and sentiment data in JSON format

[0828] Output: HTTP POST request sent to the server

[0829] Step 4:

[0830] The server receives the HTTP POST request sent from the device and parses the JSON data, extracting keywords, budget, color, style, and sentiment data.

[0831] Input: The received HTTP POST request

[0832] Output: Extracted keywords, budget, color, style, and sentiment data

[0833] Step 5:

[0834] The server generates and executes an SQL query based on the extracted data, such as: SELECT FROM items WHERE style="simple" AND color="blue" AND price <= 5000 AND emotion="fun", to search for matching items in the database.

[0835] Input: Extracted keywords, budget, color, style, sentiment data

[0836] Output: Search results from the database (using SQL queries)

[0837] Step 6:

[0838] The server generates outfit suggestions that match the user's criteria and emotional data based on the search results. The search results are then converted back to JSON format and sent back to the device.

[0839] Input: Search results from the database

[0840] Output: A list of outfit options converted to JSON format (e.g., [{"item": "Blue T-shirt", "price": 3000, "style": "Simple"}])

[0841] Step 7:

[0842] The device parses the HTTP response received from the server, extracts the JSON data, dynamically generates HTML content based on this data, and displays the results to the user.

[0843] Input: Received HTTP response

[0844] Output: Dynamically generated HTML content

[0845] summary

[0846] This process allows users to receive personalized search results based on real-time sentiment, improving the user experience.

[0847] (Application example 2)

[0848] 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."

[0849] Conventional online shopping systems have the problem of limiting the user experience because they do not take into account the emotions or moods of users when they search for products by entering keywords or conditions. Another issue is that it takes time and effort for users to find products and outfits that match their emotions.

[0850] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for searching a database, means for generating candidates and returning them to the terminal, means for converting data including emotion data into JSON format and sending it to the server, and means for analyzing the emotion data and reflecting it in candidate generation. This makes it possible to suggest products based on the user's emotions.

[0851] "User" refers to a person who uses the system to search for and purchase products.

[0852] "Keywords" refers to words or phrases that users enter to specifically express their search intent.

[0853] "Conditions" refer to specific requirements such as budget, color, style, etc. that users specify along with keywords.

[0854] "Device" refers to an electronic device, such as a computer, smartphone, or tablet, that a User uses to access the System.

[0855] "Server" refers to a central management system that receives data sent from the terminal, searches a database, and returns the results to the terminal.

[0856] A "database" refers to a collection of digital information that stores product information, inventory information, and related metadata.

[0857] "Search" refers to the act of retrieving information from a database based on specified conditions.

[0858] "JSON format" is an abbreviation for JavaScript Object Notation, and refers to a lightweight data exchange format for expressing data in an easily structurable form.

[0859] An "HTTP POST request" refers to a request format that uses the HTTP protocol for a client to send data to a server.

[0860] "Emotion engine" refers to a software module that recognizes and analyzes user emotions in real time.

[0861] "Suggestions" refers to a list of products and outfits suggested based on the conditions and emotions entered by the user.

[0862] "HTML content" refers to information written in a markup language that makes up a web page.

[0863] To implement this invention, cooperation between the user, the terminal, and the server is essential. The user first accesses the online shopping system and enters keywords related to the product they are looking for, as well as conditions such as budget, color, and style, into the input fields on the screen. This communicates the user's intentions and wishes to the system.

[0864] The device receives the keywords and conditions entered by the user and converts this data into JSON format. Furthermore, the device is equipped with an emotion engine that analyzes the user's facial expressions and voice in real time to recognize their emotions. This emotion data is also included in the JSON format. A specific emotion engine that can be used is DeepFace.

[0865] The device sends the generated JSON data to the server as an HTTP POST request. The server receives this request and analyzes the data. The analyzed data includes keywords, conditions, and emotional data. The server searches the database based on this data and generates candidates for relevant products and outfits.

[0866] Specifically, if a user inputs criteria such as "casual," "budget 5,000 yen," "blue," and "simple," and the emotion engine recognizes the emotion "fun" from the user's facial expression, the device converts this data into JSON format and sends it to the server. The server receives the data and searches for matching items in its database. At this time, it also takes the emotional data into consideration and prioritizes items with colors and designs that match the emotion of "fun."

[0867] The server then converts the selected product information back into JSON format and sends it back to the device. The device then receives this data, dynamically generates HTML content, and displays the results to the user, allowing the user to easily find products and outfits that match their emotions.

[0868] Examples of prompt sentences include the following:

[0869] "I'm looking for casual fashion items. My budget is under 5,000 yen, the color is blue, and the style is simple. I'm in a fun mood right now, so please suggest products that fit that."

[0870] "I like the color blue and would like to wear something casual and simple. I'm in a fun mood, so please find an outfit that matches that feeling."

[0871] In this way, it becomes possible to suggest products that take the user's emotions into account, improving the online shopping user experience.

[0872] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0873] Step 1:

[0874] A user accesses an online shopping system and enters keywords and multiple criteria (budget, color, style, etc.).

[0875] Input: Keywords, Budget, Color, Style

[0876] Output: A data set containing the user's intent and desires

[0877] Step 2:

[0878] The device receives data entered by the user and converts it into JSON format. It also uses an emotion engine to recognize emotions from the user's facial expressions and voice in real time.

[0879] Input: User input data, user facial expressions and voice

[0880] Output: JSON format data containing keywords, conditions, and sentiment

[0881] Step 3:

[0882] The device sends the generated JSON data to the server as an HTTP POST request.

[0883] Input: JSON format data

[0884] Output: HTTP POST request to the server

[0885] Step 4:

[0886] The server receives the HTTP POST request sent from the device and parses the JSON data, extracting keywords, conditions, and sentiment data.

[0887] Input: HTTP POST request (JSON format data)

[0888] Output: Parsed data with keywords, terms, and sentiment

[0889] Step 5:

[0890] The server searches the database based on the analyzed data and generates relevant products and outfit suggestions, prioritizing the search results by taking into account the emotional data.

[0891] Input: Parsed data

[0892] Output: Candidate product list

[0893] Step 6:

[0894] The server converts the generated candidate product list back into JSON format and sends it back to the terminal.

[0895] Input: candidate product list

[0896] Output: JSON format candidate product list

[0897] Step 7:

[0898] The terminal parses the JSON data received from the server, dynamically generates HTML content, and displays the results to the user.

[0899] Input: JSON format candidate product list received from the server

[0900] Output: Product list displayed in HTML format

[0901] An example of a specific prompt sentence is, "I'm looking for a casual fashion item. My budget is under 5,000 yen, the color is blue, and the style is simple. I'm in a happy mood right now, so please suggest a product that suits that."

[0902] 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.

[0903] 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.

[0904] 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.

[0905] [Third embodiment]

[0906] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0907] 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.

[0908] 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).

[0909] 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.

[0910] 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.

[0911] 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).

[0912] 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. 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.

[0913] 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.

[0914] 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.

[0915] 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.

[0916] 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.

[0917] 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."

[0918] In order to implement the present invention, cooperation between the user, the terminal, and the server is important. The specific mechanism of the invention is as follows.

[0919] User operations

[0920] Users first access an online shopping site and enter keywords related to the outfit they are looking for in a designated input field. They also select criteria such as budget, color, and style from checkboxes and drop-down menus. This process aggregates information that conveys the user's intentions and preferences to the system.

[0921] Terminal handling

[0922] The device retrieves the keywords entered by the user and the conditions selected. The retrieved data is converted into JSON format and sent to the server. The data is sent to the server using an HTTP POST request. At this stage, the information entered by the user is preserved and passed to the server.

[0923] Server receives and searches data

[0924] The server receives the request sent from the device. It parses the received JSON data and extracts filter criteria such as keywords, budget, color, and style. The server then uses these criteria to construct an SQL query to search for matching items in the database. The SQL query is executed against the database, which contains product information, inventory information, and associated metadata.

[0925] Generating and submitting search results

[0926] Based on the data returned as search results, the server generates coordination candidates. For each item, it creates detailed information that matches the user's search criteria and builds a candidate list. The constructed candidate list is then converted back to JSON format and sent back to the device.

[0927] Displaying results on a terminal

[0928] The device receives the JSON data returned from the server, analyzes it, and dynamically generates HTML content to display to the user. This allows the user to view a list of products and outfit suggestions that match the search criteria.

[0929] Specific examples

[0930] For example, if a user enters the keyword "casual," a budget of 5,000 yen, color "blue," and style "simple," the system will operate as follows:

[0931] 1. The user enters conditions such as "casual, budget 5,000 yen, blue, simple."

[0932] 2. The device converts this data into JSON format and sends it to the server.

[0933] 3. The server receives the request and searches the database for the corresponding item.

[0934] 4. The server generates coordination candidates based on the search results and returns them to the device.

[0935] 5. The device will display the returned list of options, allowing the user to browse through them and select the items they like.

[0936] In this way, the present invention allows users to find their desired outfits efficiently in a short time, improving the user experience.

[0937] The processing flow will be explained below.

[0938] Step 1:

[0939] A user visits an online shopping site, enters keywords related to the style they are looking for in a designated input field, and selects criteria such as budget, color, style, etc. from checkboxes and drop-down menus. Once this input is complete, the user clicks the "Search" button.

[0940] Step 2:

[0941] The device receives the keywords and selected conditions entered by the user, and converts the data into JSON format.

[0942] Step 3:

[0943] The device prepares an HTTP POST request with the generated JSON data as its content. The HTTP request includes the keywords and conditions entered by the user. Once ready, the request is sent to the server.

[0944] Step 4:

[0945] The server receives the HTTP POST request from the device, parses the JSON data from the request, and extracts filter conditions such as keywords, budget, color, and style.

[0946] Step 5:

[0947] The server constructs an SQL query for searching the database based on the extracted filter conditions, and the constructed SQL query is for obtaining the corresponding product information.

[0948] Step 6:

[0949] The server executes the constructed SQL query against the database, which returns items that match the specified criteria.

[0950] Step 7:

[0951] The server generates outfit suggestions that match the user's criteria based on the search results returned from the database, and the generated list of suggestions is converted back into JSON format.

[0952] Step 8:

[0953] The server prepares an HTTP response containing the generated JSON data, and when ready, sends the HTTP response to the terminal.

[0954] Step 9:

[0955] The device receives the HTTP response sent from the server, parses the JSON data from the response, and dynamically generates HTML content to display the results to the user.

[0956] Step 10:

[0957] Users can view a list of possible outfits displayed on their device, select the items they want, and access the details page to complete the purchase.

[0958] Example 1

[0959] 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."

[0960] Currently, there are systems that allow users to efficiently search for and coordinate products that suit their preferences, but these systems have problems such as being complex and difficult to use, or the search results do not meet the user's expectations.The purpose of this invention is to provide a system that can quickly and easily present optimal coordination candidates based on the user's intentions.

[0961] 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.

[0962] In this invention, the server includes means for analyzing received data and extracting filter conditions, means for searching a database based on the filter conditions, and means for generating outfit candidates based on the search results, thereby enabling the efficient generation and provision of products and outfit candidates that are optimal for the keywords and conditions entered by the user.

[0963] "User" refers to a person who uses the system to search for and coordinate products.

[0964] "Keywords" refer to specific words or phrases that users enter when searching for products or outfits.

[0965] "Conditions" are multiple options that users specify when coordinating outfits or searching for products, and include budget, color, style, etc.

[0966] "Terminal" refers to the electronic device that a user actually uses to access the system, including a personal computer or smartphone.

[0967] A "server" refers to a central computer that processes data and manages databases for a system.

[0968] The "JSON format" is a data exchange format for expressing data in a structured text-based format.

[0969] An "HTTP POST request" is a protocol for a client to send data to a server, and is used to add data to a specific resource.

[0970] "Filter conditions" are specific conditions necessary for a search that are extracted from the data received and analyzed by the server.

[0971] "Database" refers to an integrated data storage system that stores product information, inventory information, metadata, etc.

[0972] "SQL query" means a statement written in Structured Query Language for manipulating a database.

[0973] "Coordination candidates" refer to combinations of multiple recommended items generated by the server based on conditions entered by the user.

[0974] "HTML content" refers to data written in a markup language that constitutes the display content of a web page.

[0975] "Dynamically generated" refers to generating or changing data in real time as the program is executed.

[0976] The detailed description necessary to practice the present invention is provided below.

[0977] User operations

[0978] First, users access an online shopping site. The site provides an input field for entering keywords related to the outfit they are looking for. There are also check boxes and drop-down menus for setting conditions such as budget, color, and style. For example, users can enter the keyword "casual" and conditions such as "budget 5,000 yen," "blue," and "simple."

[0979] Terminal handling

[0980] The device receives keywords and multiple conditions entered by the user. This data is converted to JSON format using a script such as JavaScript. The device then sends this JSON data to the server using an HTTP POST request. The technology used can be, for example, a web browser, a mobile application, or JavaScript.

[0981] Data reception and analysis by the server

[0982] The server receives the HTTP POST request sent from the device, parses the received JSON data, and extracts filter conditions such as keywords ("casual"), budget ("5,000 yen"), color ("blue"), and style ("simple"). Backend technologies such as Python and Node.js are used for this analysis.

[0983] Database search by server

[0984] The server generates an SQL query based on the extracted filter conditions and searches the database. For example, using a database management system such as MySQL, you can construct an SQL query like this:

[0985] sql

[0986] SELECT FROM products WHERE category = 'casual' AND price <= 5000 AND color = 'blue' AND style = 'simple';

[0987] The query searches for matching product information, inventory information, and metadata.

[0988] Server generates and sends search results

[0989] The server generates outfit suggestions that match the user's search criteria based on the results retrieved from the database, adds detailed information about each item (product name, price, color, style, stock status, etc.), converts it into JSON format, and sends it back to the device.

[0990] Displaying results on a terminal

[0991] The device receives the JSON data returned from the server. The received data is parsed using JavaScript and dynamically generates HTML content. For example, the following product information is displayed:

[0992] html

[0993]

[0994] <h2> Blue Casual Shirt< / h2>

[0995] Price: 4,000 yen

[0996] Color: Blue

[0997] Style: Casual

[0998] In stock: 10

[0999]

[1000]

[1001] <h2> Blue Jeans< / h2>

[1002] Price: 3500 yen

[1003] Color: Blue

[1004] Style: Simple

[1005] In stock: 5

[1006]

[1007] Users can choose their favorite items from the displayed items.

[1008] Examples of concrete examples and prompts

[1009] For example, if a user enters criteria such as "casual, budget 5000 yen, blue, simple", the system will act as follows:

[1010] 1. The user enters conditions such as "casual, budget 5,000 yen, blue, simple."

[1011] 2. The device converts this data into JSON format and sends it to the server using an HTTP POST request.

[1012] 3. The server receives the request and searches the database based on the criteria.

[1013] 4. The server generates coordination candidates based on the search results, converts them into JSON format, and returns them to the device.

[1014] 5. The device parses the JSON data and dynamically generates and displays HTML content.

[1015] An example of an input prompt for a generative AI model would be:

[1016] The user has entered conditions such as "casual, budget 5000 yen, blue, simple." Please search for outfit candidates that match these conditions and return the results.

[1017] In this way, the present invention allows the user to find a desired outfit efficiently in a short time, improving the user experience.

[1018] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1019] System program processing flow

[1020] Step 1:

[1021] A user accesses an online shopping site and enters keywords and multiple conditions (e.g., "casual," "budget 5,000 yen," "blue," "simple"). This aggregates the search conditions. The inputs include keywords, budget, color, and style, and are passed to the device.

[1022] Step 2:

[1023] The device retrieves the data (keywords and conditions) entered by the user. Specifically, it collects form data using a script such as JavaScript. The collected data is structured as follows:

[1024] json

[1025] {

[1026] "keyword": "casual",

[1027] "budget": 5000,

[1028] "color": "blue",

[1029] "style": "simple"

[1030] }

[1031] This acquired data is passed to the terminal as input and then converted to JSON format.

[1032] Step 3:

[1033] The data acquired by the device is converted to JSON format. The JavaScript JSON.stringify method is used for the data conversion. The converted data is output in the following format:

[1034] json

[1035] {

[1036] "keyword": "casual",

[1037] "budget": 5000,

[1038] "color": "blue",

[1039] "style": "simple"

[1040] }

[1041] The converted data is passed to the terminal as input for the HTTP POST request.

[1042] Step 4:

[1043] The device sends JSON data to the server using an HTTP POST request. Specifically, the request is sent using the fetch API or XMLHttpRequest. The input of this step is the converted JSON data, and the output is sent to the server.

[1044] Step 5:

[1045] The server receives an HTTP POST request sent from the device. The received data is in JSON format, and the server parses it. Specifically, it parses the JSON data using a parsing library in Python or Node.js. The input to this step is the JSON data received via the HTTP request, and the parsed filter conditions are output.

[1046] Step 6:

[1047] The server generates an SQL query based on the analyzed filter conditions and searches the database. Specifically, it generates the following query using SQL:

[1048] sql

[1049] SELECT FROM products WHERE category = 'casual' AND price <= 5000 AND color = 'blue' AND style = 'simple';

[1050] It takes filter conditions as input and produces search results retrieved from a database as output.

[1051] Step 7:

[1052] The server retrieves search results from the database and converts the outfit suggestions that match the user's criteria into JSON format. Specifically, it uses Python or Node.js to serialize the structured data into JSON format. The following JSON data is generated as output:

[1053] json

[1054] [

[1055] {

[1056] "product_name": "Blue Casual Shirt",

[1057] "price": 4000,

[1058] "color": "blue",

[1059] "style": "casual",

[1060] "stock": 10

[1061] },

[1062] {

[1063] "product_name": "Blue Jeans",

[1064] "price": 3500,

[1065] "color": "blue",

[1066] "style": "simple",

[1067] "stock": 5

[1068] }

[1069] ]

[1070] The input to this step is a database search result, and the output is transformed JSON data.

[1071] Step 8:

[1072] The server returns the generated JSON data to the terminal as an HTTP response. Specifically, it sets the JSON data in the body of the HTTP response and sends it to the client. The input to this step is the generated JSON data, and it is sent to the terminal as the output.

[1073] Step 9:

[1074] The device receives and parses the JSON data returned from the server. Specifically, it parses the data using the JavaScript JSON.parse method. The received data is input, and the parsed data is output.

[1075] Step 10:

[1076] Dynamically generate HTML content based on the data analyzed by the device. Specifically, JavaScript is used to manipulate the DOM and generate the following HTML:

[1077] html

[1078]

[1079] <h2> Blue Casual Shirt< / h2>

[1080] Price: 4,000 yen

[1081] Color: Blue

[1082] Style: Casual

[1083] In stock: 10

[1084]

[1085]

[1086] <h2> Blue Jeans< / h2>

[1087] Price: 3500 yen

[1088] Color: Blue

[1089] Style: Simple

[1090] In stock: 5

[1091]

[1092] This allows users to visually see search results, with parsed JSON data as input and generated HTML content as output.

[1093] (Application example 1)

[1094] 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."

[1095] Conventional online shopping sites make it difficult for users to quickly find the outfits they want, and are unable to provide optimal suggestions for each individual user. Furthermore, they lack features to improve the user experience, such as voice input and social media sharing. There is a need for a system that can solve these problems and enable users to efficiently find the outfits they want.

[1096] 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.

[1097] In this invention, the server includes means for individually proposing optimal outfits based on past search history and purchase history, means for specifying conditions through voice input, and means for sharing selected outfits on social networking services. This allows users to receive optimal suggestions based on their own preferences and past behavior, allows them to specify conditions more easily through voice input, and further enhances the social experience value by sharing selected items on SNS.

[1098] "User" refers to a person who uses the system to search for outfit suggestions.

[1099] "Keywords" refer to words or phrases related to the outfit the user desires.

[1100] "Conditions" refer to factors such as budget, color, and style that users specify to narrow down their outfits.

[1101] "Terminal" refers to a device, such as a smartphone or computer, that a user uses to access the system.

[1102] The term "server" refers to a remote computer system that receives data sent by a user, searches a database, and generates and returns coordinate candidates.

[1103] "Database" refers to a collection of information that stores product information and metadata.

[1104] An "SQL query" is a query statement used to retrieve specific information from a database.

[1105] "HTML content" refers to content written in a markup language used to define the structure of a web page.

[1106] "Past search history" refers to a record of searches a user has previously conducted.

[1107] "Purchase history" refers to a record of products a user has purchased to date.

[1108] "Voice input" refers to the function that allows the user to specify conditions by voice through a microphone.

[1109] "Social networking service" refers to a platform, such as Facebook or Twitter, that enables users to interact with other users online.

[1110] This invention relates to a system that provides outfit suggestions based on keywords and multiple conditions specified by a user. Specifically, this system includes means for a user to input keywords and conditions such as budget, color, and style, means for a terminal to transmit the input data to a server, means for the server to receive the data and search a database, means for the server to generate suggestions and return them to the terminal, means for the terminal to display the results to the user, means for individually proposing optimal outfits based on past search history and purchase history, means for specifying conditions through voice input, and means for sharing selected outfits on a social networking service.

[1111] Hardware and Software Use

[1112] The server uses server software (e.g., Python Flask) to communicate with the database server and execute SQL queries. The database uses SQLite to store product information and metadata. The terminal uses HTML / CSS / JavaScript to provide a user interface, receives input from the user, converts it into JSON format, and sends it to the server.

[1113] Data processing and calculation

[1114] 1. The user enters keywords and conditions using the terminal.

[1115] Example: "Casual, budget 5000 yen, blue, simple"

[1116] 2. The device converts the input data into JSON format and sends an HTTP POST request to the server.

[1117] 3. The server parses the received JSON data and extracts conditions such as keywords, budget, color, and style.

[1118] 4. The server generates an SQL query based on the extracted conditions and searches for the corresponding product information in the database.

[1119] 5. The server generates coordination candidates based on the search results and returns them to the device in JSON format.

[1120] 6. The device parses the received JSON data and dynamically generates HTML content to display to the user.

[1121] Specific examples

[1122] If a user enters the keyword "casual," a budget of 5,000 yen, color "blue," and style "simple," the results will be as follows.

[1123] 1. The user enters criteria such as "casual, budget 5,000 yen, blue, simple."

[1124] 2. The device converts this data into JSON format and sends it to the server.

[1125] 3. The server receives the request and searches the database for matching products based on the criteria.

[1126] 4. The server generates coordination candidates based on the search results and returns them to the device.

[1127] 5. The device displays the returned candidate list as dynamic HTML content, allowing the user to browse through them and select the items they like.

[1128] An example of a prompt sentence using a generative AI model is, "The user is looking for a simple, casual, blue outfit within a budget of 5,000 yen. Please search the database for matching products and create a list." This allows the server to suggest products that meet the criteria.

[1129] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1130] Step 1:

[1131] The user enters keywords and conditions.

[1132] Input: Keywords (e.g., "casual"), budget (e.g., 5,000 yen), color (e.g., "blue"), style (e.g., "simple")

[1133] Output: User input data

[1134] What it does: The user enters conditions using input fields, checkboxes, drop-down menus, or even voice input. The device captures this data.

[1135] Step 2:

[1136] The terminal converts the input data into JSON format and sends it to the server via an HTTP POST request.

[1137] Input: User-entered data

[1138] Output: JSON format data

[1139] Specific operation: The terminal converts the user's input data into JSON format and sends it to the server using an HTTP POST request. Converting into JSON format improves data integrity and transmission efficiency.

[1140] Step 3:

[1141] The server receives the JSON data and parses the conditions.

[1142] Input: JSON format data

[1143] Output: Conditions (keywords, budget, color, style)

[1144] How it works: The server receives an HTTP request and parses the received JSON data to extract conditions such as keywords, budget, color, style, etc. This is done using the Python json library.

[1145] Step 4:

[1146] The server generates an SQL query based on the criteria and searches the database.

[1147] Input: Conditions (keywords, budget, color, style)

[1148] Output: Matching product information

[1149] Specific operation: The server generates an SQL query based on the extracted conditions and searches the SQLite database. The generated SQL query is executed using an ORM such as SQLAlchemy, which retrieves product information that matches the conditions.

[1150] Step 5:

[1151] The server generates coordination suggestions based on the search results and returns them to the device in JSON format.

[1152] Input: Relevant product information

[1153] Output: Coordinate candidates (JSON format)

[1154] Specific operation: The server creates outfit suggestions based on the search results and converts them back into JSON format. The generated JSON data is sent back to the device as an HTTP response. In this process, past search and purchase history is also taken into consideration.

[1155] Step 6:

[1156] The device parses the returned JSON data, dynamically generates HTML content, and displays it to the user.

[1157] Input: Coordinate candidates (JSON format)

[1158] Output: Dynamically generated HTML content

[1159] How it works: The device parses the JSON data received from the server and dynamically displays outfit suggestions using HTML / CSS / JavaScript. Users can browse the results and select their favorite items. Features include suggestions based on past search and purchase history, voice input for specifying search criteria, and the ability to share on social media.

[1160] 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.

[1161] To implement the present invention, cooperation between the user, the terminal, and the server is important. Furthermore, the present invention also incorporates an emotion engine for recognizing the user's emotions. The specific mechanism of the invention is as follows.

[1162] User operations

[1163] Users access an online shopping site, enter keywords related to the outfit they are looking for in designated input fields, and select criteria such as budget, color, and style from checkboxes and drop-down menus. This aggregates information that conveys the user's intentions and preferences to the system.

[1164] Terminal handling

[1165] The device acquires the keywords entered by the user and the conditions selected. The acquired data is converted into JSON format. The device also has a built-in emotion engine that recognizes the user's emotions, recognizing emotions from the user's facial expressions and voice in real time. This emotion data is also included in the JSON format.

[1166] Sending data to the server

[1167] The device prepares an HTTP POST request with the generated JSON data, including the keywords and conditions entered by the user and the recognized emotion data, and then sends the request to the server.

[1168] Server receives and searches data

[1169] The server receives an HTTP POST request from the device. It parses the received JSON data and extracts filter criteria such as keywords, budget, color, and style, as well as user sentiment data. The server then uses these criteria to construct an SQL query to search for matching items in the database. The SQL query is executed against the database, which contains product information, inventory information, and associated metadata.

[1170] Generating and submitting search results

[1171] Based on the data returned as search results, the server generates outfit candidates that match the user's criteria and emotional data. For example, if the user expresses the emotion "fun," the server will prioritize items in colors and styles that match that emotion. The generated candidate list is then converted back to JSON format and sent back to the device.

[1172] Displaying results on a terminal

[1173] The device receives the HTTP response sent from the server, analyzes the JSON data from the response, and dynamically generates HTML content to display the results to the user. This allows the user to view a list of products and outfit suggestions that match the search criteria and their current emotions.

[1174] Specific examples

[1175] For example, if a user selects the keyword "casual," a budget of 5,000 yen, the color "blue," the style "simple," and also indicates the emotion "fun," the system will operate as follows:

[1176] 1. The user enters conditions such as "casual, budget 5,000 yen, blue, simple."

[1177] 2. The emotion engine recognizes the emotion "fun" from the user's facial expression.

[1178] 3. The device converts this data into JSON format and sends it to the server.

[1179] 4. The server receives the request and searches the database for the corresponding item.

[1180] 5. Based on the search results, the server generates coordination candidates that correspond to the user's emotions and returns them to the device.

[1181] 6. The device will display the returned list of options, allowing the user to browse through them and select the items they like.

[1182] In this way, the present invention allows users to efficiently find outfits that suit their emotions, improving the user experience of online shopping.

[1183] The processing flow will be explained below.

[1184] Step 1:

[1185] A user accesses an online shopping site, enters keywords related to the outfit they are looking for in a designated input field, and selects criteria such as budget, color, and style from checkboxes and drop-down menus. Once this input is complete, the user clicks the "Search" button.

[1186] Step 2:

[1187] The device acquires the keywords entered by the user and the conditions selected. The acquired data is converted into JSON format. The device also has a built-in emotion engine that recognizes the user's emotions, recognizing emotions from the user's facial expressions and voice in real time. This emotion data is also included in the JSON format.

[1188] Step 3:

[1189] The device prepares an HTTP POST request with the generated JSON data as its content. The HTTP request includes the keywords and conditions entered by the user, as well as the recognized emotion data. Once ready, the request is sent to the server.

[1190] Step 4:

[1191] The server receives the HTTP POST request from the device, parses the JSON data from the request, and extracts filter conditions such as keywords, budget, color, and style, as well as user sentiment data.

[1192] Step 5:

[1193] The server constructs an SQL query to search the database based on the extracted filter conditions and emotion data, and the constructed SQL query is used to obtain the relevant product information.

[1194] Step 6:

[1195] The server executes the constructed SQL query against the database, which returns items that match the specified criteria.

[1196] Step 7:

[1197] The server generates outfit suggestions that match the user's criteria and emotional data based on the search results returned from the database. For example, if the user expresses the emotion "fun," it will prioritize items in colors and styles that match that emotion. The generated candidate list is then converted back into JSON format.

[1198] Step 8:

[1199] The server prepares an HTTP response containing the generated JSON data, and when ready, sends the HTTP response to the terminal.

[1200] Step 9:

[1201] The device receives the HTTP response sent from the server, parses the JSON data from the response, and dynamically generates HTML content to display the results to the user.

[1202] Step 10:

[1203] Users can view a list of possible outfits displayed on their device, select the items they want, and access the details page to complete the purchase.

[1204] Specific examples

[1205] For example, if a user selects the keyword "casual," a budget of 5,000 yen, the color "blue," the style "simple," and also indicates the emotion "fun," the system will operate as follows:

[1206] 1. The user enters conditions such as "casual, budget 5,000 yen, blue, simple."

[1207] 2. The emotion engine recognizes the emotion "fun" from the user's facial expression.

[1208] 3. The device converts this data into JSON format and sends it to the server.

[1209] 4. The server receives the request and searches the database for the corresponding item.

[1210] 5. Based on the search results, the server generates coordination candidates that correspond to the user's emotions and returns them to the device.

[1211] 6. The device will display the returned list of options, allowing the user to browse through them and select the items they like.

[1212] In this way, the present invention allows users to efficiently find outfits that suit their emotions, improving the user experience of online shopping.

[1213] Example 2

[1214] 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."

[1215] Conventional online shopping systems only provide search results based on user input criteria and are unable to display results that reflect the user's real-time emotional state, resulting in a limited user experience and preventing more advanced personalization to improve user satisfaction.

[1216] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1217] In this invention, the server includes means for recognizing emotions from a user's facial expressions and voice in real time using an emotion engine, means for transmitting JSON-formatted data including input data and recognized emotion data to the server, means for the server to receive the data, generate and execute an SQL query for searching a database, and means for generating candidates based on the user's input conditions and emotion data and returning them to the terminal, thereby making it possible to provide personalized search results that reflect the user's real-time emotions.

[1218] "User" means an individual or organization that uses the online shopping site to search for and purchase products.

[1219] A "keyword" is a word or phrase that a user enters as a search condition for a product.

[1220] "Conditions" are information in addition to keywords that narrow down search results, and include budget, color, style, etc.

[1221] A "terminal" is a device operated by a user, such as a computer, smartphone, or tablet.

[1222] "Data" refers to information including keywords and conditions entered by the user, as well as recognized emotional information.

[1223] "Emotion data" is emotional information obtained from the user's facial expressions and voice recognized in real time by the emotion engine.

[1224] The "JSON format" is a lightweight data exchange format for expressing data structures.

[1225] A "server" is a central computer system that receives requests from users and performs processes such as database searches and candidate generation.

[1226] An "SQL query" is a standardized query language for searching and manipulating data in a relational database.

[1227] "Candidates" is a list of product suggestions generated by the server based on the user's input conditions and emotion data.

[1228] "HTML content" refers to a document format for configuring the display content of a web page, and is data that is dynamically generated for displaying the results.

[1229] In order to implement the present invention, cooperation between users, terminals, and servers is essential. How each of these components functions will be described in detail below.

[1230] User operations

[1231] A user first visits an online shopping site, where they enter keywords related to the outfit they are looking for, and then select criteria such as budget, color, and style using checkboxes and drop-down menus. This information plays a key role in identifying the products they are looking for.

[1232] Terminal handling

[1233] The terminal is a device for acquiring keywords and conditions entered by the user. The acquired data is converted into JSON format. Furthermore, the terminal is equipped with an emotion engine (e.g., Microsoft Azure Emotion API or Google Cloud Vision API) for recognizing the user's emotions, and recognizes emotions from the user's facial expressions and voice in real time. This emotion data is also included in the JSON format.

[1234] Sending data to the server

[1235] The device prepares an HTTP POST request with the generated JSON data, including the keywords and conditions entered by the user and the recognized emotion data, and then sends the HTTP request to the server.

[1236] Server receives and searches data

[1237] The server receives the HTTP POST request sent from the device. It parses the received JSON data and extracts filter criteria such as keywords, budget, color, and style, as well as user sentiment data. The server then constructs an SQL query to search the database based on these criteria. The SQL query is executed against the database, which contains product information, inventory information, and associated metadata.

[1238] Generating and submitting search results

[1239] The server generates outfit suggestions that match the user's criteria and emotional data based on the search results. For example, if the user expresses the emotion "fun," the server will prioritize items in colors and styles that match that emotion. The generated candidate list is then converted back to JSON format and sent back to the device.

[1240] Displaying results on a terminal

[1241] The device receives the HTTP response sent from the server, analyzes the JSON data from the response, and dynamically generates HTML content to display the results to the user. This allows the user to view a list of products and outfit suggestions that match the search criteria and their current emotions.

[1242] Specific examples

[1243] For example, if a user selects the keyword "casual," a budget of 5,000 yen, the color "blue," the style "simple," and also indicates the emotion "fun," the system will operate as follows:

[1244] 1. The user enters conditions such as "casual, budget 5,000 yen, blue, simple."

[1245] 2. The emotion engine recognizes the emotion "fun" from the user's facial expression.

[1246] 3. The device converts this data into JSON format and sends it to the server.

[1247] 4. The server receives the request and searches the database for the corresponding item.

[1248] 5. Based on the search results, the server generates coordination candidates that correspond to the user's emotions and returns them to the device.

[1249] 6. The device will display the returned list of options, allowing the user to browse through them and select the items they like.

[1250] Example prompts for generative AI models

[1251] "If a user visits an online shopping site and enters criteria such as 'casual,' 'budget: 5000 yen,' 'color: blue,' and 'style: simple,' and the emotion engine also recognizes the emotion 'fun,' what would happen?"

[1252] In this way, the system of the present invention realizes product search and display that reflects the user's real-time emotions, allowing users to efficiently find outfits that match their emotions and improving the user experience of online shopping.

[1253] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1254] Program processing flow

[1255] Step 1:

[1256] Users access online shopping sites and input and select criteria such as keywords, budget, color, and style to search for outfits. The data input here includes keywords (e.g., "casual"), budget (e.g., "5,000 yen"), color (e.g., "blue"), and style (e.g., "simple").

[1257] Input: Keywords, Budget, Color, Style

[1258] Output: The conditions entered by the user

[1259] Step 2:

[1260] The device receives the keywords and conditions entered by the user, converts this data into JSON format, and uses an emotion engine to recognize emotions from the user's facial expressions and voice in real time, and includes this emotion data in the JSON data. The emotion engine can use, for example, the Microsoft Azure Emotion API or the Google Cloud Vision API.

[1261] Input: User-entered conditions, facial expressions, and voice

[1262] Output: Data converted to JSON format (e.g., {"keyword": "casual", "budget": 5000, "color": "blue", "style": "simple", "emotion": "fun"})

[1263] Step 3:

[1264] The device prepares an HTTP POST request containing the generated JSON data and sends it to the server, which may include header information and an authentication token.

[1265] Input: User criteria and sentiment data in JSON format

[1266] Output: HTTP POST request sent to the server

[1267] Step 4:

[1268] The server receives the HTTP POST request sent from the device and parses the JSON data, extracting keywords, budget, color, style, and sentiment data.

[1269] Input: The received HTTP POST request

[1270] Output: Extracted keywords, budget, color, style, and sentiment data

[1271] Step 5:

[1272] The server generates and executes an SQL query based on the extracted data, such as: SELECT FROM items WHERE style="simple" AND color="blue" AND price <= 5000 AND emotion="fun", to search for matching items in the database.

[1273] Input: Extracted keywords, budget, color, style, sentiment data

[1274] Output: Search results from the database (using SQL queries)

[1275] Step 6:

[1276] The server generates outfit suggestions that match the user's criteria and emotional data based on the search results. The search results are then converted back to JSON format and sent back to the device.

[1277] Input: Search results from the database

[1278] Output: A list of outfit options converted to JSON format (e.g., [{"item": "Blue T-shirt", "price": 3000, "style": "Simple"}])

[1279] Step 7:

[1280] The device parses the HTTP response received from the server, extracts the JSON data, dynamically generates HTML content based on this data, and displays the results to the user.

[1281] Input: Received HTTP response

[1282] Output: Dynamically generated HTML content

[1283] summary

[1284] This process allows users to receive personalized search results based on real-time sentiment, improving the user experience.

[1285] (Application example 2)

[1286] 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."

[1287] Conventional online shopping systems have the problem of limiting the user experience because they do not take into account the emotions or moods of users when they search for products by entering keywords or conditions. Another issue is that it takes time and effort for users to find products and outfits that match their emotions.

[1288] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for searching a database, means for generating candidates and returning them to the terminal, means for converting data including emotion data into JSON format and sending it to the server, and means for analyzing the emotion data and reflecting it in candidate generation. This makes it possible to suggest products based on the user's emotions.

[1289] "User" refers to a person who uses the system to search for and purchase products.

[1290] "Keywords" refers to words or phrases that users enter to specifically express their search intent.

[1291] "Conditions" refer to specific requirements such as budget, color, style, etc. that users specify along with keywords.

[1292] "Device" refers to an electronic device, such as a computer, smartphone, or tablet, that a User uses to access the System.

[1293] "Server" refers to a central management system that receives data sent from the terminal, searches a database, and returns the results to the terminal.

[1294] A "database" refers to a collection of digital information that stores product information, inventory information, and related metadata.

[1295] "Search" refers to the act of retrieving information from a database based on specified conditions.

[1296] "JSON format" is an abbreviation for JavaScript Object Notation, and refers to a lightweight data exchange format for expressing data in an easily structurable form.

[1297] An "HTTP POST request" refers to a request format that uses the HTTP protocol for a client to send data to a server.

[1298] "Emotion engine" refers to a software module that recognizes and analyzes user emotions in real time.

[1299] "Suggestions" refers to a list of products and outfits suggested based on the conditions and emotions entered by the user.

[1300] "HTML content" refers to information written in a markup language that makes up a web page.

[1301] To implement this invention, cooperation between the user, the terminal, and the server is essential. The user first accesses the online shopping system and enters keywords related to the product they are looking for, as well as conditions such as budget, color, and style, into the input fields on the screen. This communicates the user's intentions and wishes to the system.

[1302] The device receives the keywords and conditions entered by the user and converts this data into JSON format. Furthermore, the device is equipped with an emotion engine that analyzes the user's facial expressions and voice in real time to recognize their emotions. This emotion data is also included in the JSON format. A specific emotion engine that can be used is DeepFace.

[1303] The device sends the generated JSON data to the server as an HTTP POST request. The server receives this request and analyzes the data. The analyzed data includes keywords, conditions, and emotional data. The server searches the database based on this data and generates candidates for relevant products and outfits.

[1304] Specifically, if a user inputs criteria such as "casual," "budget 5,000 yen," "blue," and "simple," and the emotion engine recognizes the emotion "fun" from the user's facial expression, the device converts this data into JSON format and sends it to the server. The server receives the data and searches for matching items in its database. At this time, it also takes the emotional data into consideration and prioritizes items with colors and designs that match the emotion of "fun."

[1305] The server then converts the selected product information back into JSON format and sends it back to the device. The device then receives this data, dynamically generates HTML content, and displays the results to the user, allowing the user to easily find products and outfits that match their emotions.

[1306] Examples of prompt sentences include the following:

[1307] "I'm looking for casual fashion items. My budget is under 5,000 yen, the color is blue, and the style is simple. I'm in a fun mood right now, so please suggest products that fit that."

[1308] "I like the color blue and would like to wear something casual and simple. I'm in a fun mood, so please find an outfit that matches that feeling."

[1309] In this way, it becomes possible to suggest products that take the user's emotions into account, improving the online shopping user experience.

[1310] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1311] Step 1:

[1312] A user accesses an online shopping system and enters keywords and multiple criteria (budget, color, style, etc.).

[1313] Input: Keywords, Budget, Color, Style

[1314] Output: A data set containing the user's intent and desires

[1315] Step 2:

[1316] The device receives data entered by the user and converts it into JSON format. It also uses an emotion engine to recognize emotions from the user's facial expressions and voice in real time.

[1317] Input: User input data, user facial expressions and voice

[1318] Output: JSON format data containing keywords, conditions, and sentiment

[1319] Step 3:

[1320] The device sends the generated JSON data to the server as an HTTP POST request.

[1321] Input: JSON format data

[1322] Output: HTTP POST request to the server

[1323] Step 4:

[1324] The server receives the HTTP POST request sent from the device and parses the JSON data, extracting keywords, conditions, and sentiment data.

[1325] Input: HTTP POST request (JSON format data)

[1326] Output: Parsed data with keywords, terms, and sentiment

[1327] Step 5:

[1328] The server searches the database based on the analyzed data and generates relevant products and outfit suggestions, prioritizing the search results by taking into account the emotional data.

[1329] Input: Parsed data

[1330] Output: Candidate product list

[1331] Step 6:

[1332] The server converts the generated candidate product list back into JSON format and sends it back to the terminal.

[1333] Input: candidate product list

[1334] Output: JSON format candidate product list

[1335] Step 7:

[1336] The terminal parses the JSON data received from the server, dynamically generates HTML content, and displays the results to the user.

[1337] Input: JSON format candidate product list received from the server

[1338] Output: Product list displayed in HTML format

[1339] An example of a specific prompt sentence is, "I'm looking for a casual fashion item. My budget is under 5,000 yen, the color is blue, and the style is simple. I'm in a happy mood right now, so please suggest a product that suits that."

[1340] 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.

[1341] 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.

[1342] 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.

[1343] [Fourth embodiment]

[1344] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1345] 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.

[1346] 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).

[1347] 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.

[1348] 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.

[1349] 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).

[1350] 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. 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.

[1351] 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.

[1352] 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.

[1353] 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.

[1354] 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.

[1355] 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.

[1356] 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."

[1357] In order to implement the present invention, cooperation between the user, the terminal, and the server is important. The specific mechanism of the invention is as follows.

[1358] User operations

[1359] Users first access an online shopping site and enter keywords related to the outfit they are looking for in a designated input field. They also select criteria such as budget, color, and style from checkboxes and drop-down menus. This process aggregates information that conveys the user's intentions and preferences to the system.

[1360] Terminal handling

[1361] The device retrieves the keywords entered by the user and the conditions selected. The retrieved data is converted into JSON format and sent to the server. The data is sent to the server using an HTTP POST request. At this stage, the information entered by the user is preserved and passed to the server.

[1362] Server receives and searches data

[1363] The server receives the request sent from the device. It parses the received JSON data and extracts filter criteria such as keywords, budget, color, and style. The server then uses these criteria to construct an SQL query to search for matching items in the database. The SQL query is executed against the database, which contains product information, inventory information, and associated metadata.

[1364] Generating and submitting search results

[1365] Based on the data returned as search results, the server generates coordination candidates. For each item, it creates detailed information that matches the user's search criteria and builds a candidate list. The constructed candidate list is then converted back to JSON format and sent back to the device.

[1366] Displaying results on a terminal

[1367] The device receives the JSON data returned from the server, analyzes it, and dynamically generates HTML content to display to the user. This allows the user to view a list of products and outfit suggestions that match the search criteria.

[1368] Specific examples

[1369] For example, if a user enters the keyword "casual," a budget of 5,000 yen, color "blue," and style "simple," the system will operate as follows:

[1370] 1. The user enters conditions such as "casual, budget 5,000 yen, blue, simple."

[1371] 2. The device converts this data into JSON format and sends it to the server.

[1372] 3. The server receives the request and searches the database for the corresponding item.

[1373] 4. The server generates coordination candidates based on the search results and returns them to the device.

[1374] 5. The device will display the returned list of options, allowing the user to browse through them and select the items they like.

[1375] In this way, the present invention allows users to find their desired outfits efficiently in a short time, improving the user experience.

[1376] The processing flow will be explained below.

[1377] Step 1:

[1378] A user visits an online shopping site, enters keywords related to the style they are looking for in a designated input field, and selects criteria such as budget, color, style, etc. from checkboxes and drop-down menus. Once this input is complete, the user clicks the "Search" button.

[1379] Step 2:

[1380] The device receives the keywords and selected conditions entered by the user, and converts the data into JSON format.

[1381] Step 3:

[1382] The device prepares an HTTP POST request with the generated JSON data as its content. The HTTP request includes the keywords and conditions entered by the user. Once ready, the request is sent to the server.

[1383] Step 4:

[1384] The server receives the HTTP POST request from the device, parses the JSON data from the request, and extracts filter conditions such as keywords, budget, color, and style.

[1385] Step 5:

[1386] The server constructs an SQL query for searching the database based on the extracted filter conditions, and the constructed SQL query is for obtaining the corresponding product information.

[1387] Step 6:

[1388] The server executes the constructed SQL query against the database, which returns items that match the specified criteria.

[1389] Step 7:

[1390] The server generates outfit suggestions that match the user's criteria based on the search results returned from the database, and the generated list of suggestions is converted back into JSON format.

[1391] Step 8:

[1392] The server prepares an HTTP response containing the generated JSON data, and when ready, sends the HTTP response to the terminal.

[1393] Step 9:

[1394] The device receives the HTTP response sent from the server, parses the JSON data from the response, and dynamically generates HTML content to display the results to the user.

[1395] Step 10:

[1396] Users can view a list of possible outfits displayed on their device, select the items they want, and access the details page to complete the purchase.

[1397] Example 1

[1398] 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."

[1399] Currently, there are systems that allow users to efficiently search for and coordinate products that suit their preferences, but these systems have problems such as being complex and difficult to use, or the search results do not meet the user's expectations.The purpose of this invention is to provide a system that can quickly and easily present optimal coordination candidates based on the user's intentions.

[1400] 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.

[1401] In this invention, the server includes means for analyzing received data and extracting filter conditions, means for searching a database based on the filter conditions, and means for generating outfit candidates based on the search results, thereby enabling the efficient generation and provision of products and outfit candidates that are optimal for the keywords and conditions entered by the user.

[1402] "User" refers to a person who uses the system to search for and coordinate products.

[1403] "Keywords" refer to specific words or phrases that users enter when searching for products or outfits.

[1404] "Conditions" are multiple options that users specify when coordinating outfits or searching for products, and include budget, color, style, etc.

[1405] "Terminal" refers to the electronic device that a user actually uses to access the system, including a personal computer or smartphone.

[1406] A "server" refers to a central computer that processes data and manages databases for a system.

[1407] The "JSON format" is a data exchange format for expressing data in a structured text-based format.

[1408] An "HTTP POST request" is a protocol for a client to send data to a server, and is used to add data to a specific resource.

[1409] "Filter conditions" are specific conditions necessary for a search that are extracted from the data received and analyzed by the server.

[1410] "Database" refers to an integrated data storage system that stores product information, inventory information, metadata, etc.

[1411] "SQL query" means a statement written in Structured Query Language for manipulating a database.

[1412] "Coordination candidates" refer to combinations of multiple recommended items generated by the server based on conditions entered by the user.

[1413] "HTML content" refers to data written in a markup language that constitutes the display content of a web page.

[1414] "Dynamically generated" refers to generating or changing data in real time as the program is executed.

[1415] The detailed description necessary to practice the present invention is provided below.

[1416] User operations

[1417] First, users access an online shopping site. The site provides an input field for entering keywords related to the outfit they are looking for. There are also check boxes and drop-down menus for setting conditions such as budget, color, and style. For example, users can enter the keyword "casual" and conditions such as "budget 5,000 yen," "blue," and "simple."

[1418] Terminal handling

[1419] The device receives keywords and multiple conditions entered by the user. This data is converted to JSON format using a script such as JavaScript. The device then sends this JSON data to the server using an HTTP POST request. The technology used can be, for example, a web browser, a mobile application, or JavaScript.

[1420] Data reception and analysis by the server

[1421] The server receives the HTTP POST request sent from the device, parses the received JSON data, and extracts filter conditions such as keywords ("casual"), budget ("5,000 yen"), color ("blue"), and style ("simple"). Backend technologies such as Python and Node.js are used for this analysis.

[1422] Database search by server

[1423] The server generates an SQL query based on the extracted filter conditions and searches the database. For example, using a database management system such as MySQL, you can construct an SQL query like this:

[1424] sql

[1425] SELECT FROM products WHERE category = 'casual' AND price <= 5000 AND color = 'blue' AND style = 'simple';

[1426] The query searches for matching product information, inventory information, and metadata.

[1427] Server generates and sends search results

[1428] The server generates outfit suggestions that match the user's search criteria based on the results retrieved from the database, adds detailed information about each item (product name, price, color, style, stock status, etc.), converts it into JSON format, and sends it back to the device.

[1429] Displaying results on a terminal

[1430] The device receives the JSON data returned from the server. The received data is parsed using JavaScript and dynamically generates HTML content. For example, the following product information is displayed:

[1431] html

[1432]

[1433] <h2> Blue Casual Shirt< / h2>

[1434] Price: 4,000 yen

[1435] Color: Blue

[1436] Style: Casual

[1437] In stock: 10

[1438]

[1439]

[1440] <h2> Blue Jeans< / h2>

[1441] Price: 3500 yen

[1442] Color: Blue

[1443] Style: Simple

[1444] In stock: 5

[1445]

[1446] Users can choose their favorite items from the displayed items.

[1447] Examples of concrete examples and prompts

[1448] For example, if a user enters criteria such as "casual, budget 5000 yen, blue, simple", the system will act as follows:

[1449] 1. The user enters conditions such as "casual, budget 5,000 yen, blue, simple."

[1450] 2. The device converts this data into JSON format and sends it to the server using an HTTP POST request.

[1451] 3. The server receives the request and searches the database based on the criteria.

[1452] 4. The server generates coordination candidates based on the search results, converts them into JSON format, and returns them to the device.

[1453] 5. The device parses the JSON data and dynamically generates and displays HTML content.

[1454] An example of an input prompt for a generative AI model would be:

[1455] The user has entered conditions such as "casual, budget 5000 yen, blue, simple." Please search for outfit candidates that match these conditions and return the results.

[1456] In this way, the present invention allows the user to find a desired outfit efficiently in a short time, improving the user experience.

[1457] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1458] System program processing flow

[1459] Step 1:

[1460] A user accesses an online shopping site and enters keywords and multiple conditions (e.g., "casual," "budget 5,000 yen," "blue," "simple"). This aggregates the search conditions. The inputs include keywords, budget, color, and style, and are passed to the device.

[1461] Step 2:

[1462] The device retrieves the data (keywords and conditions) entered by the user. Specifically, it collects form data using a script such as JavaScript. The collected data is structured as follows:

[1463] json

[1464] {

[1465] "keyword": "casual",

[1466] "budget": 5000,

[1467] "color": "blue",

[1468] "style": "simple"

[1469] }

[1470] This acquired data is passed to the terminal as input and then converted to JSON format.

[1471] Step 3:

[1472] The data acquired by the device is converted to JSON format. The JavaScript JSON.stringify method is used for the data conversion. The converted data is output in the following format:

[1473] json

[1474] {

[1475] "keyword": "casual",

[1476] "budget": 5000,

[1477] "color": "blue",

[1478] "style": "simple"

[1479] }

[1480] The converted data is passed to the terminal as input for the HTTP POST request.

[1481] Step 4:

[1482] The device sends JSON data to the server using an HTTP POST request. Specifically, the request is sent using the fetch API or XMLHttpRequest. The input of this step is the converted JSON data, and the output is sent to the server.

[1483] Step 5:

[1484] The server receives an HTTP POST request sent from the device. The received data is in JSON format, and the server parses it. Specifically, it parses the JSON data using a parsing library in Python or Node.js. The input to this step is the JSON data received via the HTTP request, and the parsed filter conditions are output.

[1485] Step 6:

[1486] The server generates an SQL query based on the analyzed filter conditions and searches the database. Specifically, it generates the following query using SQL:

[1487] sql

[1488] SELECT FROM products WHERE category = 'casual' AND price <= 5000 AND color = 'blue' AND style = 'simple';

[1489] It takes filter conditions as input and produces search results retrieved from a database as output.

[1490] Step 7:

[1491] The server retrieves search results from the database and converts the outfit suggestions that match the user's criteria into JSON format. Specifically, it uses Python or Node.js to serialize the structured data into JSON format. The following JSON data is generated as output:

[1492] json

[1493] [

[1494] {

[1495] "product_name": "Blue Casual Shirt",

[1496] "price": 4000,

[1497] "color": "blue",

[1498] "style": "casual",

[1499] "stock": 10

[1500] },

[1501] {

[1502] "product_name": "Blue Jeans",

[1503] "price": 3500,

[1504] "color": "blue",

[1505] "style": "simple",

[1506] "stock": 5

[1507] }

[1508] ]

[1509] The input to this step is a database search result, and the output is transformed JSON data.

[1510] Step 8:

[1511] The server returns the generated JSON data to the terminal as an HTTP response. Specifically, it sets the JSON data in the body of the HTTP response and sends it to the client. The input to this step is the generated JSON data, and it is sent to the terminal as the output.

[1512] Step 9:

[1513] The device receives and parses the JSON data returned from the server. Specifically, it parses the data using the JavaScript JSON.parse method. The received data is input, and the parsed data is output.

[1514] Step 10:

[1515] Dynamically generate HTML content based on the data analyzed by the device. Specifically, JavaScript is used to manipulate the DOM and generate the following HTML:

[1516] html

[1517]

[1518] <h2> Blue Casual Shirt< / h2>

[1519] Price: 4,000 yen

[1520] Color: Blue

[1521] Style: Casual

[1522] In stock: 10

[1523]

[1524]

[1525] <h2> Blue Jeans< / h2>

[1526] Price: 3500 yen

[1527] Color: Blue

[1528] Style: Simple

[1529] In stock: 5

[1530]

[1531] This allows users to visually see search results, with parsed JSON data as input and generated HTML content as output.

[1532] (Application example 1)

[1533] 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."

[1534] Conventional online shopping sites make it difficult for users to quickly find the outfits they want, and are unable to provide optimal suggestions for each individual user. Furthermore, they lack features to improve the user experience, such as voice input and social media sharing. There is a need for a system that can solve these problems and enable users to efficiently find the outfits they want.

[1535] 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.

[1536] In this invention, the server includes means for individually proposing optimal outfits based on past search history and purchase history, means for specifying conditions through voice input, and means for sharing selected outfits on social networking services. This allows users to receive optimal suggestions based on their own preferences and past behavior, allows them to specify conditions more easily through voice input, and further enhances the social experience value by sharing selected items on SNS.

[1537] "User" refers to a person who uses the system to search for outfit suggestions.

[1538] "Keywords" refer to words or phrases related to the outfit the user desires.

[1539] "Conditions" refer to factors such as budget, color, and style that users specify to narrow down their outfits.

[1540] "Terminal" refers to a device, such as a smartphone or computer, that a user uses to access the system.

[1541] The term "server" refers to a remote computer system that receives data sent by a user, searches a database, and generates and returns coordinate candidates.

[1542] "Database" refers to a collection of information that stores product information and metadata.

[1543] An "SQL query" is a query statement used to retrieve specific information from a database.

[1544] "HTML content" refers to content written in a markup language used to define the structure of a web page.

[1545] "Past search history" refers to a record of searches a user has previously conducted.

[1546] "Purchase history" refers to a record of products a user has purchased to date.

[1547] "Voice input" refers to the function that allows the user to specify conditions by voice through a microphone.

[1548] "Social networking service" refers to a platform, such as Facebook or Twitter, that enables users to interact with other users online.

[1549] This invention relates to a system that provides outfit suggestions based on keywords and multiple conditions specified by a user. Specifically, this system includes means for a user to input keywords and conditions such as budget, color, and style, means for a terminal to transmit the input data to a server, means for the server to receive the data and search a database, means for the server to generate suggestions and return them to the terminal, means for the terminal to display the results to the user, means for individually proposing optimal outfits based on past search history and purchase history, means for specifying conditions through voice input, and means for sharing selected outfits on a social networking service.

[1550] Hardware and Software Use

[1551] The server uses server software (e.g., Python Flask) to communicate with the database server and execute SQL queries. The database uses SQLite to store product information and metadata. The terminal uses HTML / CSS / JavaScript to provide a user interface, receives input from the user, converts it into JSON format, and sends it to the server.

[1552] Data processing and calculation

[1553] 1. The user enters keywords and conditions using the terminal.

[1554] Example: "Casual, budget 5000 yen, blue, simple"

[1555] 2. The device converts the input data into JSON format and sends an HTTP POST request to the server.

[1556] 3. The server parses the received JSON data and extracts conditions such as keywords, budget, color, and style.

[1557] 4. The server generates an SQL query based on the extracted conditions and searches for the corresponding product information in the database.

[1558] 5. The server generates coordination candidates based on the search results and returns them to the device in JSON format.

[1559] 6. The device parses the received JSON data and dynamically generates HTML content to display to the user.

[1560] Specific examples

[1561] If a user enters the keyword "casual," a budget of 5,000 yen, color "blue," and style "simple," the results will be as follows.

[1562] 1. The user enters criteria such as "casual, budget 5,000 yen, blue, simple."

[1563] 2. The device converts this data into JSON format and sends it to the server.

[1564] 3. The server receives the request and searches the database for matching products based on the criteria.

[1565] 4. The server generates coordination candidates based on the search results and returns them to the device.

[1566] 5. The device displays the returned candidate list as dynamic HTML content, allowing the user to browse through them and select the items they like.

[1567] An example of a prompt sentence using a generative AI model is, "The user is looking for a simple, casual, blue outfit within a budget of 5,000 yen. Please search the database for matching products and create a list." This allows the server to suggest products that meet the criteria.

[1568] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1569] Step 1:

[1570] The user enters keywords and conditions.

[1571] Input: Keywords (e.g., "casual"), budget (e.g., 5,000 yen), color (e.g., "blue"), style (e.g., "simple")

[1572] Output: User input data

[1573] What it does: The user enters conditions using input fields, checkboxes, drop-down menus, or even voice input. The device captures this data.

[1574] Step 2:

[1575] The terminal converts the input data into JSON format and sends it to the server via an HTTP POST request.

[1576] Input: User-entered data

[1577] Output: JSON format data

[1578] Specific operation: The terminal converts the user's input data into JSON format and sends it to the server using an HTTP POST request. Converting into JSON format improves data integrity and transmission efficiency.

[1579] Step 3:

[1580] The server receives the JSON data and parses the conditions.

[1581] Input: JSON format data

[1582] Output: Conditions (keywords, budget, color, style)

[1583] How it works: The server receives an HTTP request and parses the received JSON data to extract conditions such as keywords, budget, color, style, etc. This is done using the Python json library.

[1584] Step 4:

[1585] The server generates an SQL query based on the criteria and searches the database.

[1586] Input: Conditions (keywords, budget, color, style)

[1587] Output: Matching product information

[1588] Specific operation: The server generates an SQL query based on the extracted conditions and searches the SQLite database. The generated SQL query is executed using an ORM such as SQLAlchemy, which retrieves product information that matches the conditions.

[1589] Step 5:

[1590] The server generates coordination suggestions based on the search results and returns them to the device in JSON format.

[1591] Input: Relevant product information

[1592] Output: Coordinate candidates (JSON format)

[1593] Specific operation: The server creates outfit suggestions based on the search results and converts them back into JSON format. The generated JSON data is sent back to the device as an HTTP response. In this process, past search and purchase history is also taken into consideration.

[1594] Step 6:

[1595] The device parses the returned JSON data, dynamically generates HTML content, and displays it to the user.

[1596] Input: Coordinate candidates (JSON format)

[1597] Output: Dynamically generated HTML content

[1598] How it works: The device parses the JSON data received from the server and dynamically displays outfit suggestions using HTML / CSS / JavaScript. Users can browse the results and select their favorite items. Features include suggestions based on past search and purchase history, voice input for specifying search criteria, and the ability to share on social media.

[1599] 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.

[1600] To implement the present invention, cooperation between the user, the terminal, and the server is important. Furthermore, the present invention also incorporates an emotion engine for recognizing the user's emotions. The specific mechanism of the invention is as follows.

[1601] User operations

[1602] Users access an online shopping site, enter keywords related to the outfit they are looking for in designated input fields, and select criteria such as budget, color, and style from checkboxes and drop-down menus. This aggregates information that conveys the user's intentions and preferences to the system.

[1603] Terminal handling

[1604] The device acquires the keywords entered by the user and the conditions selected. The acquired data is converted into JSON format. The device also has a built-in emotion engine that recognizes the user's emotions, recognizing emotions from the user's facial expressions and voice in real time. This emotion data is also included in the JSON format.

[1605] Sending data to the server

[1606] The device prepares an HTTP POST request with the generated JSON data, including the keywords and conditions entered by the user and the recognized emotion data, and then sends the request to the server.

[1607] Server receives and searches data

[1608] The server receives an HTTP POST request from the device. It parses the received JSON data and extracts filter criteria such as keywords, budget, color, and style, as well as user sentiment data. The server then uses these criteria to construct an SQL query to search for matching items in the database. The SQL query is executed against the database, which contains product information, inventory information, and associated metadata.

[1609] Generating and submitting search results

[1610] Based on the data returned as search results, the server generates outfit candidates that match the user's criteria and emotional data. For example, if the user expresses the emotion "fun," the server will prioritize items in colors and styles that match that emotion. The generated candidate list is then converted back to JSON format and sent back to the device.

[1611] Displaying results on a terminal

[1612] The device receives the HTTP response sent from the server, analyzes the JSON data from the response, and dynamically generates HTML content to display the results to the user. This allows the user to view a list of products and outfit suggestions that match the search criteria and their current emotions.

[1613] Specific examples

[1614] For example, if a user selects the keyword "casual," a budget of 5,000 yen, the color "blue," the style "simple," and also indicates the emotion "fun," the system will operate as follows:

[1615] 1. The user enters conditions such as "casual, budget 5,000 yen, blue, simple."

[1616] 2. The emotion engine recognizes the emotion "fun" from the user's facial expression.

[1617] 3. The device converts this data into JSON format and sends it to the server.

[1618] 4. The server receives the request and searches the database for the corresponding item.

[1619] 5. Based on the search results, the server generates coordination candidates that correspond to the user's emotions and returns them to the device.

[1620] 6. The device will display the returned list of options, allowing the user to browse through them and select the items they like.

[1621] In this way, the present invention allows users to efficiently find outfits that suit their emotions, improving the user experience of online shopping.

[1622] The processing flow will be explained below.

[1623] Step 1:

[1624] A user accesses an online shopping site, enters keywords related to the outfit they are looking for in a designated input field, and selects criteria such as budget, color, and style from checkboxes and drop-down menus. Once this input is complete, the user clicks the "Search" button.

[1625] Step 2:

[1626] The device acquires the keywords entered by the user and the conditions selected. The acquired data is converted into JSON format. The device also has a built-in emotion engine that recognizes the user's emotions, recognizing emotions from the user's facial expressions and voice in real time. This emotion data is also included in the JSON format.

[1627] Step 3:

[1628] The device prepares an HTTP POST request with the generated JSON data as its content. The HTTP request includes the keywords and conditions entered by the user, as well as the recognized emotion data. Once ready, the request is sent to the server.

[1629] Step 4:

[1630] The server receives the HTTP POST request from the device, parses the JSON data from the request, and extracts filter conditions such as keywords, budget, color, and style, as well as user sentiment data.

[1631] Step 5:

[1632] The server constructs an SQL query to search the database based on the extracted filter conditions and emotion data, and the constructed SQL query is used to obtain the relevant product information.

[1633] Step 6:

[1634] The server executes the constructed SQL query against the database, which returns items that match the specified criteria.

[1635] Step 7:

[1636] The server generates outfit suggestions that match the user's criteria and emotional data based on the search results returned from the database. For example, if the user expresses the emotion "fun," it will prioritize items in colors and styles that match that emotion. The generated candidate list is then converted back into JSON format.

[1637] Step 8:

[1638] The server prepares an HTTP response containing the generated JSON data, and when ready, sends the HTTP response to the terminal.

[1639] Step 9:

[1640] The device receives the HTTP response sent from the server, parses the JSON data from the response, and dynamically generates HTML content to display the results to the user.

[1641] Step 10:

[1642] Users can view a list of possible outfits displayed on their device, select the items they want, and access the details page to complete the purchase.

[1643] Specific examples

[1644] For example, if a user selects the keyword "casual," a budget of 5,000 yen, the color "blue," the style "simple," and also indicates the emotion "fun," the system will operate as follows:

[1645] 1. The user enters conditions such as "casual, budget 5,000 yen, blue, simple."

[1646] 2. The emotion engine recognizes the emotion "fun" from the user's facial expression.

[1647] 3. The device converts this data into JSON format and sends it to the server.

[1648] 4. The server receives the request and searches the database for the corresponding item.

[1649] 5. Based on the search results, the server generates coordination candidates that correspond to the user's emotions and returns them to the device.

[1650] 6. The device will display the returned list of options, allowing the user to browse through them and select the items they like.

[1651] In this way, the present invention allows users to efficiently find outfits that suit their emotions, improving the user experience of online shopping.

[1652] Example 2

[1653] 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."

[1654] Conventional online shopping systems only provide search results based on user input criteria and are unable to display results that reflect the user's real-time emotional state, resulting in a limited user experience and preventing more advanced personalization to improve user satisfaction.

[1655] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1656] In this invention, the server includes means for recognizing emotions from a user's facial expressions and voice in real time using an emotion engine, means for transmitting JSON-formatted data including input data and recognized emotion data to the server, means for the server to receive the data, generate and execute an SQL query for searching a database, and means for generating candidates based on the user's input conditions and emotion data and returning them to the terminal, thereby making it possible to provide personalized search results that reflect the user's real-time emotions.

[1657] "User" means an individual or organization that uses the online shopping site to search for and purchase products.

[1658] A "keyword" is a word or phrase that a user enters as a search condition for a product.

[1659] "Conditions" are information in addition to keywords that narrow down search results, and include budget, color, style, etc.

[1660] A "terminal" is a device operated by a user, such as a computer, smartphone, or tablet.

[1661] "Data" refers to information including keywords and conditions entered by the user, as well as recognized emotional information.

[1662] "Emotion data" is emotional information obtained from the user's facial expressions and voice recognized in real time by the emotion engine.

[1663] The "JSON format" is a lightweight data exchange format for expressing data structures.

[1664] A "server" is a central computer system that receives requests from users and performs processes such as database searches and candidate generation.

[1665] An "SQL query" is a standardized query language for searching and manipulating data in a relational database.

[1666] "Candidates" is a list of product suggestions generated by the server based on the user's input conditions and emotion data.

[1667] "HTML content" refers to a document format for configuring the display content of a web page, and is data that is dynamically generated for displaying the results.

[1668] In order to implement the present invention, cooperation between users, terminals, and servers is essential. How each of these components functions will be described in detail below.

[1669] User operations

[1670] A user first visits an online shopping site, where they enter keywords related to the outfit they are looking for, and then select criteria such as budget, color, and style using checkboxes and drop-down menus. This information plays a key role in identifying the products they are looking for.

[1671] Terminal handling

[1672] The terminal is a device for acquiring keywords and conditions entered by the user. The acquired data is converted into JSON format. Furthermore, the terminal is equipped with an emotion engine (e.g., Microsoft Azure Emotion API or Google Cloud Vision API) for recognizing the user's emotions, and recognizes emotions from the user's facial expressions and voice in real time. This emotion data is also included in the JSON format.

[1673] Sending data to the server

[1674] The device prepares an HTTP POST request with the generated JSON data, including the keywords and conditions entered by the user and the recognized emotion data, and then sends the HTTP request to the server.

[1675] Server receives and searches data

[1676] The server receives the HTTP POST request sent from the device. It parses the received JSON data and extracts filter criteria such as keywords, budget, color, and style, as well as user sentiment data. The server then constructs an SQL query to search the database based on these criteria. The SQL query is executed against the database, which contains product information, inventory information, and associated metadata.

[1677] Generating and submitting search results

[1678] The server generates outfit suggestions that match the user's criteria and emotional data based on the search results. For example, if the user expresses the emotion "fun," the server will prioritize items in colors and styles that match that emotion. The generated candidate list is then converted back to JSON format and sent back to the device.

[1679] Displaying results on a terminal

[1680] The device receives the HTTP response sent from the server, analyzes the JSON data from the response, and dynamically generates HTML content to display the results to the user. This allows the user to view a list of products and outfit suggestions that match the search criteria and their current emotions.

[1681] Specific examples

[1682] For example, if a user selects the keyword "casual," a budget of 5,000 yen, the color "blue," the style "simple," and also indicates the emotion "fun," the system will operate as follows:

[1683] 1. The user enters conditions such as "casual, budget 5,000 yen, blue, simple."

[1684] 2. The emotion engine recognizes the emotion "fun" from the user's facial expression.

[1685] 3. The device converts this data into JSON format and sends it to the server.

[1686] 4. The server receives the request and searches the database for the corresponding item.

[1687] 5. Based on the search results, the server generates coordination candidates that correspond to the user's emotions and returns them to the device.

[1688] 6. The device will display the returned list of options, allowing the user to browse through them and select the items they like.

[1689] Example prompts for generative AI models

[1690] "If a user visits an online shopping site and enters criteria such as 'casual,' 'budget: 5000 yen,' 'color: blue,' and 'style: simple,' and the emotion engine also recognizes the emotion 'fun,' what would happen?"

[1691] In this way, the system of the present invention realizes product search and display that reflects the user's real-time emotions, allowing users to efficiently find outfits that match their emotions and improving the user experience of online shopping.

[1692] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1693] Program processing flow

[1694] Step 1:

[1695] Users access online shopping sites and input and select criteria such as keywords, budget, color, and style to search for outfits. The data input here includes keywords (e.g., "casual"), budget (e.g., "5,000 yen"), color (e.g., "blue"), and style (e.g., "simple").

[1696] Input: Keywords, Budget, Color, Style

[1697] Output: The conditions entered by the user

[1698] Step 2:

[1699] The device receives the keywords and conditions entered by the user, converts this data into JSON format, and uses an emotion engine to recognize emotions from the user's facial expressions and voice in real time, and includes this emotion data in the JSON data. The emotion engine can use, for example, the Microsoft Azure Emotion API or the Google Cloud Vision API.

[1700] Input: User-entered conditions, facial expressions, and voice

[1701] Output: Data converted to JSON format (e.g., {"keyword": "casual", "budget": 5000, "color": "blue", "style": "simple", "emotion": "fun"})

[1702] Step 3:

[1703] The device prepares an HTTP POST request containing the generated JSON data and sends it to the server, which may include header information and an authentication token.

[1704] Input: User criteria and sentiment data in JSON format

[1705] Output: HTTP POST request sent to the server

[1706] Step 4:

[1707] The server receives the HTTP POST request sent from the device and parses the JSON data, extracting keywords, budget, color, style, and sentiment data.

[1708] Input: The received HTTP POST request

[1709] Output: Extracted keywords, budget, color, style, and sentiment data

[1710] Step 5:

[1711] The server generates and executes an SQL query based on the extracted data, such as: SELECT FROM items WHERE style="simple" AND color="blue" AND price <= 5000 AND emotion="fun", to search for matching items in the database.

[1712] Input: Extracted keywords, budget, color, style, sentiment data

[1713] Output: Search results from the database (using SQL queries)

[1714] Step 6:

[1715] The server generates outfit suggestions that match the user's criteria and emotional data based on the search results. The search results are then converted back to JSON format and sent back to the device.

[1716] Input: Search results from the database

[1717] Output: A list of outfit options converted to JSON format (e.g., [{"item": "Blue T-shirt", "price": 3000, "style": "Simple"}])

[1718] Step 7:

[1719] The device parses the HTTP response received from the server, extracts the JSON data, dynamically generates HTML content based on this data, and displays the results to the user.

[1720] Input: Received HTTP response

[1721] Output: Dynamically generated HTML content

[1722] summary

[1723] This process allows users to receive personalized search results based on real-time sentiment, improving the user experience.

[1724] (Application example 2)

[1725] 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."

[1726] Conventional online shopping systems have the problem of limiting the user experience because they do not take into account the emotions or moods of users when they search for products by entering keywords or conditions. Another issue is that it takes time and effort for users to find products and outfits that match their emotions.

[1727] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for searching a database, means for generating candidates and returning them to the terminal, means for converting data including emotion data into JSON format and sending it to the server, and means for analyzing the emotion data and reflecting it in candidate generation. This makes it possible to suggest products based on the user's emotions.

[1728] "User" refers to a person who uses the system to search for and purchase products.

[1729] "Keywords" refers to words or phrases that users enter to specifically express their search intent.

[1730] "Conditions" refer to specific requirements such as budget, color, style, etc. that users specify along with keywords.

[1731] "Device" refers to an electronic device, such as a computer, smartphone, or tablet, that a User uses to access the System.

[1732] "Server" refers to a central management system that receives data sent from the terminal, searches a database, and returns the results to the terminal.

[1733] A "database" refers to a collection of digital information that stores product information, inventory information, and related metadata.

[1734] "Search" refers to the act of retrieving information from a database based on specified conditions.

[1735] "JSON format" is an abbreviation for JavaScript Object Notation, and refers to a lightweight data exchange format for expressing data in an easily structurable form.

[1736] An "HTTP POST request" refers to a request format that uses the HTTP protocol for a client to send data to a server.

[1737] "Emotion engine" refers to a software module that recognizes and analyzes user emotions in real time.

[1738] "Suggestions" refers to a list of products and outfits suggested based on the conditions and emotions entered by the user.

[1739] "HTML content" refers to information written in a markup language that makes up a web page.

[1740] To implement this invention, cooperation between the user, the terminal, and the server is essential. The user first accesses the online shopping system and enters keywords related to the product they are looking for, as well as conditions such as budget, color, and style, into the input fields on the screen. This communicates the user's intentions and wishes to the system.

[1741] The device receives the keywords and conditions entered by the user and converts this data into JSON format. Furthermore, the device is equipped with an emotion engine that analyzes the user's facial expressions and voice in real time to recognize their emotions. This emotion data is also included in the JSON format. A specific emotion engine that can be used is DeepFace.

[1742] The device sends the generated JSON data to the server as an HTTP POST request. The server receives this request and analyzes the data. The analyzed data includes keywords, conditions, and emotional data. The server searches the database based on this data and generates candidates for relevant products and outfits.

[1743] Specifically, if a user inputs criteria such as "casual," "budget 5,000 yen," "blue," and "simple," and the emotion engine recognizes the emotion "fun" from the user's facial expression, the device converts this data into JSON format and sends it to the server. The server receives the data and searches for matching items in its database. At this time, it also takes the emotional data into consideration and prioritizes items with colors and designs that match the emotion of "fun."

[1744] The server then converts the selected product information back into JSON format and sends it back to the device. The device then receives this data, dynamically generates HTML content, and displays the results to the user, allowing the user to easily find products and outfits that match their emotions.

[1745] Examples of prompt sentences include the following:

[1746] "I'm looking for casual fashion items. My budget is under 5,000 yen, the color is blue, and the style is simple. I'm in a fun mood right now, so please suggest products that fit that."

[1747] "I like the color blue and would like to wear something casual and simple. I'm in a fun mood, so please find an outfit that matches that feeling."

[1748] In this way, it becomes possible to suggest products that take the user's emotions into account, improving the online shopping user experience.

[1749] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1750] Step 1:

[1751] A user accesses an online shopping system and enters keywords and multiple criteria (budget, color, style, etc.).

[1752] Input: Keywords, Budget, Color, Style

[1753] Output: A data set containing the user's intent and desires

[1754] Step 2:

[1755] The device receives data entered by the user and converts it into JSON format. It also uses an emotion engine to recognize emotions from the user's facial expressions and voice in real time.

[1756] Input: User input data, user facial expressions and voice

[1757] Output: JSON format data containing keywords, conditions, and sentiment

[1758] Step 3:

[1759] The device sends the generated JSON data to the server as an HTTP POST request.

[1760] Input: JSON format data

[1761] Output: HTTP POST request to the server

[1762] Step 4:

[1763] The server receives the HTTP POST request sent from the device and parses the JSON data, extracting keywords, conditions, and sentiment data.

[1764] Input: HTTP POST request (JSON format data)

[1765] Output: Parsed data with keywords, terms, and sentiment

[1766] Step 5:

[1767] The server searches the database based on the analyzed data and generates relevant products and outfit suggestions, prioritizing the search results by taking into account the emotional data.

[1768] Input: Parsed data

[1769] Output: Candidate product list

[1770] Step 6:

[1771] The server converts the generated candidate product list back into JSON format and sends it back to the terminal.

[1772] Input: candidate product list

[1773] Output: JSON format candidate product list

[1774] Step 7:

[1775] The terminal parses the JSON data received from the server, dynamically generates HTML content, and displays the results to the user.

[1776] Input: JSON format candidate product list received from the server

[1777] Output: Product list displayed in HTML format

[1778] An example of a specific prompt sentence is, "I'm looking for a casual fashion item. My budget is under 5,000 yen, the color is blue, and the style is simple. I'm in a happy mood right now, so please suggest a product that suits that."

[1779] 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.

[1780] 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.

[1781] 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.

[1782] 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.

[1783] 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.

[1784] 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.

[1785] 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).

[1786] 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.

[1787] 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."

[1788] 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.

[1789] 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).

[1790] 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.

[1791] 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.

[1792] 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.

[1793] 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.

[1794] 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.

[1795] 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.

[1796] 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.

[1797] 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.

[1798] 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.

[1799] 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.

[1800] The following is further disclosed regarding the above embodiment.

[1801] (Claim 1)

[1802] a means for the user to enter keywords and multiple criteria;

[1803] A means for transmitting input data from the terminal to a server;

[1804] a means by which the server receives the data and searches the database;

[1805] A means for the server to generate candidates and return them to the terminal;

[1806] The system includes a means for the terminal to display the results to the user.

[1807] (Claim 2)

[1808] 10. The system of claim 1, wherein the server includes means for constructing an SQL query to search for the relevant items.

[1809] (Claim 3)

[1810] 10. The system of claim 1, further comprising means for dynamically generating HTML content for display by the terminal to the user.

[1811] "Example 1"

[1812] (Claim 1)

[1813] a means for the user to enter keywords and multiple criteria;

[1814] A means for the terminal to convert input data into JSON format;

[1815] A means for the terminal to send the converted data to the server via an HTTP POST request;

[1816] A means for analyzing the data received by the server and extracting filter conditions;

[1817] a means for the server to search the database based on the filter criteria;

[1818] A means for the server to generate coordination candidates based on the search results;

[1819] A means for the server to reconvert the generated candidates into JSON format and return them to the terminal;

[1820] A system that includes a means for the device to parse the returned JSON data and dynamically generate HTML content for display to the user.

[1821] (Claim 2)

[1822] 2. The system according to claim 1, wherein the server includes means for generating coordinate candidates based on the search results.

[1823] (Claim 3)

[1824] 10. The system of claim 1, wherein the terminal includes means for parsing received JSON data and dynamically generating HTML content.

[1825] "Application Example 1"

[1826] (Claim 1)

[1827] a means for the user to enter keywords and multiple criteria;

[1828] A means for transmitting input data from the terminal to a server;

[1829] a means by which the server receives the data and searches the database;

[1830] A means for the server to generate candidates and return them to the terminal;

[1831] a means by which the terminal displays the results to the user; and

[1832] A method to suggest the best outfits for each customer based on their past search and purchase history,

[1833] A means for specifying conditions through voice input;

[1834] A system that includes a means for sharing selected outfits on social networking services.

[1835] (Claim 2)

[1836] 10. The system of claim 1, wherein the server includes means for constructing an SQL query to search for relevant items.

[1837] (Claim 3)

[1838] 10. The system of claim 1, further comprising means for dynamically generating HTML content for display by the terminal to the user.

[1839] "Example 2: Combining Emotion Engines"

[1840] (Claim 1)

[1841] a means for the user to enter keywords and multiple criteria;

[1842] A means for converting the data input by the terminal into a JSON format including the user's emotion data and transmitting it to a server;

[1843] a means for the server to receive the data and generate and execute SQL queries to search the database;

[1844] A means for the server to generate candidates based on the user's input conditions and emotion data and return them to the terminal;

[1845] The system includes a means for dynamically generating HTML content for the terminal to display results to the user.

[1846] (Claim 2)

[1847] 10. The system of claim 1, further comprising means for recognizing emotions from a user's facial expressions and voice in real time using an emotion engine.

[1848] (Claim 3)

[1849] 10. The system of claim 1, wherein the terminal includes means for analyzing data received from the server and dynamically generating HTML content for displaying results to the user.

[1850] "Application example 2 when combining emotion engines"

[1851] (Claim 1)

[1852] a means for the user to enter keywords and multiple criteria;

[1853] A means for transmitting input data from the terminal to a server;

[1854] a means by which the server receives the data and searches the database;

[1855] A means for the server to generate candidates and return them to the terminal;

[1856] a means by which the terminal displays the results to the user; and

[1857] A means for the device to recognize the user's emotions in real time;

[1858] A means for converting data including emotion data into JSON format and transmitting the data to a server;

[1859] The system includes a means for the server to analyze emotion data and reflect the data in candidate generation.

[1860] (Claim 2)

[1861] 10. The system of claim 1, wherein the server includes means for constructing an SQL query to search for the relevant items.

[1862] (Claim 3)

[1863] 10. The system of claim 1, further comprising means for dynamically generating HTML content for display by the terminal to the user. [Explanation of symbols]

[1864] 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 the user to enter keywords and multiple criteria; A means for transmitting input data from the terminal to a server; a means by which the server receives the data and searches the database; A means for the server to generate candidates and return them to the terminal; The system includes a means for the terminal to display the results to the user.

2. 10. The system of claim 1, wherein the server includes means for constructing an SQL query to retrieve the relevant items.

3. 10. The system of claim 1, wherein the terminal includes means for dynamically generating HTML content for display to the user.

Images