System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting a list of items a user wishes to purchase; crawler bot means for collecting item price information from a web site; generative AI model means for calculating an optimal purchase plan based on the collected price information; and means for providing the calculated purchase plan to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Due to the recent rise in inflation, consumers are increasingly seeking cheaper products. However, conventional price comparison websites and apps only allow comparison of prices for individual products, making it difficult to comprehensively compare prices for multiple products. Furthermore, in order to efficiently purchase ingredients for cooking at the lowest price, consumers must research multiple websites and stores, which requires a significant amount of effort and time. Against this background, the present invention aims to reduce consumers' time and effort and financial burden by providing a system that comprehensively compares prices for multiple products and proposes optimal purchasing plans. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system that includes a means for a user to input a list of products they wish to purchase, a crawler bot that collects product price information from websites, a generative AI model that calculates an optimal purchase plan based on the collected price information, and a means for providing the calculated purchase plan to the user. Furthermore, by including a means for a user to input additional information and a means for collecting inventory information from nearby stores and reflecting this information in the optimal purchase plan, a more comprehensive and accurate optimal purchase plan can be provided.

[0006] "User" refers to a person who uses the system to input a list of products they wish to purchase and receives suggestions for the optimal purchase plan.

[0007] "Product Desired for Purchase" refers to an item included in a list of products that a User wishes to purchase through the System.

[0008] A "crawler bot" is a program that automatically crawls websites on the Internet and collects specific information.

[0009] A "generative AI model" refers to an algorithm or program that uses artificial intelligence to calculate the optimal purchasing plan based on collected data.

[0010] The "optimal purchase plan" refers to a plan that suggests the most economical and efficient way to purchase multiple products based on a list entered by the user.

[0011] "Additional information" refers to specific products or conditions that the user wants to add in addition to the basic desired products.

[0012] "Inventory information" refers to data indicating the current inventory status of a product at nearby stores.

[0013] "System" refers to a series of components including user terminals, servers, crawler bots, generative AI models, and the programs that link them. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] The present invention provides a system that allows a user to input a list of products they wish to purchase and suggests an optimal purchasing plan. A method for implementing this system will be described in detail below using the procedures and configuration shown below.

[0036] First, the user uses the user terminal to input a list of products they wish to purchase. Specifically, the user uses a screen to input multiple products such as "potatoes," "carrots," "onions," "meat," and "roux." In addition, the user can input additional information such as "I would like to add apples as a secret ingredient."

[0037] Next, the server receives the user's request and analyzes its contents. Based on the analyzed data, the server launches a crawler bot. The crawler bot then crawls multiple websites on the Internet and automatically collects the latest price information for each product.

[0038] The collected price information is sent back to the server, which then inputs it into the generative AI model. The generative AI model calculates the optimal purchase plan based on the collected price information and the user's request (including additional information). The generative AI model also takes into account the price of each product, inventory information, price comparisons between multiple stores, and specific point reward services to generate the most economical plan.

[0039] The server then sends the calculated optimal purchase plan to the user's terminal. The user can then check the plan on their own terminal and purchase the products at the designated stores. This process allows the user to purchase multiple products at the lowest cost and most efficiently.

[0040] As a concrete example, consider the case where a user enters "I want to buy curry ingredients at the cheapest price." When the user enters "potatoes," "carrots," "onions," "meat," "roux," and "apples" into a list, the server receives this and launches a crawler bot. The crawler bot collects price information for each item, and the generative AI model calculates the optimal plan. For example, it can suggest the nearby supermarket with the lowest total price and also display the actual cost including the initial point reward.

[0041] This saves users the time and effort of comparing prices themselves, allowing them to shop in the most economical way possible.

[0042] The processing flow will be explained below.

[0043] Step 1:

[0044] The user uses a terminal to input the items they wish to purchase. Specifically, the user launches the application's input screen and inputs a list of ingredients such as "potatoes," "carrots," "onions," "meat," and "roux." They can also input additional information, such as "apple as a secret ingredient."

[0045] Step 2:

[0046] The terminal formats the input data and sends it to the server. The terminal compiles the list of products desired for purchase and additional information into one request data.

[0047] Step 3:

[0048] The server analyzes the request received from the terminal. Specifically, the server breaks down the request data and extracts the name of each product and additional information.

[0049] Step 4:

[0050] The server launches a crawler bot, which crawls multiple websites on the Internet and collects price information for the specified product.

[0051] Step 5:

[0052] The crawler bot sends the collected price information to a server, which receives it and stores it in a database.

[0053] Step 6:

[0054] The server launches a generative AI model based on the stored price information, which receives the price information and additional information as input and calculates the optimal purchase plan.

[0055] Step 7:

[0056] The server receives the optimal purchase plan calculated by the generative AI model, formats the plan, and prepares it for delivery to the user.

[0057] Step 8:

[0058] The server sends the calculated purchase plan to the user terminal, where the user can check the proposed plan.

[0059] Step 9:

[0060] The user purchases products at the specified store based on the proposed purchase plan, enabling the user to make the most economical and efficient purchases according to the information presented.

[0061] Example 1

[0062] 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."

[0063] The problem that this invention aims to solve is to provide the most economical and efficient purchase plan by allowing users to easily input a list of products they wish to purchase and quickly collecting the latest price information from multiple websites, thereby significantly reducing the time and effort required for users to compare product prices.

[0064] 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.

[0065] In this invention, the server includes a means for a user to input a list of products they wish to purchase, a means for the server to receive and analyze requests from the user, a means for a crawler bot to crawl websites and collect product price information, a generating AI model means for calculating an optimal purchase plan based on the collected price information, and a means for providing the calculated purchase plan to a user terminal, thereby enabling a user to purchase multiple products in the most economical and efficient manner.

[0066] The "means by which users input a list of products they wish to purchase" refers to an interface for users to input information about products they wish to purchase, and is composed of an application or web form using a device such as a smartphone or PC.

[0067] "The means by which the server receives and analyzes requests from users" refers to a program on the server that receives user input data and analyzes its contents, and has the function of extracting and classifying request data.

[0068] "Means for crawler bots to crawl websites and collect product price information" refers to a software program that automatically crawls multiple websites on the Internet and collects price and inventory information about products.

[0069] The "generative AI model means for calculating the optimal purchase plan based on collected price information" refers to an artificial intelligence model for calculating the optimal purchase plan based on collected price data and user request information, and includes a calculation algorithm that takes into account price comparison and point redemption.

[0070] The "means for providing the calculated purchase plan to the user's device" is a system for notifying the user of the optimal purchase plan calculated by the generative AI model, and has the function of delivering information to the user's device via the Internet.

[0071] The "means for the user to input additional information" is an interface that allows the user to input specific conditions or wishes in addition to the shopping list, and has the function of recording the user's specific requests.

[0072] "A means for collecting inventory and price information from multiple websites on the Internet and reflecting it in the optimal purchase plan" is a system that calculates the optimal purchase plan in real time using inventory and price information collected from multiple sites.

[0073] The present invention relates to a system that allows a user to input a list of products they wish to purchase and proposes an optimal purchasing plan. A method for implementing this system will be described in detail below using the procedures and configuration shown below.

[0074] First, the user uses a user terminal to input a list of items they wish to purchase. Specifically, the user uses an internet-connected device such as a smartphone or PC to input the list of items they wish to purchase into a dedicated app or web form. For example, the user can input items such as "potatoes," "carrots," "onions," "meat," and "roux," and can also enter additional information such as "I'd like to add apples as a secret ingredient."

[0075] Next, the server receives and analyzes the request from the user. The server analyzes the received data and extracts information about the entered product. Based on the analyzed data, the server issues a command to launch the crawler bot.

[0076] Crawler bots crawl multiple websites on the Internet and automatically collect the latest price and stock information for products. Crawler bots collect data such as product names, prices, stock status, and store information.

[0077] The collected price information is sent to a server, which inputs it into a generative AI model. The generative AI model calculates the optimal purchase plan based on the collected price information, the user's request, and additional information. The generative AI model performs its calculations by taking into account price comparisons, inventory information, price comparisons between multiple stores, specific point reward services, and more.

[0078] After calculating the optimal purchase plan, the server sends the calculation results to the user's terminal, where the user can check the proposed purchase plan and purchase the products at the specified store or online shop.

[0079] As a concrete example, consider the case where a user enters "I want to buy curry ingredients at the cheapest price." When the user enters "potatoes," "carrots," "onions," "meat," "roux," and "apples" into a list, the server receives this and launches a crawler bot. The crawler bot collects price and stock information for each item, and the generative AI model calculates the optimal purchase plan. For example, it can suggest the nearby supermarket or online shop with the lowest total price, and also display the actual cost including the initial point reward.

[0080] In this way, users can purchase multiple products at the lowest possible cost and most efficiently.

[0081] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0082] Step 1:

[0083] The user inputs a list of items they wish to purchase.

[0084] Specific operation: The user accesses a dedicated app or web form using a smartphone or PC and inputs a list of products such as "potatoes," "carrots," "onions," "meat," and "roux." They can also add additional information such as "I'd like to add apples as a secret ingredient."

[0085] Input: List of items you wish to purchase and additional information.

[0086] Output: Data entered into the input form.

[0087] Step 2:

[0088] The server receives and analyzes the request from the user.

[0089] How it works: The server receives the data sent from the user device and analyzes its contents to extract information about each product and additional information. The analysis is performed using a text processing algorithm.

[0090] Input: Data submitted by the user (list of products and additional information).

[0091] Output: A list of parsed products and additional information.

[0092] Step 3:

[0093] The server launches the crawler bot.

[0094] Specific operation: Based on the analyzed data, the server issues a command to launch a crawler bot, which then crawls designated websites and automatically collects the latest product price and stock information.

[0095] Input: A parsed list of products.

[0096] Output: Instructions to launch the crawler bot.

[0097] Step 4:

[0098] Crawler bots crawl websites and collect product price information.

[0099] Specific operation: The crawler bot accesses each website and collects price and stock information for products such as "potatoes" and "carrots" using web scraping technology.

[0100] Input: A list of specified products.

[0101] Output: Up-to-date price and availability information for each product.

[0102] Step 5:

[0103] The collected price information is fed into a generative AI model.

[0104] How it works: The crawler bot sends the collected price information to the server, which then inputs it into the generative AI model, which preprocesses the data and creates an input dataset for calculating the optimal purchase plan.

[0105] Input: Collected pricing and inventory information.

[0106] Output: The dataset that is input to the generative AI model.

[0107] Step 6:

[0108] A generative AI model calculates the optimal purchase plan.

[0109] How it works: Based on collected pricing information, the user's request, and additional information, the generative AI model calculates the optimal purchase plan, taking into account price comparisons, inventory availability, and multiple purchasing options.

[0110] Input: Input datasets (pricing information, inventory information, user requests).

[0111] Output: Best buy plan.

[0112] Step 7:

[0113] The server sends the calculation results to the user terminal.

[0114] Specific operation: The server receives the calculation results of the optimal purchase plan from the generative AI model and sends them to the user's device. The user receives and displays this data on their own device.

[0115] Enter: Best buy plan.

[0116] Output: The optimal purchase plan sent to the user device.

[0117] Step 8:

[0118] The user checks the purchase plan and purchases the product at the specified store or online shop.

[0119] Specific operation: The user checks the purchase plan sent on the device and purchases the product from the recommended store or online shop. The purchase plan describes the most economical and efficient way to purchase the product.

[0120] Input: The purchase plan displayed on the user's device.

[0121] Output: The actual action of purchasing the product.

[0122] (Application example 1)

[0123] 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."

[0124] In today's world, when users purchase products from multiple online shopping sites, it is extremely difficult to compare prices and find the optimal purchase plan. At the same time, they must also be able to respond to detailed requests based on product inventory information and specific conditions. In such situations, users end up spending a great deal of time and effort, resulting in a decrease in purchasing efficiency. To solve this problem, a system is needed that allows users to easily list products and automatically provides the optimal purchase plan.

[0125] 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.

[0126] In this invention, the server includes a means for a user to input a list of products they wish to purchase, a crawler bot means for collecting product price information from multiple websites on the Internet, a generation AI model means for calculating an optimal purchase plan based on the collected price information and additional information, a means for providing the calculated purchase plan to the user, and an application means for being installed on a smartphone. This allows the user to easily input a list of products they wish to purchase and quickly obtain an optimal purchase plan that includes additional conditions.

[0127] The term "means for a user to input a list of products that the user wishes to purchase" refers to an interface or function that allows the user to electronically input a list of products that the user wishes to purchase.

[0128] "Crawler bot means for collecting product price information from multiple websites on the Internet" refers to programs and functions for automatically crawling multiple websites on the Internet and collecting the latest product price information.

[0129] "Generative AI model means for calculating the optimal purchase plan based on collected price information and additional information" refers to the calculation function of an artificial intelligence model for calculating the optimal purchase plan using collected price information and additional information provided by the user.

[0130] "Means for providing the calculated purchase plan to the user" refers to an interface or function for presenting the optimal purchase plan calculated by the generative AI model in a form that is accessible to the user.

[0131] "Application means installed on a smartphone" refers to a software application that is downloaded and installed on a smartphone and can perform a series of operations from inputting a list of products desired to be purchased to being provided with the most suitable purchase plan.

[0132] "Means for collecting inventory information from nearby stores and online sales sites and reflecting it in an optimal purchasing plan" refers to functions and programs for collecting inventory information from nearby physical stores and online sales sites and incorporating that information into an optimal purchasing plan.

[0133] To implement the present invention, the following configuration and processing procedure are followed.

[0134] First, a user inputs a list of items they wish to purchase using an application installed on their smartphone. This application provides an interface that transmits the information the user inputs to the server. As a specific example, a user can input a list of items such as "potatoes," "carrots," "onions," "meat," and "roux," and then add additional information such as "I would like to add apples as a secret ingredient."

[0135] The server analyzes the received data and launches a crawler bot, which crawls multiple websites across the Internet to gather up-to-date pricing and availability information for the specified product. The crawler bot uses, for example, the Requests and BeautifulSoup libraries to extract the required information from the web pages.

[0136] The collected pricing information and additional information is sent back to the server and then fed into a generative AI model, which uses an artificial intelligence model such as OpenAI's GPT-3 to calculate the optimal purchase plan. An example prompt for this is below:

[0137] "Plan the best purchase plan for the following items:

[0138] Potatoes: 100 yen, carrots: 50 yen, onions: 80 yen, meat: 500 yen, roux: 200 yen, apples: 150 yen

[0139] Additional information: I like to add apples as a secret ingredient.

[0140] When calculating the optimal purchase plan, the generative AI model takes into account price and availability information, as well as specific rewards programs and user-defined conditions.

[0141] The calculated optimal purchase plan is sent from the server to the application, where the user can check it on their smartphone. The user can then purchase products from the designated online shopping site or a nearby store according to the purchase plan.

[0142] For example, if a user types "I want to buy curry ingredients at the cheapest price," a crawler bot will collect the prices of each item, and a generative AI model will calculate the optimal plan. For example, it will suggest the nearby store with the cheapest total price, and it will also display the actual cost including the initial point reward.

[0143] This allows users to significantly reduce the time and effort spent on price comparisons and planning purchases, enabling them to shop in an economical and efficient manner.

[0144] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0145] Step 1:

[0146] The user launches the application installed on their smartphone and inputs a list of products they wish to purchase. They can also input additional conditions as needed. As input, the user provides a list of products such as "potatoes," "carrots," "onions," "meat," and "roux," along with an additional condition such as "I would like to add apple as a secret ingredient." Based on this input, the application sends the data to the server.

[0147] Step 2:

[0148] The server receives and analyzes the data sent by the user. Specifically, it parses the received data to extract each product and additional conditions, and prepares to launch the crawler bot. It receives the JSON data entered by the user as input, extracts the product list and additional conditions, and generates structured data for launching the crawler bot.

[0149] Step 3:

[0150] The server launches a crawler bot to collect the latest product price information from multiple websites on the Internet. The crawler bot accesses each website and parses the HTML to extract price information. It receives a list of products as input and generates data containing price information for each product as output.

[0151] Step 4:

[0152] The server inputs the collected price information into the generative AI model. Specifically, the collected price information and the user's additional conditions are formatted as a prompt sentence and sent to the generative AI model to calculate the optimal purchase plan. The input is the price information and additional conditions, and the output is the optimal purchase plan.

[0153] Step 5:

[0154] The generative AI model calculates the optimal purchase plan. The calculation takes into account collected price information, inventory information, additional user conditions, point redemption information, etc. It receives price information and user conditions as input, and generates the optimal purchase plan in text format as output. For example, a detailed purchase plan is provided in the form of "Potatoes: 100 yen at store A, Carrots: 50 yen at store B."

[0155] Step 6:

[0156] The server sends the calculated optimal purchase plan to the user's smartphone. It receives the purchase plan from the generative AI model as input and generates data to display the plan on the user's device as output. This allows the user to check the optimal purchase plan on their smartphone.

[0157] Step 7:

[0158] The user purchases products at the specified store or online shopping site based on the purchase plan notified through the application. This eliminates the need for price comparisons and stock confirmation, enabling economical shopping. User behavior includes actually making a purchase using the optimal purchase plan provided by the application.

[0159] 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.

[0160] The present invention is a system that allows a user to input a list of items they wish to purchase and proposes the optimal purchase plan, and also has the ability to recognize the user's emotions and adjust the proposal content based on that information. A method for implementing this system will be described in detail using the following procedures and configuration.

[0161] First, the user uses the user terminal to input a list of items they wish to purchase. Specifically, the user uses a screen to input items such as "potatoes," "carrots," "onions," "meat," and "roux." Additional information can also be entered, such as "I'd like to add apple as a secret ingredient." Additionally, the user terminal is equipped with an emotion engine that analyzes the user's emotions from their facial expressions and voice, and sends that data to the system.

[0162] Next, the server receives the user's request and emotional data and analyzes the content. Based on the analyzed data, the server launches a crawler bot that crawls multiple websites on the Internet and automatically collects the latest price information for each product. The collected price information is then sent back to the server, which then inputs it into the generative AI model.

[0163] The generative AI model receives collected price information, user requests, and emotional data as input and calculates the optimal purchase plan. The generative AI model generates the most economical plan by taking into account the price of each product, inventory information, price comparisons between multiple stores, and specific point reward services. If the user is feeling dissatisfied or stressed, the emotion engine adjusts the suggestions to improve user satisfaction, such as suggesting simpler options by taking their emotions into consideration.

[0164] The calculated optimal purchase plan is sent by the server to the user's terminal. The user can then check the plan on their own terminal and purchase the products at the specified stores. This process not only enables the user to purchase multiple products at the lowest cost and most efficiently, but also allows the user to receive optimal suggestions based on their emotions.

[0165] As a concrete example, consider the case where a user inputs "I want to buy curry ingredients at the cheapest price." If the user inputs "potatoes," "carrots," "onions," "meat," "roux," and "apples" into a list, and the user's emotional data indicates "stress," the server not only launches a crawler bot to collect price information for each item, but also takes this emotional data into account and inputs it into the generative AI model. The generative AI model generates a simple and intuitive purchasing plan to prevent the user from feeling stressed, and the server sends this to the user's device. The user can purchase products in the most economical and efficient way possible, without feeling stressed.

[0166] The processing flow will be explained below.

[0167] Step 1:

[0168] The user uses a terminal to input the items they wish to purchase. The user inputs a list of items such as "potatoes," "carrots," "onions," "meat," and "roux." The user also inputs additional information such as "add apples as a secret ingredient."

[0169] Step 2:

[0170] The emotion engine installed in the device analyzes the user's facial expressions and voice and generates emotion data. For example, if it is determined that the user is feeling stressed, emotion data containing that information is sent from the device to the server.

[0171] Step 3:

[0172] The server analyzes the list of desired products and emotion data received from the terminal. The server breaks down the user's request, extracts the name of each product and additional information, and stores the emotion data separately.

[0173] Step 4:

[0174] The server launches a crawler bot, which crawls multiple websites on the Internet to gather the latest price information for the specified product.

[0175] Step 5:

[0176] The crawler bot sends the collected price information to a server, which stores it in a database.

[0177] Step 6:

[0178] The server launches a generative AI model based on the stored price information. The generative AI model receives price information, user requests, additional information, and emotional data as input data and calculates the optimal purchase plan.

[0179] Step 7:

[0180] The server receives the optimal purchase plan calculated by the generative AI model. The server then takes emotional data into account and adjusts the proposal to avoid stress for the user. For example, it prioritizes simple plans that minimize complex store-to-store travel.

[0181] Step 8:

[0182] The server sends the adjusted purchase plan to the user's terminal, where the user can check the plan.

[0183] Step 9:

[0184] The user purchases products at the designated store based on the proposed purchase plan, which not only allows the user to purchase products in the most economical and efficient way, but also increases emotional satisfaction.

[0185] Example 2

[0186] 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."

[0187] Conventional online shopping systems have difficulty generating optimal purchase plans simply by inputting the products a user wishes to purchase. Furthermore, they lack the functionality to provide purchase plans that take into account the user's emotions and reduce stress and dissatisfaction. As a result, there are problems with lower user satisfaction and a decrease in willingness to purchase.

[0188] 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.

[0189] In this invention, the server includes a means for a user to input a list of products they wish to purchase, a means for acquiring user emotion data, a crawler bot means for collecting product price information from websites, a generative AI model means for calculating an optimal purchase plan based on the collected price information and user emotion data, and a means for providing the calculated purchase plan to the user. This makes it possible to provide the most economical and efficient purchase plan while taking user emotions into consideration, thereby improving user satisfaction.

[0190] The "means for a user to input a list of products desired for purchase" refers to a means for a user to provide a list of products desired by the user to the system through text input, voice input, or other input method.

[0191] The "means for acquiring user emotion data" is a means for analyzing emotions from the user's facial expressions, voice, etc., and acquiring the analysis results as data.

[0192] The "crawler bot means for collecting product price information from websites" is a program that crawls multiple websites on the Internet and automatically collects the latest price information for each product.

[0193] The "generative AI model means for calculating an optimal purchase plan based on collected price information and user emotional data" is an artificial intelligence model for receiving collected price information and user emotional data as input data and generating an optimal purchase plan.

[0194] The "means for providing the calculated purchase plan to the user" is a means for transmitting the generated purchase plan to the user terminal so that the user can check the plan.

[0195] The present invention is a system that allows users to input a list of products they wish to purchase and proposes the optimal purchase plan, and also has the function of recognizing the user's emotions and adjusting the proposal content based on that information. In implementing this system, the user terminal and the server mainly work together.

[0196] System configuration and hardware / software used

[0197] First, the user uses the user terminal to input a list of products they wish to purchase. Specifically, they use a screen where they can input products such as "potatoes," "carrots," "onions," "meat," and "roux." In addition to the product list, the user can also input additional information such as "I'd like to add apples as a secret ingredient."

[0198] The user device is equipped with an emotion engine that analyzes emotions from the user's facial expressions and voice and sends the data to a server. The emotion engine's hardware includes a camera and microphone, and the software uses an emotion analysis program.

[0199] Next, the server receives the user's request and emotional data and analyzes the content. This analysis is performed using a database and analytical algorithms. Based on this analyzed data, the server launches a crawler bot, which crawls multiple websites on the Internet and automatically collects the latest price information for each product. The collected price information is then sent back to the server.

[0200] The server inputs price information, user requests, and emotional data into a generative AI model. The generative AI model uses technologies such as OpenAI's GPT-4 to calculate the most economical purchase plan, taking into account each product's price, inventory information, price comparisons between multiple stores, and specific point reward services. Additionally, if the user is feeling dissatisfied or stressed, the emotion engine will take their emotions into consideration and suggest simpler options, thereby improving user satisfaction.

[0201] The calculated optimal purchase plan is sent by the server to the user's terminal. The user can then check this plan on their own terminal and purchase the products at the specified store. This not only enables the user to purchase multiple products at the lowest cost and most efficiently, but also allows the user to receive optimal suggestions based on their emotions.

[0202] Examples of concrete examples and prompts

[0203] As a concrete example, consider the case where a user inputs "I want to buy curry ingredients at the cheapest price." If the user inputs "potatoes," "carrots," "onions," "meat," "roux," and "apples" into a list, and the user's emotional data indicates "stress," the server not only launches a crawler bot to collect price information for each item, but also takes this emotional data into account and inputs it into the generative AI model. The generative AI model generates a simple and intuitive purchasing plan to prevent the user from feeling stressed, and the server sends this to the user's device. The user can purchase products in the most economical and efficient way possible, without feeling stressed.

[0204] Example prompt sentence:

[0205] "Generate a plan to purchase ingredients for curry at the lowest price. The purchase list is potatoes, carrots, onions, meat, roux, and apples. User sentiment data indicates stress. Provide a simple and intuitive purchasing plan."

[0206] As a result, the present invention can improve user satisfaction and provide an optimal purchasing experience.

[0207] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0208] Step 1:

[0209] The user inputs a list of products that he or she wishes to purchase using the user terminal.

[0210] Specifically, the user enters items such as "potatoes," "carrots," "onions," "meat," and "roux" into an input form on the terminal screen. A shopping list is generated based on the input data and sent to the system.

[0211] Step 2:

[0212] The device acquires emotional data and analyzes the user's facial expressions and voice.

[0213] Specifically, the device's camera and microphone capture the user's facial expressions and voice, which are then analyzed by the emotion engine. Emotional data such as "stress" is generated as a result of the analysis and sent to the server.

[0214] Step 3:

[0215] The server receives the request and emotion data and analyzes the content.

[0216] Specifically, the server receives the purchase list and emotion data sent by the user and analyzes them using an analysis algorithm. The input data are the purchase list and emotion data, and the output is the analyzed information.

[0217] Step 4:

[0218] The server launches a crawler bot that crawls multiple websites on the Internet to collect the latest price information.

[0219] Specifically, the crawler bot patrols designated e-commerce sites and collects the latest price information for items such as potatoes, carrots, and onions. This collected price information is then saved on the server and output.

[0220] Step 5:

[0221] The server inputs collected price information, user requests, and sentiment data into a generative AI model.

[0222] Specifically, the server inputs the collected price information, request information from the user, and emotional data into a generative AI model (e.g., OpenAI's GPT-4). The generative AI model processes this data and calculates the optimal purchase plan. The input data are price information, user request, and emotional data, and the output is the generated purchase plan.

[0223] Step 6:

[0224] The server transmits the calculated purchase plan to the user terminal.

[0225] Specifically, the server sends the purchase plan created by the generative AI model to the user's device. The optimal purchase method for multiple products is displayed on the device. The input data is the generated purchase plan, and the output is the plan information displayed on the user's device.

[0226] Step 7:

[0227] The user confirms the purchase plan and purchases the product at the specified store.

[0228] Specifically, the user checks the purchase plan displayed on the terminal and purchases products at each store according to that plan. Specific store information is displayed as the optimal purchase method, such as "purchase potatoes at supermarket A" and "purchase carrots at supermarket B." The input data is the displayed purchase plan, and the output is the products actually purchased by the user.

[0229] (Application example 2)

[0230] 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."

[0231] Current shopping support systems propose optimal purchase plans based on product lists and price information entered by users, but because they do not take into account the user's emotional state, they may produce proposals that are unsatisfying. Furthermore, because they do not take into consideration users who are stressed or dissatisfied, there is a problem that the user experience is not improved. The objective of this invention is to provide a more satisfying shopping experience by analyzing the user's emotions and making proposals accordingly.

[0232] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0233] In this invention, the server includes means for a user to input a list of products they wish to purchase, crawler bot means for collecting product price information from websites, generation AI model means for calculating an optimal purchase plan based on the collected price information, means for analyzing the user's emotional data using an emotion analysis engine, and means for adjusting and providing the calculated purchase plan based on the user's emotions. This makes it possible to propose an optimal purchase plan that takes the user's emotional state into consideration, improving the user experience.

[0234] The "means for the user to input a list of products that the user wishes to purchase" is an interface that allows the user to input the products that the user wishes to purchase in list form.

[0235] A "crawler bot means for collecting product price information from websites" is a software robot that crawls websites on the Internet and automatically collects product price information.

[0236] The "generative AI model means for calculating the optimal purchase plan based on collected price information" is an artificial intelligence model that receives collected product price information as input data and calculates the optimal purchase plan.

[0237] The "means for analyzing the user's emotional data using an emotional analysis engine" refers to software and hardware for analyzing the user's facial expressions and voice and acquiring emotional data.

[0238] The "means for adjusting and providing a calculated purchase plan based on the user's emotions" refers to a means for adjusting a calculated purchase plan in consideration of the user's emotion data and providing the plan to the user.

[0239] The present invention is a system that allows a user to input a list of products they wish to purchase and proposes the optimal purchase plan, and also has the function of recognizing the user's emotions and adjusting the proposal content based on that information. The specific configuration for implementing this system is shown below.

[0240] First, a user uses a smartphone to input a list of products they wish to purchase. This smartphone is equipped with an emotion analysis engine that uses a camera and microphone to analyze the user's facial expressions and voice to obtain emotional data. The product list and emotional data input by the user are then sent to the server.

[0241] The server analyzes the received user request and emotional data, and launches a crawler bot to collect product price information from the Internet. This crawler bot patrols designated websites and obtains the latest price information for, for example, potatoes, carrots, onions, meat, roux, and apples.

[0242] The collected price information is sent to a server and input to a generative AI model. This generative AI model receives price information, user requests, and sentiment data as input data and calculates the optimal purchase plan. The generative AI model used here is, for example, OpenAI's text generation API.

[0243] The calculated purchase plan is adjusted taking into account the user's emotional data. If the user is feeling stressed, a simple and intuitive purchase plan is proposed to improve the user's satisfaction. This adjusted purchase plan is sent from the server to the user's device.

[0244] As a specific example, consider the case where a user requests, "I want to buy curry ingredients at the lowest price." The product list entered by the user includes potatoes, carrots, onions, meat, roux, and apples. If the emotional data indicates "stress," the server launches a crawler bot to collect price information for these items. The collected information is input into a generative AI model, which generates a simple and intuitive purchase plan to prevent the user from feeling stressed. An example of a prompt sentence is shown below.

[0245] Example prompt sentence:

[0246] "Products desired: {'Potatoes': '100 yen', 'Carrots': '50 yen', 'Onions': '30 yen', 'Meat': '200 yen', 'Rou': '150 yen', 'Apples': '300 yen'} User emotion: Stressed Please generate the optimal purchase plan."

[0247] According to this invention, it is possible to propose an optimal purchase plan taking into consideration the user's feelings, thereby greatly improving user satisfaction.

[0248] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0249] Step 1:

[0250] The user inputs a list of products they wish to purchase using their smartphone.

[0251] The input list may include, for example, "potatoes," "carrots," "onions," "meat," "roux," and "apples." List data is generated based on the user's input and sent from the terminal to the server. The output is the list data of the input products.

[0252] Step 2:

[0253] The user's device then uses its built-in camera and microphone to capture the user's facial expressions and voice.

[0254] Based on the acquired data, the emotion analysis engine analyzes the user's emotion data and obtains the analysis results (emotion data). This emotion data is also sent from the device to the server. The output is the user's emotion data.

[0255] Step 3:

[0256] The server receives and analyzes the user's list of desired products and emotion data.

[0257] Based on the analyzed data, the server issues a command to launch a crawler bot. The crawler bot crawls designated websites and collects the latest price information for each product. The input is the list data of products desired for purchase and emotion data, and the output is the collected price information.

[0258] Step 4:

[0259] The collected price information is sent to a server and stored in a database.

[0260] The server uses this price information to construct input data for the generative AI model. The input data to the generative AI model includes product names, prices, and user sentiment data. The output is the input data for the generative AI model.

[0261] Step 5:

[0262] The server inputs price information stored in a database and user emotion data into the generative AI model.

[0263] The generative AI model calculates the optimal purchase plan based on input data. The calculation process takes into account price comparisons for each product, inventory information, point reward services, and other factors. The output is the calculated optimal purchase plan.

[0264] Step 6:

[0265] The server adjusts the optimal purchase plan calculated by the generative AI model based on the user's emotional data.

[0266] For example, if the user is feeling "stressed," the system adjusts the calculated plan to be simple and intuitive. The input is the calculated purchase plan and the user's emotional data, and the output is an adjusted purchase plan based on the emotion.

[0267] Step 7:

[0268] The server sends the adjusted optimal purchase plan to the user's smartphone.

[0269] The user can check this purchase plan on their own terminal and purchase the product at the specified store. The output is the final purchase plan, which is the output the user receives.

[0270] This not only enables users to purchase multiple products at the lowest cost and most efficiently, but also allows users to receive optimal suggestions based on their emotions.

[0271] 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.

[0272] 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.

[0273] 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.

[0274] [Second embodiment]

[0275] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0276] 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.

[0277] 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).

[0278] 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.

[0279] 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.

[0280] 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).

[0281] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0282] 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.

[0283] 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.

[0284] 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.

[0285] 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.

[0286] 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."

[0287] The present invention provides a system that allows a user to input a list of products they wish to purchase and suggests an optimal purchasing plan. A method for implementing this system will be described in detail below using the procedures and configuration shown below.

[0288] First, the user uses the user terminal to input a list of products they wish to purchase. Specifically, the user uses a screen to input multiple products such as "potatoes," "carrots," "onions," "meat," and "roux." In addition, the user can input additional information such as "I would like to add apples as a secret ingredient."

[0289] Next, the server receives the user's request and analyzes its contents. Based on the analyzed data, the server launches a crawler bot. The crawler bot then crawls multiple websites on the Internet and automatically collects the latest price information for each product.

[0290] The collected price information is sent back to the server, which then inputs it into the generative AI model. The generative AI model calculates the optimal purchase plan based on the collected price information and the user's request (including additional information). The generative AI model also takes into account the price of each product, inventory information, price comparisons between multiple stores, and specific point reward services to generate the most economical plan.

[0291] The server then sends the calculated optimal purchase plan to the user's terminal. The user can then check the plan on their own terminal and purchase the products at the designated stores. This process allows the user to purchase multiple products at the lowest cost and most efficiently.

[0292] As a concrete example, consider the case where a user enters "I want to buy curry ingredients at the cheapest price." When the user enters "potatoes," "carrots," "onions," "meat," "roux," and "apples" into a list, the server receives this and launches a crawler bot. The crawler bot collects price information for each item, and the generative AI model calculates the optimal plan. For example, it can suggest the nearby supermarket with the lowest total price and also display the actual cost including the initial point reward.

[0293] This saves users the time and effort of comparing prices themselves, allowing them to shop in the most economical way possible.

[0294] The processing flow will be explained below.

[0295] Step 1:

[0296] The user uses a terminal to input the items they wish to purchase. Specifically, the user launches the application's input screen and inputs a list of ingredients such as "potatoes," "carrots," "onions," "meat," and "roux." They can also input additional information, such as "apple as a secret ingredient."

[0297] Step 2:

[0298] The terminal formats the input data and sends it to the server. The terminal compiles the list of products desired for purchase and additional information into one request data.

[0299] Step 3:

[0300] The server analyzes the request received from the terminal. Specifically, the server breaks down the request data and extracts the name of each product and additional information.

[0301] Step 4:

[0302] The server launches a crawler bot, which crawls multiple websites on the Internet and collects price information for the specified product.

[0303] Step 5:

[0304] The crawler bot sends the collected price information to a server, which receives it and stores it in a database.

[0305] Step 6:

[0306] The server launches a generative AI model based on the stored price information, which receives the price information and additional information as input and calculates the optimal purchase plan.

[0307] Step 7:

[0308] The server receives the optimal purchase plan calculated by the generative AI model, formats the plan, and prepares it for delivery to the user.

[0309] Step 8:

[0310] The server sends the calculated purchase plan to the user terminal, where the user can check the proposed plan.

[0311] Step 9:

[0312] The user purchases products at the specified store based on the proposed purchase plan, enabling the user to make the most economical and efficient purchases according to the information presented.

[0313] Example 1

[0314] 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."

[0315] The problem that this invention aims to solve is to provide the most economical and efficient purchase plan by allowing users to easily input a list of products they wish to purchase and quickly collecting the latest price information from multiple websites, thereby significantly reducing the time and effort required for users to compare product prices.

[0316] 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.

[0317] In this invention, the server includes a means for a user to input a list of products they wish to purchase, a means for the server to receive and analyze requests from the user, a means for a crawler bot to crawl websites and collect product price information, a generating AI model means for calculating an optimal purchase plan based on the collected price information, and a means for providing the calculated purchase plan to a user terminal, thereby enabling a user to purchase multiple products in the most economical and efficient manner.

[0318] The "means by which users input a list of products they wish to purchase" refers to an interface for users to input information about products they wish to purchase, and is composed of an application or web form using a device such as a smartphone or PC.

[0319] "The means by which the server receives and analyzes requests from users" refers to a program on the server that receives user input data and analyzes its contents, and has the function of extracting and classifying request data.

[0320] "Means for crawler bots to crawl websites and collect product price information" refers to a software program that automatically crawls multiple websites on the Internet and collects price and inventory information about products.

[0321] The "generative AI model means for calculating the optimal purchase plan based on collected price information" refers to an artificial intelligence model for calculating the optimal purchase plan based on collected price data and user request information, and includes a calculation algorithm that takes into account price comparison and point redemption.

[0322] The "means for providing the calculated purchase plan to the user's device" is a system for notifying the user of the optimal purchase plan calculated by the generative AI model, and has the function of delivering information to the user's device via the Internet.

[0323] The "means for the user to input additional information" is an interface that allows the user to input specific conditions or wishes in addition to the shopping list, and has the function of recording the user's specific requests.

[0324] "A means for collecting inventory and price information from multiple websites on the Internet and reflecting it in the optimal purchase plan" is a system that calculates the optimal purchase plan in real time using inventory and price information collected from multiple sites.

[0325] The present invention relates to a system that allows a user to input a list of products they wish to purchase and proposes an optimal purchasing plan. A method for implementing this system will be described in detail below using the procedures and configuration shown below.

[0326] First, the user uses a user terminal to input a list of items they wish to purchase. Specifically, the user uses an internet-connected device such as a smartphone or PC to input the list of items they wish to purchase into a dedicated app or web form. For example, the user can input items such as "potatoes," "carrots," "onions," "meat," and "roux," and can also enter additional information such as "I'd like to add apples as a secret ingredient."

[0327] Next, the server receives and analyzes the request from the user. The server analyzes the received data and extracts information about the entered product. Based on the analyzed data, the server issues a command to launch the crawler bot.

[0328] Crawler bots crawl multiple websites on the Internet and automatically collect the latest price and stock information for products. Crawler bots collect data such as product names, prices, stock status, and store information.

[0329] The collected price information is sent to a server, which inputs it into a generative AI model. The generative AI model calculates the optimal purchase plan based on the collected price information, the user's request, and additional information. The generative AI model performs its calculations by taking into account price comparisons, inventory information, price comparisons between multiple stores, specific point reward services, and more.

[0330] After calculating the optimal purchase plan, the server sends the calculation results to the user's terminal, where the user can check the proposed purchase plan and purchase the products at the specified store or online shop.

[0331] As a concrete example, consider the case where a user enters "I want to buy curry ingredients at the cheapest price." When the user enters "potatoes," "carrots," "onions," "meat," "roux," and "apples" into a list, the server receives this and launches a crawler bot. The crawler bot collects price and stock information for each item, and the generative AI model calculates the optimal purchase plan. For example, it can suggest the nearby supermarket or online shop with the lowest total price, and also display the actual cost including the initial point reward.

[0332] In this way, users can purchase multiple products at the lowest possible cost and most efficiently.

[0333] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0334] Step 1:

[0335] The user inputs a list of items they wish to purchase.

[0336] Specific operation: The user accesses a dedicated app or web form using a smartphone or PC and inputs a list of products such as "potatoes," "carrots," "onions," "meat," and "roux." They can also add additional information such as "I'd like to add apples as a secret ingredient."

[0337] Input: List of items you wish to purchase and additional information.

[0338] Output: Data entered into the input form.

[0339] Step 2:

[0340] The server receives and analyzes the request from the user.

[0341] How it works: The server receives the data sent from the user device and analyzes its contents to extract information about each product and additional information. The analysis is performed using a text processing algorithm.

[0342] Input: Data submitted by the user (list of products and additional information).

[0343] Output: A list of parsed products and additional information.

[0344] Step 3:

[0345] The server launches the crawler bot.

[0346] Specific operation: Based on the analyzed data, the server issues a command to launch a crawler bot, which then crawls designated websites and automatically collects the latest product price and stock information.

[0347] Input: A parsed list of products.

[0348] Output: Instructions to launch the crawler bot.

[0349] Step 4:

[0350] Crawler bots crawl websites and collect product price information.

[0351] Specific operation: The crawler bot accesses each website and collects price and stock information for products such as "potatoes" and "carrots" using web scraping technology.

[0352] Input: A list of specified products.

[0353] Output: Up-to-date price and availability information for each product.

[0354] Step 5:

[0355] The collected price information is fed into a generative AI model.

[0356] How it works: The crawler bot sends the collected price information to the server, which then inputs it into the generative AI model, which preprocesses the data and creates an input dataset for calculating the optimal purchase plan.

[0357] Input: Collected pricing and inventory information.

[0358] Output: The dataset that is input to the generative AI model.

[0359] Step 6:

[0360] A generative AI model calculates the optimal purchase plan.

[0361] How it works: Based on collected pricing information, the user's request, and additional information, the generative AI model calculates the optimal purchase plan, taking into account price comparisons, inventory availability, and multiple purchasing options.

[0362] Input: Input datasets (pricing information, inventory information, user requests).

[0363] Output: Best buy plan.

[0364] Step 7:

[0365] The server sends the calculation results to the user terminal.

[0366] Specific operation: The server receives the calculation results of the optimal purchase plan from the generative AI model and sends them to the user's device. The user receives and displays this data on their own device.

[0367] Enter: Best buy plan.

[0368] Output: The optimal purchase plan sent to the user device.

[0369] Step 8:

[0370] The user checks the purchase plan and purchases the product at the specified store or online shop.

[0371] Specific operation: The user checks the purchase plan sent on the device and purchases the product from the recommended store or online shop. The purchase plan describes the most economical and efficient way to purchase the product.

[0372] Input: The purchase plan displayed on the user's device.

[0373] Output: The actual action of purchasing the product.

[0374] (Application example 1)

[0375] 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."

[0376] In today's world, when users purchase products from multiple online shopping sites, it is extremely difficult to compare prices and find the optimal purchase plan. At the same time, they must also be able to respond to detailed requests based on product inventory information and specific conditions. In such situations, users end up spending a great deal of time and effort, resulting in a decrease in purchasing efficiency. To solve this problem, a system is needed that allows users to easily list products and automatically provides the optimal purchase plan.

[0377] 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.

[0378] In this invention, the server includes a means for a user to input a list of products they wish to purchase, a crawler bot means for collecting product price information from multiple websites on the Internet, a generation AI model means for calculating an optimal purchase plan based on the collected price information and additional information, a means for providing the calculated purchase plan to the user, and an application means for being installed on a smartphone. This allows the user to easily input a list of products they wish to purchase and quickly obtain an optimal purchase plan that includes additional conditions.

[0379] The term "means for a user to input a list of products that the user wishes to purchase" refers to an interface or function that allows the user to electronically input a list of products that the user wishes to purchase.

[0380] "Crawler bot means for collecting product price information from multiple websites on the Internet" refers to programs and functions for automatically crawling multiple websites on the Internet and collecting the latest product price information.

[0381] "Generative AI model means for calculating the optimal purchase plan based on collected price information and additional information" refers to the calculation function of an artificial intelligence model for calculating the optimal purchase plan using collected price information and additional information provided by the user.

[0382] "Means for providing the calculated purchase plan to the user" refers to an interface or function for presenting the optimal purchase plan calculated by the generative AI model in a form that is accessible to the user.

[0383] "Application means installed on a smartphone" refers to a software application that is downloaded and installed on a smartphone and can perform a series of operations from inputting a list of products desired to be purchased to being provided with the most suitable purchase plan.

[0384] "Means for collecting inventory information from nearby stores and online sales sites and reflecting it in an optimal purchasing plan" refers to functions and programs for collecting inventory information from nearby physical stores and online sales sites and incorporating that information into an optimal purchasing plan.

[0385] To implement the present invention, the following configuration and processing procedure are followed.

[0386] First, a user inputs a list of items they wish to purchase using an application installed on their smartphone. This application provides an interface that transmits the information the user inputs to the server. As a specific example, a user can input a list of items such as "potatoes," "carrots," "onions," "meat," and "roux," and then add additional information such as "I would like to add apples as a secret ingredient."

[0387] The server analyzes the received data and launches a crawler bot, which crawls multiple websites across the Internet to gather up-to-date pricing and availability information for the specified product. The crawler bot uses, for example, the Requests and BeautifulSoup libraries to extract the required information from the web pages.

[0388] The collected pricing information and additional information is sent back to the server and then fed into a generative AI model, which uses an artificial intelligence model such as OpenAI's GPT-3 to calculate the optimal purchase plan. An example prompt for this is below:

[0389] "Plan the best purchase plan for the following items:

[0390] Potatoes: 100 yen, carrots: 50 yen, onions: 80 yen, meat: 500 yen, roux: 200 yen, apples: 150 yen

[0391] Additional information: I like to add apples as a secret ingredient.

[0392] When calculating the optimal purchase plan, the generative AI model takes into account price and availability information, as well as specific rewards programs and user-defined conditions.

[0393] The calculated optimal purchase plan is sent from the server to the application, where the user can check it on their smartphone. The user can then purchase products from the designated online shopping site or a nearby store according to the purchase plan.

[0394] For example, if a user types "I want to buy curry ingredients at the cheapest price," a crawler bot will collect the prices of each item, and a generative AI model will calculate the optimal plan. For example, it will suggest the nearby store with the cheapest total price, and it will also display the actual cost including the initial point reward.

[0395] This allows users to significantly reduce the time and effort spent on price comparisons and planning purchases, enabling them to shop in an economical and efficient manner.

[0396] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0397] Step 1:

[0398] The user launches the application installed on their smartphone and inputs a list of products they wish to purchase. They can also input additional conditions as needed. As input, the user provides a list of products such as "potatoes," "carrots," "onions," "meat," and "roux," along with an additional condition such as "I would like to add apple as a secret ingredient." Based on this input, the application sends the data to the server.

[0399] Step 2:

[0400] The server receives and analyzes the data sent by the user. Specifically, it parses the received data to extract each product and additional conditions, and prepares to launch the crawler bot. It receives the JSON data entered by the user as input, extracts the product list and additional conditions, and generates structured data for launching the crawler bot.

[0401] Step 3:

[0402] The server launches a crawler bot to collect the latest product price information from multiple websites on the Internet. The crawler bot accesses each website and parses the HTML to extract price information. It receives a list of products as input and generates data containing price information for each product as output.

[0403] Step 4:

[0404] The server inputs the collected price information into the generative AI model. Specifically, the collected price information and the user's additional conditions are formatted as a prompt sentence and sent to the generative AI model to calculate the optimal purchase plan. The input is the price information and additional conditions, and the output is the optimal purchase plan.

[0405] Step 5:

[0406] The generative AI model calculates the optimal purchase plan. The calculation takes into account collected price information, inventory information, additional user conditions, point redemption information, etc. It receives price information and user conditions as input, and generates the optimal purchase plan in text format as output. For example, a detailed purchase plan is provided in the form of "Potatoes: 100 yen at store A, Carrots: 50 yen at store B."

[0407] Step 6:

[0408] The server sends the calculated optimal purchase plan to the user's smartphone. It receives the purchase plan from the generative AI model as input and generates data to display the plan on the user's device as output. This allows the user to check the optimal purchase plan on their smartphone.

[0409] Step 7:

[0410] The user purchases products at the specified store or online shopping site based on the purchase plan notified through the application. This eliminates the need for price comparisons and stock confirmation, enabling economical shopping. User behavior includes actually making a purchase using the optimal purchase plan provided by the application.

[0411] 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.

[0412] The present invention is a system that allows a user to input a list of items they wish to purchase and proposes the optimal purchase plan, and also has the ability to recognize the user's emotions and adjust the proposal content based on that information. A method for implementing this system will be described in detail using the following procedures and configuration.

[0413] First, the user uses the user terminal to input a list of items they wish to purchase. Specifically, the user uses a screen to input items such as "potatoes," "carrots," "onions," "meat," and "roux." Additional information can also be entered, such as "I'd like to add apple as a secret ingredient." Additionally, the user terminal is equipped with an emotion engine that analyzes the user's emotions from their facial expressions and voice, and sends that data to the system.

[0414] Next, the server receives the user's request and emotional data and analyzes the content. Based on the analyzed data, the server launches a crawler bot that crawls multiple websites on the Internet and automatically collects the latest price information for each product. The collected price information is then sent back to the server, which then inputs it into the generative AI model.

[0415] The generative AI model receives collected price information, user requests, and emotional data as input and calculates the optimal purchase plan. The generative AI model generates the most economical plan by taking into account the price of each product, inventory information, price comparisons between multiple stores, and specific point reward services. If the user is feeling dissatisfied or stressed, the emotion engine adjusts the suggestions to improve user satisfaction, such as suggesting simpler options by taking their emotions into consideration.

[0416] The calculated optimal purchase plan is sent by the server to the user's terminal. The user can then check the plan on their own terminal and purchase the products at the specified stores. This process not only enables the user to purchase multiple products at the lowest cost and most efficiently, but also allows the user to receive optimal suggestions based on their emotions.

[0417] As a concrete example, consider the case where a user inputs "I want to buy curry ingredients at the cheapest price." If the user inputs "potatoes," "carrots," "onions," "meat," "roux," and "apples" into a list, and the user's emotional data indicates "stress," the server not only launches a crawler bot to collect price information for each item, but also takes this emotional data into account and inputs it into the generative AI model. The generative AI model generates a simple and intuitive purchasing plan to prevent the user from feeling stressed, and the server sends this to the user's device. The user can purchase products in the most economical and efficient way possible, without feeling stressed.

[0418] The processing flow will be explained below.

[0419] Step 1:

[0420] The user uses a terminal to input the items they wish to purchase. The user inputs a list of items such as "potatoes," "carrots," "onions," "meat," and "roux." The user also inputs additional information such as "add apples as a secret ingredient."

[0421] Step 2:

[0422] The emotion engine installed in the device analyzes the user's facial expressions and voice and generates emotion data. For example, if it is determined that the user is feeling stressed, emotion data containing that information is sent from the device to the server.

[0423] Step 3:

[0424] The server analyzes the list of desired products and emotion data received from the terminal. The server breaks down the user's request, extracts the name of each product and additional information, and stores the emotion data separately.

[0425] Step 4:

[0426] The server launches a crawler bot, which crawls multiple websites on the Internet to gather the latest price information for the specified product.

[0427] Step 5:

[0428] The crawler bot sends the collected price information to a server, which stores it in a database.

[0429] Step 6:

[0430] The server launches a generative AI model based on the stored price information. The generative AI model receives price information, user requests, additional information, and emotional data as input data and calculates the optimal purchase plan.

[0431] Step 7:

[0432] The server receives the optimal purchase plan calculated by the generative AI model. The server then takes emotional data into account and adjusts the proposal to avoid stress for the user. For example, it prioritizes simple plans that minimize complex store-to-store travel.

[0433] Step 8:

[0434] The server sends the adjusted purchase plan to the user's terminal, where the user can check the plan.

[0435] Step 9:

[0436] The user purchases products at the designated store based on the proposed purchase plan, which not only allows the user to purchase products in the most economical and efficient way, but also increases emotional satisfaction.

[0437] Example 2

[0438] 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."

[0439] Conventional online shopping systems have difficulty generating optimal purchase plans simply by inputting the products a user wishes to purchase. Furthermore, they lack the functionality to provide purchase plans that take into account the user's emotions and reduce stress and dissatisfaction. As a result, there are problems with lower user satisfaction and a decrease in willingness to purchase.

[0440] 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.

[0441] In this invention, the server includes a means for a user to input a list of products they wish to purchase, a means for acquiring user emotion data, a crawler bot means for collecting product price information from websites, a generative AI model means for calculating an optimal purchase plan based on the collected price information and user emotion data, and a means for providing the calculated purchase plan to the user. This makes it possible to provide the most economical and efficient purchase plan while taking user emotions into consideration, thereby improving user satisfaction.

[0442] The "means for a user to input a list of products desired for purchase" refers to a means for a user to provide a list of products desired by the user to the system through text input, voice input, or other input method.

[0443] The "means for acquiring user emotion data" is a means for analyzing emotions from the user's facial expressions, voice, etc., and acquiring the analysis results as data.

[0444] The "crawler bot means for collecting product price information from websites" is a program that crawls multiple websites on the Internet and automatically collects the latest price information for each product.

[0445] The "generative AI model means for calculating an optimal purchase plan based on collected price information and user emotional data" is an artificial intelligence model for receiving collected price information and user emotional data as input data and generating an optimal purchase plan.

[0446] The "means for providing the calculated purchase plan to the user" is a means for transmitting the generated purchase plan to the user terminal so that the user can check the plan.

[0447] The present invention is a system that allows users to input a list of products they wish to purchase and proposes the optimal purchase plan, and also has the function of recognizing the user's emotions and adjusting the proposal content based on that information. In implementing this system, the user terminal and the server mainly work together.

[0448] System configuration and hardware / software used

[0449] First, the user uses the user terminal to input a list of products they wish to purchase. Specifically, they use a screen where they can input products such as "potatoes," "carrots," "onions," "meat," and "roux." In addition to the product list, the user can also input additional information such as "I'd like to add apples as a secret ingredient."

[0450] The user device is equipped with an emotion engine that analyzes emotions from the user's facial expressions and voice and sends the data to a server. The emotion engine's hardware includes a camera and microphone, and the software uses an emotion analysis program.

[0451] Next, the server receives the user's request and emotional data and analyzes the content. This analysis is performed using a database and analytical algorithms. Based on this analyzed data, the server launches a crawler bot, which crawls multiple websites on the Internet and automatically collects the latest price information for each product. The collected price information is then sent back to the server.

[0452] The server inputs price information, user requests, and emotional data into a generative AI model. The generative AI model uses technologies such as OpenAI's GPT-4 to calculate the most economical purchase plan, taking into account each product's price, inventory information, price comparisons between multiple stores, and specific point reward services. Additionally, if the user is feeling dissatisfied or stressed, the emotion engine will take their emotions into consideration and suggest simpler options, thereby improving user satisfaction.

[0453] The calculated optimal purchase plan is sent by the server to the user's terminal. The user can then check this plan on their own terminal and purchase the products at the specified store. This not only enables the user to purchase multiple products at the lowest cost and most efficiently, but also allows the user to receive optimal suggestions based on their emotions.

[0454] Examples of concrete examples and prompts

[0455] As a concrete example, consider the case where a user inputs "I want to buy curry ingredients at the cheapest price." If the user inputs "potatoes," "carrots," "onions," "meat," "roux," and "apples" into a list, and the user's emotional data indicates "stress," the server not only launches a crawler bot to collect price information for each item, but also takes this emotional data into account and inputs it into the generative AI model. The generative AI model generates a simple and intuitive purchasing plan to prevent the user from feeling stressed, and the server sends this to the user's device. The user can purchase products in the most economical and efficient way possible, without feeling stressed.

[0456] Example prompt sentence:

[0457] "Generate a plan to purchase ingredients for curry at the lowest price. The purchase list is potatoes, carrots, onions, meat, roux, and apples. User sentiment data indicates stress. Provide a simple and intuitive purchasing plan."

[0458] As a result, the present invention can improve user satisfaction and provide an optimal purchasing experience.

[0459] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0460] Step 1:

[0461] The user inputs a list of products that he or she wishes to purchase using the user terminal.

[0462] Specifically, the user enters items such as "potatoes," "carrots," "onions," "meat," and "roux" into an input form on the terminal screen. A shopping list is generated based on the input data and sent to the system.

[0463] Step 2:

[0464] The device acquires emotional data and analyzes the user's facial expressions and voice.

[0465] Specifically, the device's camera and microphone capture the user's facial expressions and voice, which are then analyzed by the emotion engine. Emotional data such as "stress" is generated as a result of the analysis and sent to the server.

[0466] Step 3:

[0467] The server receives the request and emotion data and analyzes the content.

[0468] Specifically, the server receives the purchase list and emotion data sent by the user and analyzes them using an analysis algorithm. The input data are the purchase list and emotion data, and the output is the analyzed information.

[0469] Step 4:

[0470] The server launches a crawler bot that crawls multiple websites on the Internet to collect the latest price information.

[0471] Specifically, the crawler bot patrols designated e-commerce sites and collects the latest price information for items such as potatoes, carrots, and onions. This collected price information is then saved on the server and output.

[0472] Step 5:

[0473] The server inputs collected price information, user requests, and sentiment data into a generative AI model.

[0474] Specifically, the server inputs the collected price information, request information from the user, and emotional data into a generative AI model (e.g., OpenAI's GPT-4). The generative AI model processes this data and calculates the optimal purchase plan. The input data are price information, user request, and emotional data, and the output is the generated purchase plan.

[0475] Step 6:

[0476] The server transmits the calculated purchase plan to the user terminal.

[0477] Specifically, the server sends the purchase plan created by the generative AI model to the user's device. The optimal purchase method for multiple products is displayed on the device. The input data is the generated purchase plan, and the output is the plan information displayed on the user's device.

[0478] Step 7:

[0479] The user confirms the purchase plan and purchases the product at the specified store.

[0480] Specifically, the user checks the purchase plan displayed on the terminal and purchases products at each store according to that plan. Specific store information is displayed as the optimal purchase method, such as "purchase potatoes at supermarket A" and "purchase carrots at supermarket B." The input data is the displayed purchase plan, and the output is the products actually purchased by the user.

[0481] (Application example 2)

[0482] 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."

[0483] Current shopping support systems propose optimal purchase plans based on product lists and price information entered by users, but because they do not take into account the user's emotional state, they may produce proposals that are unsatisfying. Furthermore, because they do not take into consideration users who are stressed or dissatisfied, there is a problem that the user experience is not improved. The objective of this invention is to provide a more satisfying shopping experience by analyzing the user's emotions and making proposals accordingly.

[0484] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0485] In this invention, the server includes means for a user to input a list of products they wish to purchase, crawler bot means for collecting product price information from websites, generation AI model means for calculating an optimal purchase plan based on the collected price information, means for analyzing the user's emotional data using an emotion analysis engine, and means for adjusting and providing the calculated purchase plan based on the user's emotions. This makes it possible to propose an optimal purchase plan that takes the user's emotional state into consideration, improving the user experience.

[0486] The "means for the user to input a list of products that the user wishes to purchase" is an interface that allows the user to input the products that the user wishes to purchase in list form.

[0487] A "crawler bot means for collecting product price information from websites" is a software robot that crawls websites on the Internet and automatically collects product price information.

[0488] The "generative AI model means for calculating the optimal purchase plan based on collected price information" is an artificial intelligence model that receives collected product price information as input data and calculates the optimal purchase plan.

[0489] The "means for analyzing the user's emotional data using an emotional analysis engine" refers to software and hardware for analyzing the user's facial expressions and voice and acquiring emotional data.

[0490] The "means for adjusting and providing a calculated purchase plan based on the user's emotions" refers to a means for adjusting a calculated purchase plan in consideration of the user's emotion data and providing the plan to the user.

[0491] The present invention is a system that allows a user to input a list of products they wish to purchase and proposes the optimal purchase plan, and also has the function of recognizing the user's emotions and adjusting the proposal content based on that information. The specific configuration for implementing this system is shown below.

[0492] First, a user uses a smartphone to input a list of products they wish to purchase. This smartphone is equipped with an emotion analysis engine that uses a camera and microphone to analyze the user's facial expressions and voice to obtain emotional data. The product list and emotional data input by the user are then sent to the server.

[0493] The server analyzes the received user request and emotional data, and launches a crawler bot to collect product price information from the Internet. This crawler bot patrols designated websites and obtains the latest price information for, for example, potatoes, carrots, onions, meat, roux, and apples.

[0494] The collected price information is sent to a server and input to a generative AI model. This generative AI model receives price information, user requests, and sentiment data as input data and calculates the optimal purchase plan. The generative AI model used here is, for example, OpenAI's text generation API.

[0495] The calculated purchase plan is adjusted taking into account the user's emotional data. If the user is feeling stressed, a simple and intuitive purchase plan is proposed to improve the user's satisfaction. This adjusted purchase plan is sent from the server to the user's device.

[0496] As a specific example, consider the case where a user requests, "I want to buy curry ingredients at the lowest price." The product list entered by the user includes potatoes, carrots, onions, meat, roux, and apples. If the emotional data indicates "stress," the server launches a crawler bot to collect price information for these items. The collected information is input into a generative AI model, which generates a simple and intuitive purchase plan to prevent the user from feeling stressed. An example of a prompt sentence is shown below.

[0497] Example prompt sentence:

[0498] "Products desired: {'Potatoes': '100 yen', 'Carrots': '50 yen', 'Onions': '30 yen', 'Meat': '200 yen', 'Rou': '150 yen', 'Apples': '300 yen'} User emotion: Stressed Please generate the optimal purchase plan."

[0499] According to this invention, it is possible to propose an optimal purchase plan taking into consideration the user's feelings, thereby greatly improving user satisfaction.

[0500] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0501] Step 1:

[0502] The user inputs a list of products they wish to purchase using their smartphone.

[0503] The input list may include, for example, "potatoes," "carrots," "onions," "meat," "roux," and "apples." List data is generated based on the user's input and sent from the terminal to the server. The output is the list data of the input products.

[0504] Step 2:

[0505] The user's device then uses its built-in camera and microphone to capture the user's facial expressions and voice.

[0506] Based on the acquired data, the emotion analysis engine analyzes the user's emotion data and obtains the analysis results (emotion data). This emotion data is also sent from the device to the server. The output is the user's emotion data.

[0507] Step 3:

[0508] The server receives and analyzes the user's list of desired products and emotion data.

[0509] Based on the analyzed data, the server issues a command to launch a crawler bot. The crawler bot crawls designated websites and collects the latest price information for each product. The input is the list data of products desired for purchase and emotion data, and the output is the collected price information.

[0510] Step 4:

[0511] The collected price information is sent to a server and stored in a database.

[0512] The server uses this price information to construct input data for the generative AI model. The input data to the generative AI model includes product names, prices, and user sentiment data. The output is the input data for the generative AI model.

[0513] Step 5:

[0514] The server inputs price information stored in a database and user emotion data into the generative AI model.

[0515] The generative AI model calculates the optimal purchase plan based on input data. The calculation process takes into account price comparisons for each product, inventory information, point reward services, and other factors. The output is the calculated optimal purchase plan.

[0516] Step 6:

[0517] The server adjusts the optimal purchase plan calculated by the generative AI model based on the user's emotional data.

[0518] For example, if the user is feeling "stressed," the system adjusts the calculated plan to be simple and intuitive. The input is the calculated purchase plan and the user's emotional data, and the output is an adjusted purchase plan based on the emotion.

[0519] Step 7:

[0520] The server sends the adjusted optimal purchase plan to the user's smartphone.

[0521] The user can check this purchase plan on their own terminal and purchase the product at the specified store. The output is the final purchase plan, which is the output the user receives.

[0522] This not only enables users to purchase multiple products at the lowest cost and most efficiently, but also allows users to receive optimal suggestions based on their emotions.

[0523] 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.

[0524] 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.

[0525] 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.

[0526] [Third embodiment]

[0527] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0528] 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.

[0529] 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).

[0530] 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.

[0531] 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.

[0532] 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).

[0533] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0534] 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.

[0535] 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.

[0536] 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.

[0537] 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.

[0538] 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."

[0539] The present invention provides a system that allows a user to input a list of products they wish to purchase and suggests an optimal purchasing plan. A method for implementing this system will be described in detail below using the procedures and configuration shown below.

[0540] First, the user uses the user terminal to input a list of products they wish to purchase. Specifically, the user uses a screen to input multiple products such as "potatoes," "carrots," "onions," "meat," and "roux." In addition, the user can input additional information such as "I would like to add apples as a secret ingredient."

[0541] Next, the server receives the user's request and analyzes its contents. Based on the analyzed data, the server launches a crawler bot. The crawler bot then crawls multiple websites on the Internet and automatically collects the latest price information for each product.

[0542] The collected price information is sent back to the server, which then inputs it into the generative AI model. The generative AI model calculates the optimal purchase plan based on the collected price information and the user's request (including additional information). The generative AI model also takes into account the price of each product, inventory information, price comparisons between multiple stores, and specific point reward services to generate the most economical plan.

[0543] The server then sends the calculated optimal purchase plan to the user's terminal. The user can then check the plan on their own terminal and purchase the products at the designated stores. This process allows the user to purchase multiple products at the lowest cost and most efficiently.

[0544] As a concrete example, consider the case where a user enters "I want to buy curry ingredients at the cheapest price." When the user enters "potatoes," "carrots," "onions," "meat," "roux," and "apples" into a list, the server receives this and launches a crawler bot. The crawler bot collects price information for each item, and the generative AI model calculates the optimal plan. For example, it can suggest the nearby supermarket with the lowest total price and also display the actual cost including the initial point reward.

[0545] This saves users the time and effort of comparing prices themselves, allowing them to shop in the most economical way possible.

[0546] The processing flow will be explained below.

[0547] Step 1:

[0548] The user uses a terminal to input the items they wish to purchase. Specifically, the user launches the application's input screen and inputs a list of ingredients such as "potatoes," "carrots," "onions," "meat," and "roux." They can also input additional information, such as "apple as a secret ingredient."

[0549] Step 2:

[0550] The terminal formats the input data and sends it to the server. The terminal compiles the list of products desired for purchase and additional information into one request data.

[0551] Step 3:

[0552] The server analyzes the request received from the terminal. Specifically, the server breaks down the request data and extracts the name of each product and additional information.

[0553] Step 4:

[0554] The server launches a crawler bot, which crawls multiple websites on the Internet and collects price information for the specified product.

[0555] Step 5:

[0556] The crawler bot sends the collected price information to a server, which receives it and stores it in a database.

[0557] Step 6:

[0558] The server launches a generative AI model based on the stored price information, which receives the price information and additional information as input and calculates the optimal purchase plan.

[0559] Step 7:

[0560] The server receives the optimal purchase plan calculated by the generative AI model, formats the plan, and prepares it for delivery to the user.

[0561] Step 8:

[0562] The server sends the calculated purchase plan to the user terminal, where the user can check the proposed plan.

[0563] Step 9:

[0564] The user purchases products at the specified store based on the proposed purchase plan, enabling the user to make the most economical and efficient purchases according to the information presented.

[0565] Example 1

[0566] 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."

[0567] The problem that this invention aims to solve is to provide the most economical and efficient purchase plan by allowing users to easily input a list of products they wish to purchase and quickly collecting the latest price information from multiple websites, thereby significantly reducing the time and effort required for users to compare product prices.

[0568] 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.

[0569] In this invention, the server includes a means for a user to input a list of products they wish to purchase, a means for the server to receive and analyze requests from the user, a means for a crawler bot to crawl websites and collect product price information, a generating AI model means for calculating an optimal purchase plan based on the collected price information, and a means for providing the calculated purchase plan to a user terminal, thereby enabling a user to purchase multiple products in the most economical and efficient manner.

[0570] The "means by which users input a list of products they wish to purchase" refers to an interface for users to input information about products they wish to purchase, and is composed of an application or web form using a device such as a smartphone or PC.

[0571] "The means by which the server receives and analyzes requests from users" refers to a program on the server that receives user input data and analyzes its contents, and has the function of extracting and classifying request data.

[0572] "Means for crawler bots to crawl websites and collect product price information" refers to a software program that automatically crawls multiple websites on the Internet and collects price and inventory information about products.

[0573] The "generative AI model means for calculating the optimal purchase plan based on collected price information" refers to an artificial intelligence model for calculating the optimal purchase plan based on collected price data and user request information, and includes a calculation algorithm that takes into account price comparison and point redemption.

[0574] The "means for providing the calculated purchase plan to the user's device" is a system for notifying the user of the optimal purchase plan calculated by the generative AI model, and has the function of delivering information to the user's device via the Internet.

[0575] The "means for the user to input additional information" is an interface that allows the user to input specific conditions or wishes in addition to the shopping list, and has the function of recording the user's specific requests.

[0576] "A means for collecting inventory and price information from multiple websites on the Internet and reflecting it in the optimal purchase plan" is a system that calculates the optimal purchase plan in real time using inventory and price information collected from multiple sites.

[0577] The present invention relates to a system that allows a user to input a list of products they wish to purchase and proposes an optimal purchasing plan. A method for implementing this system will be described in detail below using the procedures and configuration shown below.

[0578] First, the user uses a user terminal to input a list of items they wish to purchase. Specifically, the user uses an internet-connected device such as a smartphone or PC to input the list of items they wish to purchase into a dedicated app or web form. For example, the user can input items such as "potatoes," "carrots," "onions," "meat," and "roux," and can also enter additional information such as "I'd like to add apples as a secret ingredient."

[0579] Next, the server receives and analyzes the request from the user. The server analyzes the received data and extracts information about the entered product. Based on the analyzed data, the server issues a command to launch the crawler bot.

[0580] Crawler bots crawl multiple websites on the Internet and automatically collect the latest price and stock information for products. Crawler bots collect data such as product names, prices, stock status, and store information.

[0581] The collected price information is sent to a server, which inputs it into a generative AI model. The generative AI model calculates the optimal purchase plan based on the collected price information, the user's request, and additional information. The generative AI model performs its calculations by taking into account price comparisons, inventory information, price comparisons between multiple stores, specific point reward services, and more.

[0582] After calculating the optimal purchase plan, the server sends the calculation results to the user's terminal, where the user can check the proposed purchase plan and purchase the products at the specified store or online shop.

[0583] As a concrete example, consider the case where a user enters "I want to buy curry ingredients at the cheapest price." When the user enters "potatoes," "carrots," "onions," "meat," "roux," and "apples" into a list, the server receives this and launches a crawler bot. The crawler bot collects price and stock information for each item, and the generative AI model calculates the optimal purchase plan. For example, it can suggest the nearby supermarket or online shop with the lowest total price, and also display the actual cost including the initial point reward.

[0584] In this way, users can purchase multiple products at the lowest possible cost and most efficiently.

[0585] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0586] Step 1:

[0587] The user inputs a list of items they wish to purchase.

[0588] Specific operation: The user accesses a dedicated app or web form using a smartphone or PC and inputs a list of products such as "potatoes," "carrots," "onions," "meat," and "roux." They can also add additional information such as "I'd like to add apples as a secret ingredient."

[0589] Input: List of items you wish to purchase and additional information.

[0590] Output: Data entered into the input form.

[0591] Step 2:

[0592] The server receives and analyzes the request from the user.

[0593] How it works: The server receives the data sent from the user device and analyzes its contents to extract information about each product and additional information. The analysis is performed using a text processing algorithm.

[0594] Input: Data submitted by the user (list of products and additional information).

[0595] Output: A list of parsed products and additional information.

[0596] Step 3:

[0597] The server launches the crawler bot.

[0598] Specific operation: Based on the analyzed data, the server issues a command to launch a crawler bot, which then crawls designated websites and automatically collects the latest product price and stock information.

[0599] Input: A parsed list of products.

[0600] Output: Instructions to launch the crawler bot.

[0601] Step 4:

[0602] Crawler bots crawl websites and collect product price information.

[0603] Specific operation: The crawler bot accesses each website and collects price and stock information for products such as "potatoes" and "carrots" using web scraping technology.

[0604] Input: A list of specified products.

[0605] Output: Up-to-date price and availability information for each product.

[0606] Step 5:

[0607] The collected price information is fed into a generative AI model.

[0608] How it works: The crawler bot sends the collected price information to the server, which then inputs it into the generative AI model, which preprocesses the data and creates an input dataset for calculating the optimal purchase plan.

[0609] Input: Collected pricing and inventory information.

[0610] Output: The dataset that is input to the generative AI model.

[0611] Step 6:

[0612] A generative AI model calculates the optimal purchase plan.

[0613] How it works: Based on collected pricing information, the user's request, and additional information, the generative AI model calculates the optimal purchase plan, taking into account price comparisons, inventory availability, and multiple purchasing options.

[0614] Input: Input datasets (pricing information, inventory information, user requests).

[0615] Output: Best buy plan.

[0616] Step 7:

[0617] The server sends the calculation results to the user terminal.

[0618] Specific operation: The server receives the calculation results of the optimal purchase plan from the generative AI model and sends them to the user's device. The user receives and displays this data on their own device.

[0619] Enter: Best buy plan.

[0620] Output: The optimal purchase plan sent to the user device.

[0621] Step 8:

[0622] The user checks the purchase plan and purchases the product at the specified store or online shop.

[0623] Specific operation: The user checks the purchase plan sent on the device and purchases the product from the recommended store or online shop. The purchase plan describes the most economical and efficient way to purchase the product.

[0624] Input: The purchase plan displayed on the user's device.

[0625] Output: The actual action of purchasing the product.

[0626] (Application example 1)

[0627] 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."

[0628] In today's world, when users purchase products from multiple online shopping sites, it is extremely difficult to compare prices and find the optimal purchase plan. At the same time, they must also be able to respond to detailed requests based on product inventory information and specific conditions. In such situations, users end up spending a great deal of time and effort, resulting in a decrease in purchasing efficiency. To solve this problem, a system is needed that allows users to easily list products and automatically provides the optimal purchase plan.

[0629] 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.

[0630] In this invention, the server includes a means for a user to input a list of products they wish to purchase, a crawler bot means for collecting product price information from multiple websites on the Internet, a generation AI model means for calculating an optimal purchase plan based on the collected price information and additional information, a means for providing the calculated purchase plan to the user, and an application means for being installed on a smartphone. This allows the user to easily input a list of products they wish to purchase and quickly obtain an optimal purchase plan that includes additional conditions.

[0631] The term "means for a user to input a list of products that the user wishes to purchase" refers to an interface or function that allows the user to electronically input a list of products that the user wishes to purchase.

[0632] "Crawler bot means for collecting product price information from multiple websites on the Internet" refers to programs and functions for automatically crawling multiple websites on the Internet and collecting the latest product price information.

[0633] "Generative AI model means for calculating the optimal purchase plan based on collected price information and additional information" refers to the calculation function of an artificial intelligence model for calculating the optimal purchase plan using collected price information and additional information provided by the user.

[0634] "Means for providing the calculated purchase plan to the user" refers to an interface or function for presenting the optimal purchase plan calculated by the generative AI model in a form that is accessible to the user.

[0635] "Application means installed on a smartphone" refers to a software application that is downloaded and installed on a smartphone and can perform a series of operations from inputting a list of products desired to be purchased to being provided with the most suitable purchase plan.

[0636] "Means for collecting inventory information from nearby stores and online sales sites and reflecting it in an optimal purchasing plan" refers to functions and programs for collecting inventory information from nearby physical stores and online sales sites and incorporating that information into an optimal purchasing plan.

[0637] To implement the present invention, the following configuration and processing procedure are followed.

[0638] First, a user inputs a list of items they wish to purchase using an application installed on their smartphone. This application provides an interface that transmits the information the user inputs to the server. As a specific example, a user can input a list of items such as "potatoes," "carrots," "onions," "meat," and "roux," and then add additional information such as "I would like to add apples as a secret ingredient."

[0639] The server analyzes the received data and launches a crawler bot, which crawls multiple websites across the Internet to gather up-to-date pricing and availability information for the specified product. The crawler bot uses, for example, the Requests and BeautifulSoup libraries to extract the required information from the web pages.

[0640] The collected pricing information and additional information is sent back to the server and then fed into a generative AI model, which uses an artificial intelligence model such as OpenAI's GPT-3 to calculate the optimal purchase plan. An example prompt for this is below:

[0641] "Plan the best purchase plan for the following items:

[0642] Potatoes: 100 yen, carrots: 50 yen, onions: 80 yen, meat: 500 yen, roux: 200 yen, apples: 150 yen

[0643] Additional information: I like to add apples as a secret ingredient.

[0644] When calculating the optimal purchase plan, the generative AI model takes into account price and availability information, as well as specific rewards programs and user-defined conditions.

[0645] The calculated optimal purchase plan is sent from the server to the application, where the user can check it on their smartphone. The user can then purchase products from the designated online shopping site or a nearby store according to the purchase plan.

[0646] For example, if a user types "I want to buy curry ingredients at the cheapest price," a crawler bot will collect the prices of each item, and a generative AI model will calculate the optimal plan. For example, it will suggest the nearby store with the cheapest total price, and it will also display the actual cost including the initial point reward.

[0647] This allows users to significantly reduce the time and effort spent on price comparisons and planning purchases, enabling them to shop in an economical and efficient manner.

[0648] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0649] Step 1:

[0650] The user launches the application installed on their smartphone and inputs a list of products they wish to purchase. They can also input additional conditions as needed. As input, the user provides a list of products such as "potatoes," "carrots," "onions," "meat," and "roux," along with an additional condition such as "I would like to add apple as a secret ingredient." Based on this input, the application sends the data to the server.

[0651] Step 2:

[0652] The server receives and analyzes the data sent by the user. Specifically, it parses the received data to extract each product and additional conditions, and prepares to launch the crawler bot. It receives the JSON data entered by the user as input, extracts the product list and additional conditions, and generates structured data for launching the crawler bot.

[0653] Step 3:

[0654] The server launches a crawler bot to collect the latest product price information from multiple websites on the Internet. The crawler bot accesses each website and parses the HTML to extract price information. It receives a list of products as input and generates data containing price information for each product as output.

[0655] Step 4:

[0656] The server inputs the collected price information into the generative AI model. Specifically, the collected price information and the user's additional conditions are formatted as a prompt sentence and sent to the generative AI model to calculate the optimal purchase plan. The input is the price information and additional conditions, and the output is the optimal purchase plan.

[0657] Step 5:

[0658] The generative AI model calculates the optimal purchase plan. The calculation takes into account collected price information, inventory information, additional user conditions, point redemption information, etc. It receives price information and user conditions as input, and generates the optimal purchase plan in text format as output. For example, a detailed purchase plan is provided in the form of "Potatoes: 100 yen at store A, Carrots: 50 yen at store B."

[0659] Step 6:

[0660] The server sends the calculated optimal purchase plan to the user's smartphone. It receives the purchase plan from the generative AI model as input and generates data to display the plan on the user's device as output. This allows the user to check the optimal purchase plan on their smartphone.

[0661] Step 7:

[0662] The user purchases products at the specified store or online shopping site based on the purchase plan notified through the application. This eliminates the need for price comparisons and stock confirmation, enabling economical shopping. User behavior includes actually making a purchase using the optimal purchase plan provided by the application.

[0663] 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.

[0664] The present invention is a system that allows a user to input a list of items they wish to purchase and proposes the optimal purchase plan, and also has the ability to recognize the user's emotions and adjust the proposal content based on that information. A method for implementing this system will be described in detail using the following procedures and configuration.

[0665] First, the user uses the user terminal to input a list of items they wish to purchase. Specifically, the user uses a screen to input items such as "potatoes," "carrots," "onions," "meat," and "roux." Additional information can also be entered, such as "I'd like to add apple as a secret ingredient." Additionally, the user terminal is equipped with an emotion engine that analyzes the user's emotions from their facial expressions and voice, and sends that data to the system.

[0666] Next, the server receives the user's request and emotional data and analyzes the content. Based on the analyzed data, the server launches a crawler bot that crawls multiple websites on the Internet and automatically collects the latest price information for each product. The collected price information is then sent back to the server, which then inputs it into the generative AI model.

[0667] The generative AI model receives collected price information, user requests, and emotional data as input and calculates the optimal purchase plan. The generative AI model generates the most economical plan by taking into account the price of each product, inventory information, price comparisons between multiple stores, and specific point reward services. If the user is feeling dissatisfied or stressed, the emotion engine adjusts the suggestions to improve user satisfaction, such as suggesting simpler options by taking their emotions into consideration.

[0668] The calculated optimal purchase plan is sent by the server to the user's terminal. The user can then check the plan on their own terminal and purchase the products at the specified stores. This process not only enables the user to purchase multiple products at the lowest cost and most efficiently, but also allows the user to receive optimal suggestions based on their emotions.

[0669] As a concrete example, consider the case where a user inputs "I want to buy curry ingredients at the cheapest price." If the user inputs "potatoes," "carrots," "onions," "meat," "roux," and "apples" into a list, and the user's emotional data indicates "stress," the server not only launches a crawler bot to collect price information for each item, but also takes this emotional data into account and inputs it into the generative AI model. The generative AI model generates a simple and intuitive purchasing plan to prevent the user from feeling stressed, and the server sends this to the user's device. The user can purchase products in the most economical and efficient way possible, without feeling stressed.

[0670] The processing flow will be explained below.

[0671] Step 1:

[0672] The user uses a terminal to input the items they wish to purchase. The user inputs a list of items such as "potatoes," "carrots," "onions," "meat," and "roux." The user also inputs additional information such as "add apples as a secret ingredient."

[0673] Step 2:

[0674] The emotion engine installed in the device analyzes the user's facial expressions and voice and generates emotion data. For example, if it is determined that the user is feeling stressed, emotion data containing that information is sent from the device to the server.

[0675] Step 3:

[0676] The server analyzes the list of desired products and emotion data received from the terminal. The server breaks down the user's request, extracts the name of each product and additional information, and stores the emotion data separately.

[0677] Step 4:

[0678] The server launches a crawler bot, which crawls multiple websites on the Internet to gather the latest price information for the specified product.

[0679] Step 5:

[0680] The crawler bot sends the collected price information to a server, which stores it in a database.

[0681] Step 6:

[0682] The server launches a generative AI model based on the stored price information. The generative AI model receives price information, user requests, additional information, and emotional data as input data and calculates the optimal purchase plan.

[0683] Step 7:

[0684] The server receives the optimal purchase plan calculated by the generative AI model. The server then takes emotional data into account and adjusts the proposal to avoid stress for the user. For example, it prioritizes simple plans that minimize complex store-to-store travel.

[0685] Step 8:

[0686] The server sends the adjusted purchase plan to the user's terminal, where the user can check the plan.

[0687] Step 9:

[0688] The user purchases products at the designated store based on the proposed purchase plan, which not only allows the user to purchase products in the most economical and efficient way, but also increases emotional satisfaction.

[0689] Example 2

[0690] 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."

[0691] Conventional online shopping systems have difficulty generating optimal purchase plans simply by inputting the products a user wishes to purchase. Furthermore, they lack the functionality to provide purchase plans that take into account the user's emotions and reduce stress and dissatisfaction. As a result, there are problems with lower user satisfaction and a decrease in willingness to purchase.

[0692] 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.

[0693] In this invention, the server includes a means for a user to input a list of products they wish to purchase, a means for acquiring user emotion data, a crawler bot means for collecting product price information from websites, a generative AI model means for calculating an optimal purchase plan based on the collected price information and user emotion data, and a means for providing the calculated purchase plan to the user. This makes it possible to provide the most economical and efficient purchase plan while taking user emotions into consideration, thereby improving user satisfaction.

[0694] The "means for a user to input a list of products desired for purchase" refers to a means for a user to provide a list of products desired by the user to the system through text input, voice input, or other input method.

[0695] The "means for acquiring user emotion data" is a means for analyzing emotions from the user's facial expressions, voice, etc., and acquiring the analysis results as data.

[0696] The "crawler bot means for collecting product price information from websites" is a program that crawls multiple websites on the Internet and automatically collects the latest price information for each product.

[0697] The "generative AI model means for calculating an optimal purchase plan based on collected price information and user emotional data" is an artificial intelligence model for receiving collected price information and user emotional data as input data and generating an optimal purchase plan.

[0698] The "means for providing the calculated purchase plan to the user" is a means for transmitting the generated purchase plan to the user terminal so that the user can check the plan.

[0699] The present invention is a system that allows users to input a list of products they wish to purchase and proposes the optimal purchase plan, and also has the function of recognizing the user's emotions and adjusting the proposal content based on that information. In implementing this system, the user terminal and the server mainly work together.

[0700] System configuration and hardware / software used

[0701] First, the user uses the user terminal to input a list of products they wish to purchase. Specifically, they use a screen where they can input products such as "potatoes," "carrots," "onions," "meat," and "roux." In addition to the product list, the user can also input additional information such as "I'd like to add apples as a secret ingredient."

[0702] The user device is equipped with an emotion engine that analyzes emotions from the user's facial expressions and voice and sends the data to a server. The emotion engine's hardware includes a camera and microphone, and the software uses an emotion analysis program.

[0703] Next, the server receives the user's request and emotional data and analyzes the content. This analysis is performed using a database and analytical algorithms. Based on this analyzed data, the server launches a crawler bot, which crawls multiple websites on the Internet and automatically collects the latest price information for each product. The collected price information is then sent back to the server.

[0704] The server inputs price information, user requests, and emotional data into a generative AI model. The generative AI model uses technologies such as OpenAI's GPT-4 to calculate the most economical purchase plan, taking into account each product's price, inventory information, price comparisons between multiple stores, and specific point reward services. Additionally, if the user is feeling dissatisfied or stressed, the emotion engine will take their emotions into consideration and suggest simpler options, thereby improving user satisfaction.

[0705] The calculated optimal purchase plan is sent by the server to the user's terminal. The user can then check this plan on their own terminal and purchase the products at the specified store. This not only enables the user to purchase multiple products at the lowest cost and most efficiently, but also allows the user to receive optimal suggestions based on their emotions.

[0706] Examples of concrete examples and prompts

[0707] As a concrete example, consider the case where a user inputs "I want to buy curry ingredients at the cheapest price." If the user inputs "potatoes," "carrots," "onions," "meat," "roux," and "apples" into a list, and the user's emotional data indicates "stress," the server not only launches a crawler bot to collect price information for each item, but also takes this emotional data into account and inputs it into the generative AI model. The generative AI model generates a simple and intuitive purchasing plan to prevent the user from feeling stressed, and the server sends this to the user's device. The user can purchase products in the most economical and efficient way possible, without feeling stressed.

[0708] Example prompt sentence:

[0709] "Generate a plan to purchase ingredients for curry at the lowest price. The purchase list is potatoes, carrots, onions, meat, roux, and apples. User sentiment data indicates stress. Provide a simple and intuitive purchasing plan."

[0710] As a result, the present invention can improve user satisfaction and provide an optimal purchasing experience.

[0711] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0712] Step 1:

[0713] The user inputs a list of products that he or she wishes to purchase using the user terminal.

[0714] Specifically, the user enters items such as "potatoes," "carrots," "onions," "meat," and "roux" into an input form on the terminal screen. A shopping list is generated based on the input data and sent to the system.

[0715] Step 2:

[0716] The device acquires emotional data and analyzes the user's facial expressions and voice.

[0717] Specifically, the device's camera and microphone capture the user's facial expressions and voice, which are then analyzed by the emotion engine. Emotional data such as "stress" is generated as a result of the analysis and sent to the server.

[0718] Step 3:

[0719] The server receives the request and emotion data and analyzes the content.

[0720] Specifically, the server receives the purchase list and emotion data sent by the user and analyzes them using an analysis algorithm. The input data are the purchase list and emotion data, and the output is the analyzed information.

[0721] Step 4:

[0722] The server launches a crawler bot that crawls multiple websites on the Internet to collect the latest price information.

[0723] Specifically, the crawler bot patrols designated e-commerce sites and collects the latest price information for items such as potatoes, carrots, and onions. This collected price information is then saved on the server and output.

[0724] Step 5:

[0725] The server inputs collected price information, user requests, and sentiment data into a generative AI model.

[0726] Specifically, the server inputs the collected price information, request information from the user, and emotional data into a generative AI model (e.g., OpenAI's GPT-4). The generative AI model processes this data and calculates the optimal purchase plan. The input data are price information, user request, and emotional data, and the output is the generated purchase plan.

[0727] Step 6:

[0728] The server transmits the calculated purchase plan to the user terminal.

[0729] Specifically, the server sends the purchase plan created by the generative AI model to the user's device. The optimal purchase method for multiple products is displayed on the device. The input data is the generated purchase plan, and the output is the plan information displayed on the user's device.

[0730] Step 7:

[0731] The user confirms the purchase plan and purchases the product at the specified store.

[0732] Specifically, the user checks the purchase plan displayed on the terminal and purchases products at each store according to that plan. Specific store information is displayed as the optimal purchase method, such as "purchase potatoes at supermarket A" and "purchase carrots at supermarket B." The input data is the displayed purchase plan, and the output is the products actually purchased by the user.

[0733] (Application example 2)

[0734] 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."

[0735] Current shopping support systems propose optimal purchase plans based on product lists and price information entered by users, but because they do not take into account the user's emotional state, they may produce proposals that are unsatisfying. Furthermore, because they do not take into consideration users who are stressed or dissatisfied, there is a problem that the user experience is not improved. The objective of this invention is to provide a more satisfying shopping experience by analyzing the user's emotions and making proposals accordingly.

[0736] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0737] In this invention, the server includes means for a user to input a list of products they wish to purchase, crawler bot means for collecting product price information from websites, generation AI model means for calculating an optimal purchase plan based on the collected price information, means for analyzing the user's emotional data using an emotion analysis engine, and means for adjusting and providing the calculated purchase plan based on the user's emotions. This makes it possible to propose an optimal purchase plan that takes the user's emotional state into consideration, improving the user experience.

[0738] The "means for the user to input a list of products that the user wishes to purchase" is an interface that allows the user to input the products that the user wishes to purchase in list form.

[0739] A "crawler bot means for collecting product price information from websites" is a software robot that crawls websites on the Internet and automatically collects product price information.

[0740] The "generative AI model means for calculating the optimal purchase plan based on collected price information" is an artificial intelligence model that receives collected product price information as input data and calculates the optimal purchase plan.

[0741] The "means for analyzing the user's emotional data using an emotional analysis engine" refers to software and hardware for analyzing the user's facial expressions and voice and acquiring emotional data.

[0742] The "means for adjusting and providing a calculated purchase plan based on the user's emotions" refers to a means for adjusting a calculated purchase plan in consideration of the user's emotion data and providing the plan to the user.

[0743] The present invention is a system that allows a user to input a list of products they wish to purchase and proposes the optimal purchase plan, and also has the function of recognizing the user's emotions and adjusting the proposal content based on that information. The specific configuration for implementing this system is shown below.

[0744] First, a user uses a smartphone to input a list of products they wish to purchase. This smartphone is equipped with an emotion analysis engine that uses a camera and microphone to analyze the user's facial expressions and voice to obtain emotional data. The product list and emotional data input by the user are then sent to the server.

[0745] The server analyzes the received user request and emotional data, and launches a crawler bot to collect product price information from the Internet. This crawler bot patrols designated websites and obtains the latest price information for, for example, potatoes, carrots, onions, meat, roux, and apples.

[0746] The collected price information is sent to a server and input to a generative AI model. This generative AI model receives price information, user requests, and sentiment data as input data and calculates the optimal purchase plan. The generative AI model used here is, for example, OpenAI's text generation API.

[0747] The calculated purchase plan is adjusted taking into account the user's emotional data. If the user is feeling stressed, a simple and intuitive purchase plan is proposed to improve the user's satisfaction. This adjusted purchase plan is sent from the server to the user's device.

[0748] As a specific example, consider the case where a user requests, "I want to buy curry ingredients at the lowest price." The product list entered by the user includes potatoes, carrots, onions, meat, roux, and apples. If the emotional data indicates "stress," the server launches a crawler bot to collect price information for these items. The collected information is input into a generative AI model, which generates a simple and intuitive purchase plan to prevent the user from feeling stressed. An example of a prompt sentence is shown below.

[0749] Example prompt sentence:

[0750] "Products desired: {'Potatoes': '100 yen', 'Carrots': '50 yen', 'Onions': '30 yen', 'Meat': '200 yen', 'Rou': '150 yen', 'Apples': '300 yen'} User emotion: Stressed Please generate the optimal purchase plan."

[0751] According to this invention, it is possible to propose an optimal purchase plan taking into consideration the user's feelings, thereby greatly improving user satisfaction.

[0752] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0753] Step 1:

[0754] The user inputs a list of products they wish to purchase using their smartphone.

[0755] The input list may include, for example, "potatoes," "carrots," "onions," "meat," "roux," and "apples." List data is generated based on the user's input and sent from the terminal to the server. The output is the list data of the input products.

[0756] Step 2:

[0757] The user's device then uses its built-in camera and microphone to capture the user's facial expressions and voice.

[0758] Based on the acquired data, the emotion analysis engine analyzes the user's emotion data and obtains the analysis results (emotion data). This emotion data is also sent from the device to the server. The output is the user's emotion data.

[0759] Step 3:

[0760] The server receives and analyzes the user's list of desired products and emotion data.

[0761] Based on the analyzed data, the server issues a command to launch a crawler bot. The crawler bot crawls designated websites and collects the latest price information for each product. The input is the list data of products desired for purchase and emotion data, and the output is the collected price information.

[0762] Step 4:

[0763] The collected price information is sent to a server and stored in a database.

[0764] The server uses this price information to construct input data for the generative AI model. The input data to the generative AI model includes product names, prices, and user sentiment data. The output is the input data for the generative AI model.

[0765] Step 5:

[0766] The server inputs price information stored in a database and user emotion data into the generative AI model.

[0767] The generative AI model calculates the optimal purchase plan based on input data. The calculation process takes into account price comparisons for each product, inventory information, point reward services, and other factors. The output is the calculated optimal purchase plan.

[0768] Step 6:

[0769] The server adjusts the optimal purchase plan calculated by the generative AI model based on the user's emotional data.

[0770] For example, if the user is feeling "stressed," the system adjusts the calculated plan to be simple and intuitive. The input is the calculated purchase plan and the user's emotional data, and the output is an adjusted purchase plan based on the emotion.

[0771] Step 7:

[0772] The server sends the adjusted optimal purchase plan to the user's smartphone.

[0773] The user can check this purchase plan on their own terminal and purchase the product at the specified store. The output is the final purchase plan, which is the output the user receives.

[0774] This not only enables users to purchase multiple products at the lowest cost and most efficiently, but also allows users to receive optimal suggestions based on their emotions.

[0775] 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.

[0776] 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.

[0777] 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.

[0778] [Fourth embodiment]

[0779] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0780] 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.

[0781] 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).

[0782] 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.

[0783] 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.

[0784] 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).

[0785] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0786] 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.

[0787] 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.

[0788] 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.

[0789] 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.

[0790] 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.

[0791] 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."

[0792] The present invention provides a system that allows a user to input a list of products they wish to purchase and suggests an optimal purchasing plan. A method for implementing this system will be described in detail below using the procedures and configuration shown below.

[0793] First, the user uses the user terminal to input a list of products they wish to purchase. Specifically, the user uses a screen to input multiple products such as "potatoes," "carrots," "onions," "meat," and "roux." In addition, the user can input additional information such as "I would like to add apples as a secret ingredient."

[0794] Next, the server receives the user's request and analyzes its contents. Based on the analyzed data, the server launches a crawler bot. The crawler bot then crawls multiple websites on the Internet and automatically collects the latest price information for each product.

[0795] The collected price information is sent back to the server, which then inputs it into the generative AI model. The generative AI model calculates the optimal purchase plan based on the collected price information and the user's request (including additional information). The generative AI model also takes into account the price of each product, inventory information, price comparisons between multiple stores, and specific point reward services to generate the most economical plan.

[0796] The server then sends the calculated optimal purchase plan to the user's terminal. The user can then check the plan on their own terminal and purchase the products at the designated stores. This process allows the user to purchase multiple products at the lowest cost and most efficiently.

[0797] As a concrete example, consider the case where a user enters "I want to buy curry ingredients at the cheapest price." When the user enters "potatoes," "carrots," "onions," "meat," "roux," and "apples" into a list, the server receives this and launches a crawler bot. The crawler bot collects price information for each item, and the generative AI model calculates the optimal plan. For example, it can suggest the nearby supermarket with the lowest total price and also display the actual cost including the initial point reward.

[0798] This saves users the time and effort of comparing prices themselves, allowing them to shop in the most economical way possible.

[0799] The processing flow will be explained below.

[0800] Step 1:

[0801] The user uses a terminal to input the items they wish to purchase. Specifically, the user launches the application's input screen and inputs a list of ingredients such as "potatoes," "carrots," "onions," "meat," and "roux." They can also input additional information, such as "apple as a secret ingredient."

[0802] Step 2:

[0803] The terminal formats the input data and sends it to the server. The terminal compiles the list of products desired for purchase and additional information into one request data.

[0804] Step 3:

[0805] The server analyzes the request received from the terminal. Specifically, the server breaks down the request data and extracts the name of each product and additional information.

[0806] Step 4:

[0807] The server launches a crawler bot, which crawls multiple websites on the Internet and collects price information for the specified product.

[0808] Step 5:

[0809] The crawler bot sends the collected price information to a server, which receives it and stores it in a database.

[0810] Step 6:

[0811] The server launches a generative AI model based on the stored price information, which receives the price information and additional information as input and calculates the optimal purchase plan.

[0812] Step 7:

[0813] The server receives the optimal purchase plan calculated by the generative AI model, formats the plan, and prepares it for delivery to the user.

[0814] Step 8:

[0815] The server sends the calculated purchase plan to the user terminal, where the user can check the proposed plan.

[0816] Step 9:

[0817] The user purchases products at the specified store based on the proposed purchase plan, enabling the user to make the most economical and efficient purchases according to the information presented.

[0818] Example 1

[0819] 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."

[0820] The problem that this invention aims to solve is to provide the most economical and efficient purchase plan by allowing users to easily input a list of products they wish to purchase and quickly collecting the latest price information from multiple websites, thereby significantly reducing the time and effort required for users to compare product prices.

[0821] 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.

[0822] In this invention, the server includes a means for a user to input a list of products they wish to purchase, a means for the server to receive and analyze requests from the user, a means for a crawler bot to crawl websites and collect product price information, a generating AI model means for calculating an optimal purchase plan based on the collected price information, and a means for providing the calculated purchase plan to a user terminal, thereby enabling a user to purchase multiple products in the most economical and efficient manner.

[0823] The "means by which users input a list of products they wish to purchase" refers to an interface for users to input information about products they wish to purchase, and is composed of an application or web form using a device such as a smartphone or PC.

[0824] "The means by which the server receives and analyzes requests from users" refers to a program on the server that receives user input data and analyzes its contents, and has the function of extracting and classifying request data.

[0825] "Means for crawler bots to crawl websites and collect product price information" refers to a software program that automatically crawls multiple websites on the Internet and collects price and inventory information about products.

[0826] The "generative AI model means for calculating the optimal purchase plan based on collected price information" refers to an artificial intelligence model for calculating the optimal purchase plan based on collected price data and user request information, and includes a calculation algorithm that takes into account price comparison and point redemption.

[0827] The "means for providing the calculated purchase plan to the user's device" is a system for notifying the user of the optimal purchase plan calculated by the generative AI model, and has the function of delivering information to the user's device via the Internet.

[0828] The "means for the user to input additional information" is an interface that allows the user to input specific conditions or wishes in addition to the shopping list, and has the function of recording the user's specific requests.

[0829] "A means for collecting inventory and price information from multiple websites on the Internet and reflecting it in the optimal purchase plan" is a system that calculates the optimal purchase plan in real time using inventory and price information collected from multiple sites.

[0830] The present invention relates to a system that allows a user to input a list of products they wish to purchase and proposes an optimal purchasing plan. A method for implementing this system will be described in detail below using the procedures and configuration shown below.

[0831] First, the user uses a user terminal to input a list of items they wish to purchase. Specifically, the user uses an internet-connected device such as a smartphone or PC to input the list of items they wish to purchase into a dedicated app or web form. For example, the user can input items such as "potatoes," "carrots," "onions," "meat," and "roux," and can also enter additional information such as "I'd like to add apples as a secret ingredient."

[0832] Next, the server receives and analyzes the request from the user. The server analyzes the received data and extracts information about the entered product. Based on the analyzed data, the server issues a command to launch the crawler bot.

[0833] Crawler bots crawl multiple websites on the Internet and automatically collect the latest price and stock information for products. Crawler bots collect data such as product names, prices, stock status, and store information.

[0834] The collected price information is sent to a server, which inputs it into a generative AI model. The generative AI model calculates the optimal purchase plan based on the collected price information, the user's request, and additional information. The generative AI model performs its calculations by taking into account price comparisons, inventory information, price comparisons between multiple stores, specific point reward services, and more.

[0835] After calculating the optimal purchase plan, the server sends the calculation results to the user's terminal, where the user can check the proposed purchase plan and purchase the products at the specified store or online shop.

[0836] As a concrete example, consider the case where a user enters "I want to buy curry ingredients at the cheapest price." When the user enters "potatoes," "carrots," "onions," "meat," "roux," and "apples" into a list, the server receives this and launches a crawler bot. The crawler bot collects price and stock information for each item, and the generative AI model calculates the optimal purchase plan. For example, it can suggest the nearby supermarket or online shop with the lowest total price, and also display the actual cost including the initial point reward.

[0837] In this way, users can purchase multiple products at the lowest possible cost and most efficiently.

[0838] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0839] Step 1:

[0840] The user inputs a list of items they wish to purchase.

[0841] Specific operation: The user accesses a dedicated app or web form using a smartphone or PC and inputs a list of products such as "potatoes," "carrots," "onions," "meat," and "roux." They can also add additional information such as "I'd like to add apples as a secret ingredient."

[0842] Input: List of items you wish to purchase and additional information.

[0843] Output: Data entered into the input form.

[0844] Step 2:

[0845] The server receives and analyzes the request from the user.

[0846] How it works: The server receives the data sent from the user device and analyzes its contents to extract information about each product and additional information. The analysis is performed using a text processing algorithm.

[0847] Input: Data submitted by the user (list of products and additional information).

[0848] Output: A list of parsed products and additional information.

[0849] Step 3:

[0850] The server launches the crawler bot.

[0851] Specific operation: Based on the analyzed data, the server issues a command to launch a crawler bot, which then crawls designated websites and automatically collects the latest product price and stock information.

[0852] Input: A parsed list of products.

[0853] Output: Instructions to launch the crawler bot.

[0854] Step 4:

[0855] Crawler bots crawl websites and collect product price information.

[0856] Specific operation: The crawler bot accesses each website and collects price and stock information for products such as "potatoes" and "carrots" using web scraping technology.

[0857] Input: A list of specified products.

[0858] Output: Up-to-date price and availability information for each product.

[0859] Step 5:

[0860] The collected price information is fed into a generative AI model.

[0861] How it works: The crawler bot sends the collected price information to the server, which then inputs it into the generative AI model, which preprocesses the data and creates an input dataset for calculating the optimal purchase plan.

[0862] Input: Collected pricing and inventory information.

[0863] Output: The dataset that is input to the generative AI model.

[0864] Step 6:

[0865] A generative AI model calculates the optimal purchase plan.

[0866] How it works: Based on collected pricing information, the user's request, and additional information, the generative AI model calculates the optimal purchase plan, taking into account price comparisons, inventory availability, and multiple purchasing options.

[0867] Input: Input datasets (pricing information, inventory information, user requests).

[0868] Output: Best buy plan.

[0869] Step 7:

[0870] The server sends the calculation results to the user terminal.

[0871] Specific operation: The server receives the calculation results of the optimal purchase plan from the generative AI model and sends them to the user's device. The user receives and displays this data on their own device.

[0872] Enter: Best buy plan.

[0873] Output: The optimal purchase plan sent to the user device.

[0874] Step 8:

[0875] The user checks the purchase plan and purchases the product at the specified store or online shop.

[0876] Specific operation: The user checks the purchase plan sent on the device and purchases the product from the recommended store or online shop. The purchase plan describes the most economical and efficient way to purchase the product.

[0877] Input: The purchase plan displayed on the user's device.

[0878] Output: The actual action of purchasing the product.

[0879] (Application example 1)

[0880] 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."

[0881] In today's world, when users purchase products from multiple online shopping sites, it is extremely difficult to compare prices and find the optimal purchase plan. At the same time, they must also be able to respond to detailed requests based on product inventory information and specific conditions. In such situations, users end up spending a great deal of time and effort, resulting in a decrease in purchasing efficiency. To solve this problem, a system is needed that allows users to easily list products and automatically provides the optimal purchase plan.

[0882] 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.

[0883] In this invention, the server includes a means for a user to input a list of products they wish to purchase, a crawler bot means for collecting product price information from multiple websites on the Internet, a generation AI model means for calculating an optimal purchase plan based on the collected price information and additional information, a means for providing the calculated purchase plan to the user, and an application means for being installed on a smartphone. This allows the user to easily input a list of products they wish to purchase and quickly obtain an optimal purchase plan that includes additional conditions.

[0884] The term "means for a user to input a list of products that the user wishes to purchase" refers to an interface or function that allows the user to electronically input a list of products that the user wishes to purchase.

[0885] "Crawler bot means for collecting product price information from multiple websites on the Internet" refers to programs and functions for automatically crawling multiple websites on the Internet and collecting the latest product price information.

[0886] "Generative AI model means for calculating the optimal purchase plan based on collected price information and additional information" refers to the calculation function of an artificial intelligence model for calculating the optimal purchase plan using collected price information and additional information provided by the user.

[0887] "Means for providing the calculated purchase plan to the user" refers to an interface or function for presenting the optimal purchase plan calculated by the generative AI model in a form that is accessible to the user.

[0888] "Application means installed on a smartphone" refers to a software application that is downloaded and installed on a smartphone and can perform a series of operations from inputting a list of products desired to be purchased to being provided with the most suitable purchase plan.

[0889] "Means for collecting inventory information from nearby stores and online sales sites and reflecting it in an optimal purchasing plan" refers to functions and programs for collecting inventory information from nearby physical stores and online sales sites and incorporating that information into an optimal purchasing plan.

[0890] To implement the present invention, the following configuration and processing procedure are followed.

[0891] First, a user inputs a list of items they wish to purchase using an application installed on their smartphone. This application provides an interface that transmits the information the user inputs to the server. As a specific example, a user can input a list of items such as "potatoes," "carrots," "onions," "meat," and "roux," and then add additional information such as "I would like to add apples as a secret ingredient."

[0892] The server analyzes the received data and launches a crawler bot, which crawls multiple websites across the Internet to gather up-to-date pricing and availability information for the specified product. The crawler bot uses, for example, the Requests and BeautifulSoup libraries to extract the required information from the web pages.

[0893] The collected pricing information and additional information is sent back to the server and then fed into a generative AI model, which uses an artificial intelligence model such as OpenAI's GPT-3 to calculate the optimal purchase plan. An example prompt for this is below:

[0894] "Plan the best purchase plan for the following items:

[0895] Potatoes: 100 yen, carrots: 50 yen, onions: 80 yen, meat: 500 yen, roux: 200 yen, apples: 150 yen

[0896] Additional information: I like to add apples as a secret ingredient.

[0897] When calculating the optimal purchase plan, the generative AI model takes into account price and availability information, as well as specific rewards programs and user-defined conditions.

[0898] The calculated optimal purchase plan is sent from the server to the application, where the user can check it on their smartphone. The user can then purchase products from the designated online shopping site or a nearby store according to the purchase plan.

[0899] For example, if a user types "I want to buy curry ingredients at the cheapest price," a crawler bot will collect the prices of each item, and a generative AI model will calculate the optimal plan. For example, it will suggest the nearby store with the cheapest total price, and it will also display the actual cost including the initial point reward.

[0900] This allows users to significantly reduce the time and effort spent on price comparisons and planning purchases, enabling them to shop in an economical and efficient manner.

[0901] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0902] Step 1:

[0903] The user launches the application installed on their smartphone and inputs a list of products they wish to purchase. They can also input additional conditions as needed. As input, the user provides a list of products such as "potatoes," "carrots," "onions," "meat," and "roux," along with an additional condition such as "I would like to add apple as a secret ingredient." Based on this input, the application sends the data to the server.

[0904] Step 2:

[0905] The server receives and analyzes the data sent by the user. Specifically, it parses the received data to extract each product and additional conditions, and prepares to launch the crawler bot. It receives the JSON data entered by the user as input, extracts the product list and additional conditions, and generates structured data for launching the crawler bot.

[0906] Step 3:

[0907] The server launches a crawler bot to collect the latest product price information from multiple websites on the Internet. The crawler bot accesses each website and parses the HTML to extract price information. It receives a list of products as input and generates data containing price information for each product as output.

[0908] Step 4:

[0909] The server inputs the collected price information into the generative AI model. Specifically, the collected price information and the user's additional conditions are formatted as a prompt sentence and sent to the generative AI model to calculate the optimal purchase plan. The input is the price information and additional conditions, and the output is the optimal purchase plan.

[0910] Step 5:

[0911] The generative AI model calculates the optimal purchase plan. The calculation takes into account collected price information, inventory information, additional user conditions, point redemption information, etc. It receives price information and user conditions as input, and generates the optimal purchase plan in text format as output. For example, a detailed purchase plan is provided in the form of "Potatoes: 100 yen at store A, Carrots: 50 yen at store B."

[0912] Step 6:

[0913] The server sends the calculated optimal purchase plan to the user's smartphone. It receives the purchase plan from the generative AI model as input and generates data to display the plan on the user's device as output. This allows the user to check the optimal purchase plan on their smartphone.

[0914] Step 7:

[0915] The user purchases products at the specified store or online shopping site based on the purchase plan notified through the application. This eliminates the need for price comparisons and stock confirmation, enabling economical shopping. User behavior includes actually making a purchase using the optimal purchase plan provided by the application.

[0916] 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.

[0917] The present invention is a system that allows a user to input a list of items they wish to purchase and proposes the optimal purchase plan, and also has the ability to recognize the user's emotions and adjust the proposal content based on that information. A method for implementing this system will be described in detail using the following procedures and configuration.

[0918] First, the user uses the user terminal to input a list of items they wish to purchase. Specifically, the user uses a screen to input items such as "potatoes," "carrots," "onions," "meat," and "roux." Additional information can also be entered, such as "I'd like to add apple as a secret ingredient." Additionally, the user terminal is equipped with an emotion engine that analyzes the user's emotions from their facial expressions and voice, and sends that data to the system.

[0919] Next, the server receives the user's request and emotional data and analyzes the content. Based on the analyzed data, the server launches a crawler bot that crawls multiple websites on the Internet and automatically collects the latest price information for each product. The collected price information is then sent back to the server, which then inputs it into the generative AI model.

[0920] The generative AI model receives collected price information, user requests, and emotional data as input and calculates the optimal purchase plan. The generative AI model generates the most economical plan by taking into account the price of each product, inventory information, price comparisons between multiple stores, and specific point reward services. If the user is feeling dissatisfied or stressed, the emotion engine adjusts the suggestions to improve user satisfaction, such as suggesting simpler options by taking their emotions into consideration.

[0921] The calculated optimal purchase plan is sent by the server to the user's terminal. The user can then check the plan on their own terminal and purchase the products at the specified stores. This process not only enables the user to purchase multiple products at the lowest cost and most efficiently, but also allows the user to receive optimal suggestions based on their emotions.

[0922] As a concrete example, consider the case where a user inputs "I want to buy curry ingredients at the cheapest price." If the user inputs "potatoes," "carrots," "onions," "meat," "roux," and "apples" into a list, and the user's emotional data indicates "stress," the server not only launches a crawler bot to collect price information for each item, but also takes this emotional data into account and inputs it into the generative AI model. The generative AI model generates a simple and intuitive purchasing plan to prevent the user from feeling stressed, and the server sends this to the user's device. The user can purchase products in the most economical and efficient way possible, without feeling stressed.

[0923] The processing flow will be explained below.

[0924] Step 1:

[0925] The user uses a terminal to input the items they wish to purchase. The user inputs a list of items such as "potatoes," "carrots," "onions," "meat," and "roux." The user also inputs additional information such as "add apples as a secret ingredient."

[0926] Step 2:

[0927] The emotion engine installed in the device analyzes the user's facial expressions and voice and generates emotion data. For example, if it is determined that the user is feeling stressed, emotion data containing that information is sent from the device to the server.

[0928] Step 3:

[0929] The server analyzes the list of desired products and emotion data received from the terminal. The server breaks down the user's request, extracts the name of each product and additional information, and stores the emotion data separately.

[0930] Step 4:

[0931] The server launches a crawler bot, which crawls multiple websites on the Internet to gather the latest price information for the specified product.

[0932] Step 5:

[0933] The crawler bot sends the collected price information to a server, which stores it in a database.

[0934] Step 6:

[0935] The server launches a generative AI model based on the stored price information. The generative AI model receives price information, user requests, additional information, and emotional data as input data and calculates the optimal purchase plan.

[0936] Step 7:

[0937] The server receives the optimal purchase plan calculated by the generative AI model. The server then takes emotional data into account and adjusts the proposal to avoid stress for the user. For example, it prioritizes simple plans that minimize complex store-to-store travel.

[0938] Step 8:

[0939] The server sends the adjusted purchase plan to the user's terminal, where the user can check the plan.

[0940] Step 9:

[0941] The user purchases products at the designated store based on the proposed purchase plan, which not only allows the user to purchase products in the most economical and efficient way, but also increases emotional satisfaction.

[0942] Example 2

[0943] 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."

[0944] Conventional online shopping systems have difficulty generating optimal purchase plans simply by inputting the products a user wishes to purchase. Furthermore, they lack the functionality to provide purchase plans that take into account the user's emotions and reduce stress and dissatisfaction. As a result, there are problems with lower user satisfaction and a decrease in willingness to purchase.

[0945] 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.

[0946] In this invention, the server includes a means for a user to input a list of products they wish to purchase, a means for acquiring user emotion data, a crawler bot means for collecting product price information from websites, a generative AI model means for calculating an optimal purchase plan based on the collected price information and user emotion data, and a means for providing the calculated purchase plan to the user. This makes it possible to provide the most economical and efficient purchase plan while taking user emotions into consideration, thereby improving user satisfaction.

[0947] The "means for a user to input a list of products desired for purchase" refers to a means for a user to provide a list of products desired by the user to the system through text input, voice input, or other input method.

[0948] The "means for acquiring user emotion data" is a means for analyzing emotions from the user's facial expressions, voice, etc., and acquiring the analysis results as data.

[0949] The "crawler bot means for collecting product price information from websites" is a program that crawls multiple websites on the Internet and automatically collects the latest price information for each product.

[0950] The "generative AI model means for calculating an optimal purchase plan based on collected price information and user emotional data" is an artificial intelligence model for receiving collected price information and user emotional data as input data and generating an optimal purchase plan.

[0951] The "means for providing the calculated purchase plan to the user" is a means for transmitting the generated purchase plan to the user terminal so that the user can check the plan.

[0952] The present invention is a system that allows users to input a list of products they wish to purchase and proposes the optimal purchase plan, and also has the function of recognizing the user's emotions and adjusting the proposal content based on that information. In implementing this system, the user terminal and the server mainly work together.

[0953] System configuration and hardware / software used

[0954] First, the user uses the user terminal to input a list of products they wish to purchase. Specifically, they use a screen where they can input products such as "potatoes," "carrots," "onions," "meat," and "roux." In addition to the product list, the user can also input additional information such as "I'd like to add apples as a secret ingredient."

[0955] The user device is equipped with an emotion engine that analyzes emotions from the user's facial expressions and voice and sends the data to a server. The emotion engine's hardware includes a camera and microphone, and the software uses an emotion analysis program.

[0956] Next, the server receives the user's request and emotional data and analyzes the content. This analysis is performed using a database and analytical algorithms. Based on this analyzed data, the server launches a crawler bot, which crawls multiple websites on the Internet and automatically collects the latest price information for each product. The collected price information is then sent back to the server.

[0957] The server inputs price information, user requests, and emotional data into a generative AI model. The generative AI model uses technologies such as OpenAI's GPT-4 to calculate the most economical purchase plan, taking into account each product's price, inventory information, price comparisons between multiple stores, and specific point reward services. Additionally, if the user is feeling dissatisfied or stressed, the emotion engine will take their emotions into consideration and suggest simpler options, thereby improving user satisfaction.

[0958] The calculated optimal purchase plan is sent by the server to the user's terminal. The user can then check this plan on their own terminal and purchase the products at the specified store. This not only enables the user to purchase multiple products at the lowest cost and most efficiently, but also allows the user to receive optimal suggestions based on their emotions.

[0959] Examples of concrete examples and prompts

[0960] As a concrete example, consider the case where a user inputs "I want to buy curry ingredients at the cheapest price." If the user inputs "potatoes," "carrots," "onions," "meat," "roux," and "apples" into a list, and the user's emotional data indicates "stress," the server not only launches a crawler bot to collect price information for each item, but also takes this emotional data into account and inputs it into the generative AI model. The generative AI model generates a simple and intuitive purchasing plan to prevent the user from feeling stressed, and the server sends this to the user's device. The user can purchase products in the most economical and efficient way possible, without feeling stressed.

[0961] Example prompt sentence:

[0962] "Generate a plan to purchase ingredients for curry at the lowest price. The purchase list is potatoes, carrots, onions, meat, roux, and apples. User sentiment data indicates stress. Provide a simple and intuitive purchasing plan."

[0963] As a result, the present invention can improve user satisfaction and provide an optimal purchasing experience.

[0964] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0965] Step 1:

[0966] The user inputs a list of products that he or she wishes to purchase using the user terminal.

[0967] Specifically, the user enters items such as "potatoes," "carrots," "onions," "meat," and "roux" into an input form on the terminal screen. A shopping list is generated based on the input data and sent to the system.

[0968] Step 2:

[0969] The device acquires emotional data and analyzes the user's facial expressions and voice.

[0970] Specifically, the device's camera and microphone capture the user's facial expressions and voice, which are then analyzed by the emotion engine. Emotional data such as "stress" is generated as a result of the analysis and sent to the server.

[0971] Step 3:

[0972] The server receives the request and emotion data and analyzes the content.

[0973] Specifically, the server receives the purchase list and emotion data sent by the user and analyzes them using an analysis algorithm. The input data are the purchase list and emotion data, and the output is the analyzed information.

[0974] Step 4:

[0975] The server launches a crawler bot that crawls multiple websites on the Internet to collect the latest price information.

[0976] Specifically, the crawler bot patrols designated e-commerce sites and collects the latest price information for items such as potatoes, carrots, and onions. This collected price information is then saved on the server and output.

[0977] Step 5:

[0978] The server inputs collected price information, user requests, and sentiment data into a generative AI model.

[0979] Specifically, the server inputs the collected price information, request information from the user, and emotional data into a generative AI model (e.g., OpenAI's GPT-4). The generative AI model processes this data and calculates the optimal purchase plan. The input data are price information, user request, and emotional data, and the output is the generated purchase plan.

[0980] Step 6:

[0981] The server transmits the calculated purchase plan to the user terminal.

[0982] Specifically, the server sends the purchase plan created by the generative AI model to the user's device. The optimal purchase method for multiple products is displayed on the device. The input data is the generated purchase plan, and the output is the plan information displayed on the user's device.

[0983] Step 7:

[0984] The user confirms the purchase plan and purchases the product at the specified store.

[0985] Specifically, the user checks the purchase plan displayed on the terminal and purchases products at each store according to that plan. Specific store information is displayed as the optimal purchase method, such as "purchase potatoes at supermarket A" and "purchase carrots at supermarket B." The input data is the displayed purchase plan, and the output is the products actually purchased by the user.

[0986] (Application example 2)

[0987] 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."

[0988] Current shopping support systems propose optimal purchase plans based on product lists and price information entered by users, but because they do not take into account the user's emotional state, they may produce proposals that are unsatisfying. Furthermore, because they do not take into consideration users who are stressed or dissatisfied, there is a problem that the user experience is not improved. The objective of this invention is to provide a more satisfying shopping experience by analyzing the user's emotions and making proposals accordingly.

[0989] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0990] In this invention, the server includes means for a user to input a list of products they wish to purchase, crawler bot means for collecting product price information from websites, generation AI model means for calculating an optimal purchase plan based on the collected price information, means for analyzing the user's emotional data using an emotion analysis engine, and means for adjusting and providing the calculated purchase plan based on the user's emotions. This makes it possible to propose an optimal purchase plan that takes the user's emotional state into consideration, improving the user experience.

[0991] The "means for the user to input a list of products that the user wishes to purchase" is an interface that allows the user to input the products that the user wishes to purchase in list form.

[0992] A "crawler bot means for collecting product price information from websites" is a software robot that crawls websites on the Internet and automatically collects product price information.

[0993] The "generative AI model means for calculating the optimal purchase plan based on collected price information" is an artificial intelligence model that receives collected product price information as input data and calculates the optimal purchase plan.

[0994] The "means for analyzing the user's emotional data using an emotional analysis engine" refers to software and hardware for analyzing the user's facial expressions and voice and acquiring emotional data.

[0995] The "means for adjusting and providing a calculated purchase plan based on the user's emotions" refers to a means for adjusting a calculated purchase plan in consideration of the user's emotion data and providing the plan to the user.

[0996] The present invention is a system that allows a user to input a list of products they wish to purchase and proposes the optimal purchase plan, and also has the function of recognizing the user's emotions and adjusting the proposal content based on that information. The specific configuration for implementing this system is shown below.

[0997] First, a user uses a smartphone to input a list of products they wish to purchase. This smartphone is equipped with an emotion analysis engine that uses a camera and microphone to analyze the user's facial expressions and voice to obtain emotional data. The product list and emotional data input by the user are then sent to the server.

[0998] The server analyzes the received user request and emotional data, and launches a crawler bot to collect product price information from the Internet. This crawler bot patrols designated websites and obtains the latest price information for, for example, potatoes, carrots, onions, meat, roux, and apples.

[0999] The collected price information is sent to a server and input to a generative AI model. This generative AI model receives price information, user requests, and sentiment data as input data and calculates the optimal purchase plan. The generative AI model used here is, for example, OpenAI's text generation API.

[1000] The calculated purchase plan is adjusted taking into account the user's emotional data. If the user is feeling stressed, a simple and intuitive purchase plan is proposed to improve the user's satisfaction. This adjusted purchase plan is sent from the server to the user's device.

[1001] As a specific example, consider the case where a user requests, "I want to buy curry ingredients at the lowest price." The product list entered by the user includes potatoes, carrots, onions, meat, roux, and apples. If the emotional data indicates "stress," the server launches a crawler bot to collect price information for these items. The collected information is input into a generative AI model, which generates a simple and intuitive purchase plan to prevent the user from feeling stressed. An example of a prompt sentence is shown below.

[1002] Example prompt sentence:

[1003] "Products desired: {'Potatoes': '100 yen', 'Carrots': '50 yen', 'Onions': '30 yen', 'Meat': '200 yen', 'Rou': '150 yen', 'Apples': '300 yen'} User emotion: Stressed Please generate the optimal purchase plan."

[1004] According to this invention, it is possible to propose an optimal purchase plan taking into consideration the user's feelings, thereby greatly improving user satisfaction.

[1005] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1006] Step 1:

[1007] The user inputs a list of products they wish to purchase using their smartphone.

[1008] The input list may include, for example, "potatoes," "carrots," "onions," "meat," "roux," and "apples." List data is generated based on the user's input and sent from the terminal to the server. The output is the list data of the input products.

[1009] Step 2:

[1010] The user's device then uses its built-in camera and microphone to capture the user's facial expressions and voice.

[1011] Based on the acquired data, the emotion analysis engine analyzes the user's emotion data and obtains the analysis results (emotion data). This emotion data is also sent from the device to the server. The output is the user's emotion data.

[1012] Step 3:

[1013] The server receives and analyzes the user's list of desired products and emotion data.

[1014] Based on the analyzed data, the server issues a command to launch a crawler bot. The crawler bot crawls designated websites and collects the latest price information for each product. The input is the list data of products desired for purchase and emotion data, and the output is the collected price information.

[1015] Step 4:

[1016] The collected price information is sent to a server and stored in a database.

[1017] The server uses this price information to construct input data for the generative AI model. The input data to the generative AI model includes product names, prices, and user sentiment data. The output is the input data for the generative AI model.

[1018] Step 5:

[1019] The server inputs price information stored in a database and user emotion data into the generative AI model.

[1020] The generative AI model calculates the optimal purchase plan based on input data. The calculation process takes into account price comparisons for each product, inventory information, point reward services, and other factors. The output is the calculated optimal purchase plan.

[1021] Step 6:

[1022] The server adjusts the optimal purchase plan calculated by the generative AI model based on the user's emotional data.

[1023] For example, if the user is feeling "stressed," the system adjusts the calculated plan to be simple and intuitive. The input is the calculated purchase plan and the user's emotional data, and the output is an adjusted purchase plan based on the emotion.

[1024] Step 7:

[1025] The server sends the adjusted optimal purchase plan to the user's smartphone.

[1026] The user can check this purchase plan on their own terminal and purchase the product at the specified store. The output is the final purchase plan, which is the output the user receives.

[1027] This not only enables users to purchase multiple products at the lowest cost and most efficiently, but also allows users to receive optimal suggestions based on their emotions.

[1028] 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.

[1029] 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.

[1030] 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.

[1031] 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.

[1032] 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.

[1033] 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.

[1034] 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).

[1035] 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.

[1036] 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."

[1037] 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.

[1038] 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).

[1039] 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.

[1040] 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.

[1041] 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.

[1042] 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.

[1043] 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.

[1044] 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.

[1045] 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.

[1046] 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.

[1047] 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.

[1048] 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.

[1049] The following is further disclosed regarding the above embodiment.

[1050] (Claim 1)

[1051] A means for a user to input a list of products they wish to purchase;

[1052] a crawler bot means for collecting product price information from a website;

[1053] A generative AI model means for calculating an optimal purchase plan based on collected price information;

[1054] means for providing the calculated purchase plan to the user;

[1055] A system including:

[1056] (Claim 2)

[1057] 10. The system of claim 1, further comprising means for a user to input additional information.

[1058] (Claim 3)

[1059] 2. The system according to claim 1, further comprising means for collecting inventory information from nearby stores and reflecting the information in an optimal purchasing plan.

[1060] "Example 1"

[1061] (Claim 1)

[1062] A means for a user to input a list of products they wish to purchase;

[1063] A means for the server to receive and analyze requests from users;

[1064] A crawler bot crawls websites and collects product price information;

[1065] A generative AI model means for calculating an optimal purchase plan based on collected price information;

[1066] means for providing the calculated purchase plan to a user terminal;

[1067] A system including:

[1068] (Claim 2)

[1069] 10. The system of claim 1, further comprising means for a user to input additional information.

[1070] (Claim 3)

[1071] 10. The system according to claim 1, further comprising means for collecting inventory information and price information from a plurality of websites on the Internet and reflecting the information in an optimal purchase plan.

[1072] "Application Example 1"

[1073] (Claim 1)

[1074] A means for a user to input a list of products they wish to purchase;

[1075] a crawler bot means for collecting product price information from multiple websites on the Internet;

[1076] a generative AI model means for calculating an optimal purchase plan based on the collected price information and additional information;

[1077] means for providing the calculated purchase plan to the user;

[1078] an application means installed on a smartphone;

[1079] A system including:

[1080] (Claim 2)

[1081] 10. The system of claim 1, further comprising means for a user to input additional information.

[1082] (Claim 3)

[1083] 2. The system according to claim 1, further comprising means for collecting inventory information from nearby stores and mail order sites and reflecting the information in an optimal purchasing plan.

[1084] "Example 2: Combining Emotion Engines"

[1085] (Claim 1)

[1086] A means for a user to input a list of products they wish to purchase;

[1087] A means for acquiring user emotion data;

[1088] a crawler bot means for collecting product price information from a website;

[1089] A generative AI model means for calculating an optimal purchase plan based on collected price information and user sentiment data;

[1090] means for providing the calculated purchase plan to the user;

[1091] A system including:

[1092] (Claim 2)

[1093] 10. The system of claim 1, further comprising means for a user to input additional information.

[1094] (Claim 3)

[1095] 2. The system according to claim 1, further comprising means for collecting inventory information from nearby stores and reflecting the information in an optimal purchasing plan.

[1096] "Application example 2 when combining emotion engines"

[1097] (Claim 1)

[1098] A means for a user to input a list of products they wish to purchase;

[1099] a crawler bot means for collecting product price information from a website;

[1100] A generative AI model means for calculating an optimal purchase plan based on collected price information;

[1101] means for analyzing user emotion data by an emotion analysis engine;

[1102] A means for adjusting and providing the calculated purchase plan based on the user's emotions;

[1103] A system including:

[1104] (Claim 2)

[1105] 10. The system of claim 1, further comprising means for a user to input additional information.

[1106] (Claim 3)

[1107] 2. The system according to claim 1, further comprising means for collecting inventory information from nearby stores and reflecting the information in an optimal purchasing plan. [Explanation of symbols]

[1108] 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 a user to input a list of products they wish to purchase; a crawler bot means for collecting product price information from a website; A generative AI model means for calculating an optimal purchase plan based on collected price information; means for providing the calculated purchase plan to the user; A system including:

2. 10. The system of claim 1, further comprising means for a user to input additional information.

3. 2. The system according to claim 1, further comprising means for collecting inventory information from nearby stores and reflecting the information in an optimal purchasing plan.

Images