System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting data relating to products, services, or location information from a variety of data sources; means for storing and pre-processing the collected data in a database; means for executing an algorithm that calculates a statistical value based on a plurality of metrics; and means for receiving information requests from users and returning value information.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] Describe the "problem that the invention aims to solve" and the "means for solving the problem."

[0005] ---

[0006] In today's market, product and service ratings, even location-based ratings, are provided by a wide variety of sources, making it extremely difficult for users to determine their legitimacy and fairness. For example, the same product may have different prices and ratings depending on the sales platform and seller, requiring users to spend time and effort to make the optimal choice. In this environment, there is a need for a system that allows users to easily understand reliable, fair, and impartial values. [Means for solving the problem]

[0007] The present invention provides a system that includes a means for collecting data related to products, services, or location information from various data sources, a means for storing the collected data in a database and performing preprocessing, a means for executing an algorithm for calculating statistical value based on multiple indicators, and a means for receiving information requests from users and returning value information. This allows users to easily obtain highly reliable and fair value information from various information sources and make optimal choices. Furthermore, by including a means for performing data cleaning to remove outliers and fraudulent data, and a means for calculating value by integrating review evaluation points, it is possible to provide highly accurate and fair value information.

[0008] ---

[0009] "Data Sources" are multiple sources of information that provide information about products, services, or location information.

[0010] "Means of collection" refers to the method or device for collecting the necessary information from the data source using an API, web scraping tool, etc.

[0011] A "database" is a structured data storage system for storing collected information.

[0012] "Preprocessing" refers to the initial stage of processing to improve data quality, such as data cleaning and consistency checks.

[0013] An "algorithm" is a set of procedures or calculations for calculating statistical values ​​from given data.

[0014] "User" is a consumer or user who uses the system and wants to know the value of a product, service, or location information.

[0015] A "means for receiving information requests" is an interface or protocol for receiving queries or requests from users.

[0016] "Value Information" is the evaluation result of a product, service, or location information calculated using collected data and algorithms.

[0017] "Data cleaning" is the process of removing outliers and incorrect data from a dataset to ensure data integrity and accuracy.

[0018] "Integration" is a method of unifying multiple indicators obtained from different data sources to evaluate overall value.

[0019] "Pricing Information" means data regarding sales prices associated with particular products or services.

[0020] "Review rating points" are data that quantify or categorize the ratings or feedback that users give to products or services.

[0021] An "outlier" is an unusual data point that is significantly different from the rest of the data set.

[0022] "Incorrect Data" means information that is inaccurate, unreliable, false, or incomplete. [Brief explanation of the drawings]

[0023] [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

[0024] 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.

[0025] First, the terms used in the following description will be explained.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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."

[0031] [First embodiment]

[0032] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0033] 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.

[0034] 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).

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0040] 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.

[0041] 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.

[0042] 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.

[0043] 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."

[0044] ---

[0045] The present invention relates to a system that calculates the fair and equitable value of products, services, or location information based on data about the products, services, or location information that users obtain from various sources. This system is composed of components including a server, a terminal, and a user. A specific embodiment is described below.

[0046] System Overview

[0047] server

[0048] The server collects data related to products, services, or location information from various data sources via the Internet. The collected data is stored in a database, where data cleaning is performed to remove outliers and invalid data. The server also runs an algorithm to calculate statistical value using multiple indicators based on the collected data.

[0049] Terminal

[0050] The terminal receives information requests from users and sends them to the server. It has the function of displaying the value information returned from the server. Users can easily check fair and impartial value information through the terminal.

[0051] User

[0052] Users want to know the value of a product, service, or location information, so they use their device to make an information request and use the returned value information to make a purchase decision or use decision for the product or service.

[0053] Program processing overview

[0054] 1. Data Collection

[0055] The server uses various APIs and web scraping tools to gather the required information from data sources, such as price information from online stores, ratings from review sites, and location information from map services.

[0056] 2. Data storage and preprocessing

[0057] The server stores the collected data in a database, where data cleaning is performed to remove invalid data and outliers and improve the quality of the data.

[0058] 3. Value Calculation Algorithm

[0059] The server runs an algorithm that calculates the mean, median, and standard deviation of the price information and aggregates the review rating points to calculate the value of the product, service, or location information in question.

[0060] 4. User Request Processing

[0061] The device receives a request from the user and sends the information to the server. For example, a user wants to check the value of a "specific product" on their smartphone, and the device sends the request to the server.

[0062] 5. Presentation of value information

[0063] The server retrieves value information from the database based on the request and returns it to the terminal. The terminal displays the value information received from the server to the user. For example, information such as the average price, review rating, and ranking of the product is displayed.

[0064] Specific examples

[0065] For example, if a user wants to know the value of a certain electronic device,

[0066] 1. A user uses a smartphone to input a request to find out the value of an electronic device into the device.

[0067] 2. The device sends the request to the server.

[0068] 3. The server collects price information and evaluation data related to electronic devices from online stores, review sites, etc. and stores it in a database.

[0069] 4. The server performs data cleaning to remove outliers and unreliable data.

[0070] 5. The server runs a value calculation algorithm to calculate the value of the electronic device by combining the average, median, standard deviation, and review rating points of the price.

[0071] 6. The server returns the calculated value information to the terminal.

[0072] 7. The terminal displays the received value information to the user, who then decides whether or not to make a purchase based on that information.

[0073] By implementing such an embodiment, the system of the present invention allows users to efficiently obtain highly reliable value information from a vast number of information sources and make fair and impartial judgments.

[0074] The processing flow will be explained below.

[0075] ---

[0076] Step 1:

[0077] A server collects data about products, services, or locations from multiple data sources over the Internet, for example, using an online store's API to obtain pricing information and reviews, and a map service's API to obtain location information and user ratings.

[0078] Step 2:

[0079] The server stores the collected data in a database, where it remains raw and is saved for further processing.

[0080] Step 3:

[0081] The server performs data cleaning to remove outliers and fraudulent data from the stored data, for example filtering out abnormally high prices or impossible review ratings.

[0082] Step 4:

[0083] The server runs a value calculation algorithm based on the cleaned data, which calculates the average, median, and standard deviation of the price information, and also takes into account review evaluation points to calculate the overall value.

[0084] Step 5:

[0085] The terminal receives a request for information from a user and transmits the request to a server. For example, a user uses the terminal to input, "I want to know the value of a particular electronic device."

[0086] Step 6:

[0087] The server receives the request from the terminal and retrieves value information about the requested product or service from the database. The retrieved information includes the statistical value calculated in the previous step.

[0088] Step 7:

[0089] The server returns value information to the terminal, including the average, median, and standard deviation of detailed prices, review evaluation points, and so on.

[0090] Step 8:

[0091] The terminal displays the value information received from the server to the user, allowing the user to easily confirm that the value information is fair and impartial.

[0092] Step 9:

[0093] Users make decisions about purchasing or using products or services based on the displayed value information. For example, they might decide, "This electronic device has an average price of 50,000 yen and a review rating of 4.5 / 5, so it's worth buying."

[0094] Through the above steps, the system of the present invention can provide users with highly reliable and fair value information and support efficient decision-making.

[0095] Example 1

[0096] 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."

[0097] Conventional systems face challenges in consistently collecting data on products, services, or location information from a variety of sources and assessing its value, making it difficult for users to make accurate and fair judgments. In particular, they face challenges in ensuring the reliability and quality of data, and in lacking algorithms for calculating value using appropriate indicators based on collected data. Furthermore, they lack the functionality to quickly and accurately provide value information in response to user requests.

[0098] 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.

[0099] In this invention, the server includes means for collecting information on products, services, or location information from various information sources, means for storing the collected information in a database and performing preprocessing, means for executing an algorithm for calculating statistical value based on multiple indicators, means for receiving information requests from users and returning value information, and means for displaying the value information on user terminals, thereby enabling users to quickly obtain highly reliable value information and make accurate and fair decisions.

[0100] "Diverse sources" refers to multiple data providers that provide data about products, services, or locations.

[0101] "Product" refers to an individual or set of goods or consumer goods sold in a particular market.

[0102] "Service" refers to a transaction related to the provision of a particular activity or functionality.

[0103] "Location information" is data that indicates a geographical location, and includes coordinates and address information of a specific location.

[0104] "Means of collecting information" refers to a system configuration that automatically obtains data using APIs or web scraping tools.

[0105] "Database" means an electronic storage system that organizes and stores collected information so that it can be efficiently retrieved and used at a later time.

[0106] "Preprocessing means" refers to processing to improve the quality of collected data using methods such as data cleaning and data normalization.

[0107] "Multiple metrics" refers to different metrics or calculation methods for assessing and analyzing data characteristics and trends. Examples include mean, median, standard deviation, etc.

[0108] "Statistical value calculation algorithm" refers to a mathematical method or computational model that analyzes collected data and provides an objective value assessment.

[0109] "Means for receiving an information request and returning value information" refers to the process of searching a database in response to an inquiry from a user and returning the relevant information to the user.

[0110] "User Device" means an electronic device used by a User to enter information requests and view returned information. Examples include smartphones, tablets, and personal computers.

[0111] The present invention relates to a system that calculates the fair and equitable value of products, services, or location information based on data about the products, services, or locations that users obtain from various sources. This system consists of three components: a server, a terminal, and a user.

[0112] System Overview

[0113] server

[0114] The server collects data from various sources via the internet. Specific software used for this includes APIs and web scraping tools. For example, an API is used to obtain pricing information from online stores, and a web scraping tool is used to collect ratings from review sites. The collected data is stored in a database such as MySQL. The server then performs data cleaning to remove outliers and invalid data and improve data quality. Furthermore, the server calculates the mean, median, and standard deviation of the price information and runs algorithms that combine review rating points to calculate the value of the product, service, and location information.

[0115] Terminal

[0116] The terminal has the function of receiving information requests from users and sending those requests to a server. Specific examples of terminals include smartphones, tablets, and PCs. When a user inputs a request through the terminal, the request is sent to the server as an HTTP request. The value information returned from the server is displayed to the user by the terminal. The displayed content is diverse and includes, for example, "average product price," "review rating," and "ranking."

[0117] User

[0118] When a user wants to know the value of a particular product, service, or location, they use their device to request that information. An example of a request might be, "What is the market value of this electronic device?" They send a request and use the returned value information to make a purchasing decision on the product or service.

[0119] Specific examples

[0120] For example, if a user wants to know the value of an iPhone 13,

[0121] 1. A user uses their smartphone to enter a request such as, "I want to know the value of my iPhone 13."

[0122] 2. The device sends the request to the server. The request format will be something like "Product name: iPhone 13."

[0123] 3. The server collects price information and evaluation data related to the iPhone 13 from online stores (e.g., Amazon and Rakuten) and review sites (e.g., Kakaku.com) and stores it in a database.

[0124] 4. The server performs data cleaning to remove unreliable data and outliers.

[0125] 5. The server runs a value calculation algorithm and calculates the value of the iPhone 13 by combining the average price, median price, standard deviation, and review rating points. For example, the result is "average price is 100,000 yen, and review rating is 4.8 / 5."

[0126] 6. The server returns the calculated value information to the terminal.

[0127] 7. The terminal displays the received value information to the user, who then decides whether or not to make a purchase based on that information.

[0128] This system allows users to efficiently obtain highly reliable value information and make fair and impartial decisions.

[0129] Prompt Sentence Examples

[0130] "I'd like to know the market value of this electronic device. I'd like the market value calculated based on online store pricing, reviews, and related data."

[0131] This system's series of processes allows users to quickly obtain highly reliable value information from a vast number of information sources, enabling them to make more accurate decisions regarding purchases and usage.

[0132] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0133] Processing Steps

[0134] Step 1:

[0135] A server collects data about products, services, or locations from various sources. Specific tools used for collection include APIs and web scraping tools. For example, an online store's API can be called to obtain price information, and a web scraping tool can be used to collect rating data from review sites. The source's URL and API key are used as input, and the collected raw data is obtained as output.

[0136] Step 2:

[0137] The server stores the collected data in a database. For this, a database management system such as MySQL or PostgreSQL is used. Before storing it in the database, the data structure is unified and duplicate data is removed. Raw data is given as input, and cleaned data is stored in the database as output.

[0138] Step 3:

[0139] The server performs data cleaning on the stored data. This includes removing invalid data and outliers, and filling in missing data. Specifically, if the price of a certain product is extremely high or low, the data is removed. Missing values ​​are also filled in with the mean or median. The data stored in the database is given as input, and cleaned data is obtained as output.

[0140] Step 4:

[0141] The server runs an algorithm that calculates statistical value based on multiple indicators. It calculates the average, median, and standard deviation of price information and integrates review evaluation points. For example, it calculates the overall value by taking the average price information of a specific product and weighting it with the evaluation points from review sites. Cleaned data is given as input, and value information is obtained as output.

[0142] Step 5:

[0143] A user uses a device to input a request to find out the value of a particular product or service. For example, they might type "Find out the value of an iPhone 13" on their smartphone. The user's request is given as input, and the request is sent from the device to the server as output.

[0144] Step 6:

[0145] The server receives a request from the terminal and searches the database for value information on the corresponding product or service. The user request is given as input, and the corresponding value information is obtained from the server as output.

[0146] Step 7:

[0147] The server formats the acquired value information and returns it to the terminal. For example, detailed value information including the average price, median price, standard deviation price, review evaluation points, etc. is formatted. The acquired value information is given as input, and the formatted value information is returned to the terminal as output.

[0148] Step 8:

[0149] The terminal displays the received value information to the user. For example, for a specific electronic device, information such as "average price is 100,000 yen, and review rating is 4.8 / 5" is displayed. The value information returned from the server is given as input, and the specific value information is displayed on the user's screen as output.

[0150] Through this series of processing steps, the user can efficiently obtain highly reliable value information and make a fair and impartial decision.

[0151] (Application example 1)

[0152] 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."

[0153] Today's users face difficulties in accurately and quickly grasping the value of products and services obtained from a variety of information sources. It also takes a great deal of time and effort to find reliable data from the vast amount of information and to make a fair and impartial value assessment. Furthermore, when selecting a product or service, users are required to comprehensively evaluate multiple indicators, such as price and reviews, but this is not easy to achieve. A system that solves these problems is needed.

[0154] 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.

[0155] In this invention, the server includes means for collecting data on products, services, or location information from various data sources, means for storing the collected data in a database and performing preprocessing, means for executing an algorithm for calculating statistical value based on multiple indicators, means for receiving information requests on products or services from a user's terminal, generating value information based on the request, and returning the value information to the user's terminal, and means for triggering data collection using the barcode or name of the product or service. This enables users to quickly and efficiently perform reliable, fair, and impartial value assessments based on data obtained from various information sources.

[0156] - "Diverse data sources" refers to the means of obtaining data from various information providers on the Internet, APIs, web scraping tools, etc.

[0157] "Products" refers to physical and digital goods sold in the Marketplace.

[0158] "Services" include any activities, functions, or skills provided for a fee or free of charge.

[0159] "Location Information" refers to data relating to a geographic location or position.

[0160] A "database" is a system for efficiently storing, managing, and retrieving collected data.

[0161] "Preprocessing" refers to data quality improvement measures including data cleaning, normalization, and conversion to another format.

[0162] "Statistical value" refers to the overall evaluation of the data calculated based on the mean, median, standard deviation, and other statistical indicators.

[0163] An "algorithm" refers to a set of procedures or formulas for performing a particular calculation or operation.

[0164] "User terminal" includes devices used by users, such as smartphones, tablets, and personal computers.

[0165] An "information request" refers to an operation in which a user requests specific information through a terminal.

[0166] "Value information" refers to the evaluation results of products, services, or location information analyzed based on collected data.

[0167] A "barcode" is a visual representation of a unique sequence of numbers and / or letters used to identify a product.

[0168] "Name" means a unique word or phrase used to identify a particular product or service.

[0169] The present invention relates to a system that calculates the fair and equitable value of products, services, or location information based on data about the products, services, or location information that a user obtains from various information sources. The system is composed of components including a server, a terminal, and a user. Specific embodiments are described below.

[0170] System Overview

[0171] server

[0172] The server collects data about products, services, or location information from various data sources via the Internet. Data sources include online stores, review sites, and map services. The collected data is stored in a database, and data cleaning is performed to remove outliers and invalid data. The server also runs an algorithm that calculates statistical value using multiple indicators based on the collected data. This algorithm calculates the average, median, and standard deviation of price information and calculates the value of the product or service by integrating review evaluation points.

[0173] Terminal

[0174] The terminal receives an information request from the user and sends the request to the server. The request includes the name of the product or service and a barcode. It has the function of displaying the value information returned from the server. Specifically, a mobile device such as a smartphone or tablet is used as the terminal. The user can easily check fair and impartial value information through the terminal.

[0175] User

[0176] A user wants to know the value of a product, service, or location information, so they use their device to make an information request. Based on the returned value information, they can make a decision to purchase or use the product or service. For example, if a user wants to know the value of a certain electronic device, they can use their smartphone to enter the name or barcode of the electronic device and obtain the value information from the server.

[0177] Program processing

[0178] This program mainly handles the following processes: data collection, data cleaning, value calculation, and user request processing.

[0179] Hardware and software used

[0180] Hardware: User devices such as smartphones, tablets, and PCs

[0181] Software: Programming languages ​​and libraries such as Python, requests, statistics, numpy, etc. APIs used include online store APIs and review site APIs.

[0182] Specific examples

[0183] For example, if a user wants to know the value of an "iPhone 13," they open their smartphone and enter "iPhone 13" as the product name. The device sends this request to the server. The server collects price information and review ratings from online stores and review sites and stores them in a database. It performs data cleaning to remove outliers and invalid data, and calculates the value by combining the mean, median, standard deviation, and review rating points of the price information. The server sends the calculated value information back to the device, and the device displays the received value information to the user.

[0184] Prompt Sentence Examples

[0185] The user can use prompts such as:

[0186] "What is the value of the iPhone 13? I'd like to know a fair and impartial value based on price information and review ratings."

[0187] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0188] Step 1: Data collection

[0189] Based on the product or service name or barcode specified by the user, the server collects relevant data using online store APIs or review site APIs. Information obtained from data sources includes price information, review ratings, location information, etc. The input of this step is the user request, and the output is the collected raw data.

[0190] Step 2: Data storage and preprocessing

[0191] The server stores the collected raw data in a database and performs preprocessing, which includes data cleaning to remove outliers and invalid data. The input of this step is the collected raw data, and the output is a clean dataset.

[0192] Step 3: Data cleaning

[0193] The server runs a data cleaning process on the stored data to remove outliers and incorrect data, which may include, for example, removing unusually high or low prices. The input to this step is the stored raw data, and the output is the cleaned data.

[0194] Step 4: Value calculation

[0195] The server runs an algorithm to calculate statistical value based on the cleaned data. Specifically, it calculates the mean, median, and standard deviation of the price information and integrates the review rating points. The input of this step is the cleaned data, and the output is the calculated value information.

[0196] Step 5: User Request Processing

[0197] The terminal receives an information request from the user and sends that information to the server. The user inputs a product name or barcode, and the terminal sends that data to the server as a request. The input of this step is the user's request, and the output is the request sent to the server.

[0198] Step 6: Retrieving data based on the request

[0199] The server searches for and acquires the corresponding license information from the database based on the request received from the terminal. The input to this step is the request from the terminal, and the output is the acquired license information.

[0200] Step 7: Return and display of value information

[0201] The server returns the acquired value information to the terminal, which then displays it to the user. This allows the user to check information such as the average price, median, standard deviation, and review rating of the product or service. The input to this step is the value information from the server, and the output is the information displayed to the user.

[0202] 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.

[0203] ---

[0204] This invention combines a system that calculates the fair and equitable value of products, services, or location data obtained by users from various sources with an emotion engine that recognizes and analyzes user emotions. This system is composed of the following components: a server, a terminal, a user, and the emotion engine. A specific embodiment is shown below.

[0205] System Overview

[0206] server

[0207] The server collects data related to products, services, or location information from various data sources via the Internet. The collected data is stored in a database, and data cleaning is performed to remove outliers and invalid data. The server then runs an algorithm to calculate statistical value using multiple indicators based on the collected data and sentiment data.

[0208] Terminal

[0209] The device receives information requests and emotion information from the user and sends the requests to the server. It also has the function of displaying the value information returned from the server. The user can easily check the fair and just value information through the device.

[0210] User

[0211] When a user wants to know the value of a product, service, or location, they use their device to make an information request and express their emotions through facial expressions, voice, or text, which are then analyzed by the emotion engine.

[0212] Emotion Engine

[0213] The emotion engine recognizes emotions from the user's facial expressions, voice, or text and stores them in a database. The server then applies this emotion data to a value calculation algorithm to provide personalized value information corresponding to the user's emotions.

[0214] Program processing overview

[0215] 1. Data Collection

[0216] The server collects the necessary information from multiple data sources, such as online stores, review sites, and map services, and stores it in a database.

[0217] 2. Data storage and preprocessing

[0218] The server stores the collected data in a database and performs data cleaning to remove outliers and invalid data.

[0219] 3. Collecting Emotional Data

[0220] The terminal acquires data for recognizing emotions through the user's facial expressions, voice, or text, and sends it to the emotion engine.

[0221] 4. Sentiment analysis

[0222] The emotion engine analyzes the collected facial, voice, or text data to recognize the user's emotions, and the recognized emotion data is stored in a database.

[0223] 5. Value Calculation Algorithm

[0224] The server runs a value calculation algorithm based on the cleaned data and sentiment data, and calculates the overall value by integrating the average, median, and standard deviation of the price and review rating points.

[0225] 6. User Request Processing

[0226] The terminal receives a request from the user and transmits the request and the user's emotion data to the server.

[0227] 7. Obtaining and returning value information

[0228] The server receives the request, retrieves value information for the requested product, service, or location information from a database, and returns it to the terminal.

[0229] 8. Display of Value Information

[0230] The terminal displays the value information received from the server to the user, allowing the user to easily confirm that the value information is fair and impartial.

[0231] Specific examples

[0232] For example, if a user wants to know the value of a certain cafe,

[0233] 1. A user uses a smartphone to input a request to find out the value of a cafe.

[0234] 2. The device sends the request to the server.

[0235] 3. At the same time, the user looks at photos of the cafe and reads reviews, and the device sends the user's facial expressions and voice to the emotion engine.

[0236] 4. The emotion engine analyzes the user's emotions from their facial expressions and voice, and stores the emotion data in a database.

[0237] 5. The server collects price information and rating data related to the cafe from online stores, review sites, map services, etc. and stores it in a database.

[0238] 6. The server performs data cleaning to remove outliers and unreliable data.

[0239] 7. The server runs a value calculation algorithm and calculates the cafe's value by integrating the average, median, and standard deviation of the prices, review rating points, and sentiment data.

[0240] 8. The server returns the calculated value information to the terminal.

[0241] 9. The terminal displays the received value information to the user, who then decides whether to visit the cafe based on that information and their own feelings.

[0242] In such an embodiment, the system of the present invention can provide users with highly reliable and fair value information, and by incorporating emotional elements, can efficiently provide more personalized information.

[0243] The processing flow will be explained below.

[0244] ---

[0245] Step 1:

[0246] A server collects data about products, services, or location information from multiple data sources via the Internet, specifically, using APIs of online stores to obtain price information and reviews, and APIs of map services to obtain location information and user ratings.

[0247] Step 2:

[0248] The server stores the collected data in a central database, including pricing information, reviews, and location information.

[0249] Step 3:

[0250] The server performs data cleaning to remove outliers and fraudulent data from the stored data, filtering out price anomalies and unreliable reviews.

[0251] Step 4:

[0252] The terminal receives the user's information request and sends the request to the server. For example, the user might type, "I want to know the value of a particular cafe," and the terminal sends the information to the server.

[0253] Step 5:

[0254] The device captures the user's facial expressions, voice, or entered text and sends that information to the emotion engine, using a camera, microphone, or text input.

[0255] Step 6:

[0256] The emotion engine analyzes the user's facial expressions and voice / text data to recognize the user's emotions. For example, if the user is smiling, it will determine that the user is feeling "joy" and generate emotion data.

[0257] Step 7:

[0258] The emotion engine stores the recognized emotion data in a central database, which is then used in the value calculation algorithm.

[0259] Step 8:

[0260] The server runs a value calculation algorithm based on the stored cleaning data and sentiment data, integrating the average, median, and standard deviation of price information, review evaluation points, and sentiment data to calculate the overall value.

[0261] Step 9:

[0262] The server then returns the calculated value information to the device, including average prices, review ratings, rankings, and sentiment-based recommendations.

[0263] Step 10:

[0264] The device displays the received value information to the user. For example, it may display information such as, "This cafe has an average rating of 4.5 / 5, a price range of ¥800 - ¥1200, and user emotional data indicates a very high level of satisfaction."

[0265] Step 11:

[0266] The user makes a decision about purchasing or using a product or service based on the displayed value information and emotional data. For example, they might decide, "This cafe has high ratings and many positive emotional reviews, so it's worth visiting."

[0267] In this way, by having the server, terminal, and emotion engine work in cooperation, the system of the present invention can provide users with highly reliable and fair value information, and can also efficiently provide personalized information that takes emotional elements into account.

[0268] Example 2

[0269] 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."

[0270] Conventional systems cannot take user emotions into account when calculating statistical values ​​based on information obtained from various data sources, making it difficult to provide personalized value information for individual users. Furthermore, inaccurate or invalid data can significantly affect value calculations, reducing reliability. Therefore, there is a need for a method to provide accurate and reliable value information that incorporates user emotions.

[0271] 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.

[0272] In this invention, the server includes means for collecting data on products, services, or location information from various information sources, means for storing the collected data in a database and performing data cleaning and preprocessing, means for acquiring emotional data from a user's facial expressions, voice, or text, means for analyzing the collected emotional data and recognizing emotions, means for executing a statistical value calculation algorithm based on the cleaned data and emotional data, and means for receiving information requests from users and returning value information, thereby enabling the provision of accurate and personalized value information that takes user emotions into consideration.

[0273] "Diverse sources" refers to multiple types of data providers accessible via the Internet, such as online stores, review sites, and map services.

[0274] "Product, Service, or Location Information" means information about goods, services offered, and particular geographic locations that may be of interest to a user.

[0275] "Data collection means" refers to the combination of software and hardware used to obtain the required data from various sources via the Internet.

[0276] A "database" is a structured data storage system for storing, retrieving, and manipulating collected data.

[0277] "Means for performing data cleaning" refers to the process of removing outliers and incorrect data from collected data to improve the integrity and reliability of the data.

[0278] "Pre-processing means" refers to a series of processes that prepare the collected data in a format that can be used by the value calculation algorithm.

[0279] "Means for acquiring emotional data" refers to devices such as cameras, microphones, and text input devices for collecting the user's facial expressions, voice, or text data, as well as software for controlling them.

[0280] "Means for analyzing emotional data" refers to a machine learning model and its execution environment for processing collected emotional data and recognizing user emotions.

[0281] A "value calculation algorithm" is a set of calculation methods that calculates statistical values ​​based on collected data and analyzed emotional data.

[0282] "Means for receiving information requests" refers to a combination of software and hardware for receiving requests for information from users.

[0283] The "means for returning value information" refers to a combination of software and hardware for transmitting the calculated value information to the user's terminal and displaying it.

[0284] This invention combines a system that calculates the fair and equitable value of products, services, or location data obtained by users from various sources with an emotion engine that recognizes and analyzes user emotions. The system is composed of the following components: a server, a terminal, a user, and an emotion engine.

[0285] Server Configuration

[0286] The server collects data about products, services, or location information from various data sources via the Internet. Specifically, the server collects data from online stores, review sites, map services, etc., and stores it in a database. It also includes a process for performing data cleaning to remove outliers and fraudulent data. The data stored in the database is then used to run value calculation algorithms based on statistical indicators such as the average, median, and standard deviation of prices, and review rating points, using data analysis programming languages ​​such as Python and R.

[0287] Device configuration

[0288] The terminal is responsible for receiving information requests and emotional information from the user. The terminal is a device such as a smartphone or tablet that captures the user's facial expressions and voice through a camera and microphone and sends the user's request to the server. It also has the function of displaying the value information returned by the server. For example, if a user inputs a request into the terminal such as "Please tell me the current rating and average price of XX cafe," the request is sent to the server.

[0289] User Roles

[0290] When a user wants to know the value of a product, service, or location information, they use their device to make an information request. The user expresses their emotions through facial expressions, voice, or text, and the device sends the information to the emotion engine for emotional analysis. The emotional data collected in this way is sent to the server and reflected in the value calculation algorithm.

[0291] Emotion engine configuration

[0292] The emotion engine is responsible for recognizing emotions from the user's facial expressions, voice, or text and storing them in a database. The emotion engine uses a machine learning model (e.g., a generative AI model) to classify the user's emotions into categories such as positive, negative, or surprise. The server then feeds this emotion data into a value calculation algorithm to provide personalized value information corresponding to the user's emotions.

[0293] Specific examples

[0294] If a user wants to know the value of a certain cafe, the specific process is as follows:

[0295] 1. The user uses their smartphone to input a request to find out the value of a certain cafe. Example: "I want to know the rating and current average price of a certain cafe."

[0296] 2. The device sends the request to the server.

[0297] 3. At the same time, the user looks at photos of the cafe and reads reviews, and the device sends the user's facial expressions and voice to the emotion engine.

[0298] 4. The emotion engine analyzes the user's emotions from their facial expressions and voice, and stores the emotion data in a database.

[0299] 5. The server collects price information and rating data related to the cafe from online stores, review sites, map services, etc. and stores it in a database.

[0300] 6. The server performs data cleaning to remove outliers and unreliable data.

[0301] 7. The server runs a value calculation algorithm and calculates the cafe's value by integrating the average, median, and standard deviation of the prices, review rating points, and sentiment data.

[0302] 8. The server returns the calculated value information to the terminal.

[0303] 9. The terminal displays the received value information to the user, who then decides whether to visit the cafe based on that information and their own feelings.

[0304] This concludes the description of the embodiment of the present invention. This system provides users with highly reliable and fair value information, and by incorporating emotional elements, it efficiently provides more personalized information.

[0305] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0306] Processing step details

[0307] Step 1: Data collection

[0308] The server collects data about products, services, or location information from various data sources (e.g., online stores, review sites, map services) over the Internet.

[0309] Input: Your server configured API endpoint or web scraping script.

[0310] Processing: Sending API requests or scraping data from web pages.

[0311] Output: The retrieved data (e.g., price information, review ratings, location information).

[0312] Specific operation: The server periodically accesses each data source, collects information, and stores it in a database.

[0313] Step 2: Data storage and preprocessing

[0314] The server stores the collected data in a database and performs data cleaning to remove outliers and invalid data.

[0315] Input: The data collected in Step 1.

[0316] Processing: Inserting data into the database, checking data integrity and removing outliers using SQL queries and ETL processes.

[0317] Output: A clean and reliable dataset.

[0318] Specific operation: The server automates data preprocessing using an ETL tool (e.g., Apache NiFi, Talend).

[0319] Step 3: Collecting emotion data

[0320] The terminal acquires emotion data through the user's facial expressions, voice, or text, and transmits it to the emotion engine.

[0321] Input: User facial expression, voice, and text data.

[0322] Processing: Data capture from cameras and microphones and real-time processing of that data.

[0323] Output: Sentiment data for analysis.

[0324] Specific operation: The device captures the user's emotions using sensor devices (camera, microphone) equipped on the device and transmits the data via Wi-Fi or Bluetooth.

[0325] Step 4: Sentiment analysis

[0326] The emotion engine analyzes collected facial, voice, or text data to recognize the user's emotions.

[0327] Input: The emotion data collected in step 3.

[0328] Processing: Sentiment analysis using machine learning models (e.g., generative AI models).

[0329] Output: User's emotion category (e.g. positive, negative, surprised).

[0330] How it works: The emotion engine uses machine learning libraries (e.g., TensorFlow, PyTorch) to perform real-time analysis of data.

[0331] Step 5: Value calculation algorithm

[0332] The server runs a value calculation algorithm based on the cleaned data and emotion data.

[0333] Input: The clean dataset (Step 2) and the parsed sentiment data (Step 4).

[0334] Processing: Calculation and synthesis of statistical indicators using data analysis tools.

[0335] Output: Final value information (e.g. price mean, median, standard deviation, review rating points).

[0336] Specific operation: The server uses data analysis tools such as Pandas, NumPy, and Scikit-learn to calculate value based on the most recent data.

[0337] Step 6: User Request Processing

[0338] The terminal receives a request from the user and transmits the request and the user's emotion data to the server.

[0339] Input: User request (e.g., "I want to know the rating and current average price of XX Cafe").

[0340] Processing: Formatting and sending request information.

[0341] Output: Request sent to the server.

[0342] Specific operation: The device enters a request into a form and sends it to the server via an HTTP request or WebSocket.

[0343] Step 7: Obtaining and returning value information

[0344] The server receives the request, retrieves value information for the requested product, service, or location information from a database, and returns it to the terminal.

[0345] Input: User requests and data stored in the server.

[0346] Processing: Data extraction using SQL queries and data formatting.

[0347] Output: Value information data in JSON format.

[0348] Specific operation: The server extracts the necessary data using an SQL query, converts it into JSON format, and sends it to the terminal.

[0349] Step 8: Viewing Value Information

[0350] The terminal displays the value information received from the server to the user.

[0351] Input: Value information returned by the server.

[0352] Processing: Formatting and displaying value information.

[0353] Output: Visually display data to the user.

[0354] Specific operation: The terminal formats and displays the received data on the application screen, displaying it in graphs and text so that it is easy for the user to understand.

[0355] The above is the specific processing flow of this system.

[0356] (Application example 2)

[0357] 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."

[0358] Conventional value calculation systems calculate value solely based on price and review ratings, without taking into account the user's subjective feelings or purchasing intent. This makes it difficult to provide users with optimal information for their actual purchasing experience. Furthermore, users have few clues to determine whether the value information matches their own feelings and preferences. To solve this problem, a system is needed that integrates user emotional data and provides more personalized value information.

[0359] 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.

[0360] In this invention, the server includes means for collecting data on products, services, or location information from various data sources, means for storing the collected data in a database and performing preprocessing, means for executing an algorithm for calculating statistical value based on multiple indicators, means for receiving information requests from users and returning value information, means for acquiring emotional data from the user's facial expressions or voice using a camera function, means for adjusting parameters in the value calculation algorithm based on the acquired emotional data, and means for integrating the emotional data and the value information and displaying it to the user. This makes it possible to provide more personalized value information in real time that takes into account the user's subjective emotions.

[0361] "Data Source" means an information source on the Internet that provides product, service, or location data in a variety of formats.

[0362] A "database" is a structured information storage system for storing and managing collected data.

[0363] "Preprocessing" refers to processes such as data cleaning, filtering, and normalization that are carried out to improve the quality of collected data.

[0364] An "algorithm" is a series of calculation procedures for calculating statistical value based on multiple indicators.

[0365] An "information request" is a user's request to the system for value information about a product, service, or location.

[0366] "Value information" is information provided to users based on collected data and calculated statistical values.

[0367] "Camera function" refers to the function of a device to capture images or video.

[0368] "Emotion data" is information about emotions acquired from the user's facial expressions and voice and analyzed by the emotion engine.

[0369] A "parameter" is a variable used in calculations or adjustments in a value calculation algorithm.

[0370] An "emotion engine" is software or hardware that recognizes emotions from a user's facial expressions and voice and analyzes them as data.

[0371] An embodiment of the present invention is a system for enhancing the shopping experience, particularly in brick-and-mortar stores, by allowing users to scan products with their smartphones and collect real-time emotional data to provide personalized value information.

[0372] Program processing

[0373] Server Processing

[0374] The server collects data about products, services, or locations from various data sources, including online stores, review sites, and map services. The collected data is stored in a database and cleaned to remove outliers and invalid data. The server then runs an algorithm to calculate statistical value based on multiple indicators (such as the average price, median price, standard deviation, and review rating points). It also adjusts the parameters of the value calculation algorithm based on user sentiment data, which is reflected in the value information.

[0375] Terminal handling

[0376] When a user uses their smartphone to scan a product, a request for information about that product is sent to the server. At the same time, the smartphone's camera captures the user's facial expressions and voice, and sends the emotional data to the emotion engine. This emotional data is analyzed in real time, and the results are sent to the server. The value information returned from the server is displayed on the device, and the user makes a purchasing decision based on that information.

[0377] User Action

[0378] Users scan products in stores using their smartphones. This scan acquires product price and rating information, while the camera captures the user's facial expressions and voice. This allows the user's emotional data to be collected in real time and analyzed by the emotion engine. The analyzed emotional data is sent to a server and presented to the user as integrated value information.

[0379] Hardware and software used

[0380] Smartphone: Uses camera and network communication functions to capture the user's facial expressions and transmit emotional data.

[0381] Server: Collects data from various data sources, stores it in a database, cleans the data, and executes value calculation algorithms.

[0382] Database: Stores and manages collected data and emotion data.

[0383] Emotion Engine: Uses OpenCV and TensorFlow / Keras to recognize and analyze emotions from the user's facial expressions and voice.

[0384] Specific examples

[0385] For example, if a user scans a particular cafe product in a store, the following steps occur:

[0386] 1. A user uses a smartphone to scan a product in a cafe, and the smartphone camera captures the user's facial expressions and voice.

[0387] 2. The smartphone sends the captured emotion data to the emotion engine at the same time as requesting product information.

[0388] 3. The emotion engine analyzes the emotion data and sends the results to the server.

[0389] 4. The server retrieves product data from the database, performs data cleaning, and runs a value calculation algorithm based on the analyzed sentiment data to calculate the final value information.

[0390] 5. The terminal displays the value information sent from the server to the user, who then decides whether to purchase the cafe product based on this information.

[0391] Prompt Sentence Examples

[0392] Below are some example prompts to use in the emotion engine as input to the generative AI model.

[0393] text

[0394] Facial image: Image data path

[0395] Expected emotions: happy, anxious, sad, surprised, angry, neutral, disgust

[0396] This specific structure enables the system of the invention to provide more personalized value information that takes into account the user's emotions.

[0397] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0398] Step 1:

[0399] A user uses a smartphone to scan a product in a store. The input data is the scanned barcode or QR code of the product, and the smartphone camera captures the user's facial expressions and voice. The output is a product information request and captured emotion data.

[0400] Step 2:

[0401] The terminal sends a product information request and captured emotion data to the server. The input data are the product scan results and the user's emotion data, which are sent to the server. The output is the request and emotion data received by the server.

[0402] Step 3:

[0403] The server collects data about products, services, or locations from various data sources. The input data is information collected from online stores, review sites, map services, etc., and the output is the collected product data.

[0404] Step 4:

[0405] The server stores the collected data in a database and performs preprocessing. The input data is the collected product data, and the output is the data after preprocessing. This preprocessing includes data cleaning (removal of outliers and invalid data).

[0406] Step 5:

[0407] The server uses an emotion engine to analyze emotion data from the user's facial expressions and voice. The input data is the user's facial image and voice data, and the output is the type and intensity of the analyzed emotion. This analysis uses a facial recognition model and an emotion analysis model.

[0408] Step 6:

[0409] The server runs an algorithm that uses multiple indicators to calculate statistical value based on the collected data and analyzed sentiment data. The input data is preprocessed product data and analyzed sentiment data, and the output is statistical value information. The algorithm includes the average, median, and standard deviation of price, as well as review rating points.

[0410] Step 7:

[0411] The server returns the calculated value information to the terminal. The input data is statistical value information, and the output is value information received by the user's terminal.

[0412] Step 8:

[0413] The terminal displays the received value information to the user. The input data is the value information sent from the server, and the output is information that the user can visually confirm. Based on this, the user can decide whether or not to purchase the product.

[0414] These steps enable the system of the present invention to provide more personalized value information in real time, taking into account the user's emotions.

[0415] 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.

[0416] 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.

[0417] 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.

[0418] [Second embodiment]

[0419] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0420] 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.

[0421] 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).

[0422] 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.

[0423] 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.

[0424] 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).

[0425] 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.

[0426] 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.

[0427] 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.

[0428] 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.

[0429] In the smart glasses 214, 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.

[0430] 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."

[0431] ---

[0432] The present invention relates to a system that calculates the fair and equitable value of products, services, or location information based on data about the products, services, or location information that users obtain from various sources. This system is composed of components including a server, a terminal, and a user. A specific embodiment is described below.

[0433] System Overview

[0434] server

[0435] The server collects data related to products, services, or location information from various data sources via the Internet. The collected data is stored in a database, where data cleaning is performed to remove outliers and invalid data. The server also runs an algorithm to calculate statistical value using multiple indicators based on the collected data.

[0436] Terminal

[0437] The terminal receives information requests from users and sends them to the server. It has the function of displaying the value information returned from the server. Users can easily check fair and impartial value information through the terminal.

[0438] User

[0439] Users want to know the value of a product, service, or location information, so they use their device to make an information request and use the returned value information to make a purchase decision or use decision for the product or service.

[0440] Program processing overview

[0441] 1. Data Collection

[0442] The server uses various APIs and web scraping tools to gather the required information from data sources, such as price information from online stores, ratings from review sites, and location information from map services.

[0443] 2. Data storage and preprocessing

[0444] The server stores the collected data in a database, where data cleaning is performed to remove invalid data and outliers and improve the quality of the data.

[0445] 3. Value Calculation Algorithm

[0446] The server runs an algorithm that calculates the mean, median, and standard deviation of the price information and aggregates the review rating points to calculate the value of the product, service, or location information in question.

[0447] 4. User Request Processing

[0448] The device receives a request from the user and sends the information to the server. For example, a user wants to check the value of a "specific product" on their smartphone, and the device sends the request to the server.

[0449] 5. Presentation of value information

[0450] The server retrieves value information from the database based on the request and returns it to the terminal. The terminal displays the value information received from the server to the user. For example, information such as the average price, review rating, and ranking of the product is displayed.

[0451] Specific examples

[0452] For example, if a user wants to know the value of a certain electronic device,

[0453] 1. A user uses a smartphone to input a request to find out the value of an electronic device into the device.

[0454] 2. The device sends the request to the server.

[0455] 3. The server collects price information and evaluation data related to electronic devices from online stores, review sites, etc. and stores it in a database.

[0456] 4. The server performs data cleaning to remove outliers and unreliable data.

[0457] 5. The server runs a value calculation algorithm to calculate the value of the electronic device by combining the average, median, standard deviation, and review rating points of the price.

[0458] 6. The server returns the calculated value information to the terminal.

[0459] 7. The terminal displays the received value information to the user, who then decides whether or not to make a purchase based on that information.

[0460] By implementing such an embodiment, the system of the present invention allows users to efficiently obtain highly reliable value information from a vast number of information sources and make fair and impartial judgments.

[0461] The processing flow will be explained below.

[0462] ---

[0463] Step 1:

[0464] A server collects data about products, services, or locations from multiple data sources over the Internet, for example, using an online store's API to obtain pricing information and reviews, and a map service's API to obtain location information and user ratings.

[0465] Step 2:

[0466] The server stores the collected data in a database, where it remains raw and is saved for further processing.

[0467] Step 3:

[0468] The server performs data cleaning to remove outliers and fraudulent data from the stored data, for example filtering out abnormally high prices or impossible review ratings.

[0469] Step 4:

[0470] The server runs a value calculation algorithm based on the cleaned data, which calculates the average, median, and standard deviation of the price information, and also takes into account review evaluation points to calculate the overall value.

[0471] Step 5:

[0472] The terminal receives a request for information from a user and transmits the request to a server. For example, a user uses the terminal to input, "I want to know the value of a particular electronic device."

[0473] Step 6:

[0474] The server receives the request from the terminal and retrieves value information about the requested product or service from the database. The retrieved information includes the statistical value calculated in the previous step.

[0475] Step 7:

[0476] The server returns value information to the terminal, including the average, median, and standard deviation of detailed prices, review evaluation points, and so on.

[0477] Step 8:

[0478] The terminal displays the value information received from the server to the user, allowing the user to easily confirm that the value information is fair and impartial.

[0479] Step 9:

[0480] Users make decisions about purchasing or using products or services based on the displayed value information. For example, they might decide, "This electronic device has an average price of 50,000 yen and a review rating of 4.5 / 5, so it's worth buying."

[0481] Through the above steps, the system of the present invention can provide users with highly reliable and fair value information and support efficient decision-making.

[0482] Example 1

[0483] 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."

[0484] Conventional systems face challenges in consistently collecting data on products, services, or location information from a variety of sources and assessing its value, making it difficult for users to make accurate and fair judgments. In particular, they face challenges in ensuring the reliability and quality of data, and in lacking algorithms for calculating value using appropriate indicators based on collected data. Furthermore, they lack the functionality to quickly and accurately provide value information in response to user requests.

[0485] 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.

[0486] In this invention, the server includes means for collecting information on products, services, or location information from various information sources, means for storing the collected information in a database and performing preprocessing, means for executing an algorithm for calculating statistical value based on multiple indicators, means for receiving information requests from users and returning value information, and means for displaying the value information on user terminals, thereby enabling users to quickly obtain highly reliable value information and make accurate and fair decisions.

[0487] "Diverse sources" refers to multiple data providers that provide data about products, services, or locations.

[0488] "Product" refers to an individual or set of goods or consumer goods sold in a particular market.

[0489] "Service" refers to a transaction related to the provision of a particular activity or functionality.

[0490] "Location information" is data that indicates a geographical location, and includes coordinates and address information of a specific location.

[0491] "Means of collecting information" refers to a system configuration that automatically obtains data using APIs or web scraping tools.

[0492] "Database" means an electronic storage system that organizes and stores collected information so that it can be efficiently retrieved and used at a later time.

[0493] "Preprocessing means" refers to processing to improve the quality of collected data using methods such as data cleaning and data normalization.

[0494] "Multiple metrics" refers to different metrics or calculation methods for assessing and analyzing data characteristics and trends. Examples include mean, median, standard deviation, etc.

[0495] "Statistical value calculation algorithm" refers to a mathematical method or computational model that analyzes collected data and provides an objective value assessment.

[0496] "Means for receiving an information request and returning value information" refers to the process of searching a database in response to an inquiry from a user and returning the relevant information to the user.

[0497] "User Device" means an electronic device used by a User to enter information requests and view returned information. Examples include smartphones, tablets, and personal computers.

[0498] The present invention relates to a system that calculates the fair and equitable value of products, services, or location information based on data about the products, services, or locations that users obtain from various sources. This system consists of three components: a server, a terminal, and a user.

[0499] System Overview

[0500] server

[0501] The server collects data from various sources via the internet. Specific software used for this includes APIs and web scraping tools. For example, an API is used to obtain pricing information from online stores, and a web scraping tool is used to collect ratings from review sites. The collected data is stored in a database such as MySQL. The server then performs data cleaning to remove outliers and invalid data and improve data quality. Furthermore, the server calculates the mean, median, and standard deviation of the price information and runs algorithms that combine review rating points to calculate the value of the product, service, and location information.

[0502] Terminal

[0503] The terminal has the function of receiving information requests from users and sending those requests to a server. Specific examples of terminals include smartphones, tablets, and PCs. When a user inputs a request through the terminal, the request is sent to the server as an HTTP request. The value information returned from the server is displayed to the user by the terminal. The displayed content is diverse and includes, for example, "average product price," "review rating," and "ranking."

[0504] User

[0505] When a user wants to know the value of a particular product, service, or location, they use their device to request that information. An example of a request might be, "What is the market value of this electronic device?" They send a request and use the returned value information to make a purchasing decision on the product or service.

[0506] Specific examples

[0507] For example, if a user wants to know the value of an iPhone 13,

[0508] 1. A user uses their smartphone to enter a request such as, "I want to know the value of my iPhone 13."

[0509] 2. The device sends the request to the server. The request format will be something like "Product name: iPhone 13."

[0510] 3. The server collects price information and evaluation data related to the iPhone 13 from online stores (e.g., Amazon and Rakuten) and review sites (e.g., Kakaku.com) and stores it in a database.

[0511] 4. The server performs data cleaning to remove unreliable data and outliers.

[0512] 5. The server runs a value calculation algorithm and calculates the value of the iPhone 13 by combining the average price, median price, standard deviation, and review rating points. For example, the result is "average price is 100,000 yen, and review rating is 4.8 / 5."

[0513] 6. The server returns the calculated value information to the terminal.

[0514] 7. The terminal displays the received value information to the user, who then decides whether or not to make a purchase based on that information.

[0515] This system allows users to efficiently obtain highly reliable value information and make fair and impartial decisions.

[0516] Prompt Sentence Examples

[0517] "I'd like to know the market value of this electronic device. I'd like the market value calculated based on online store pricing, reviews, and related data."

[0518] This system's series of processes allows users to quickly obtain highly reliable value information from a vast number of information sources, enabling them to make more accurate decisions regarding purchases and usage.

[0519] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0520] Processing Steps

[0521] Step 1:

[0522] A server collects data about products, services, or locations from various sources. Specific tools used for collection include APIs and web scraping tools. For example, an online store's API can be called to obtain price information, and a web scraping tool can be used to collect rating data from review sites. The source's URL and API key are used as input, and the collected raw data is obtained as output.

[0523] Step 2:

[0524] The server stores the collected data in a database. For this, a database management system such as MySQL or PostgreSQL is used. Before storing it in the database, the data structure is unified and duplicate data is removed. Raw data is given as input, and cleaned data is stored in the database as output.

[0525] Step 3:

[0526] The server performs data cleaning on the stored data. This includes removing invalid data and outliers, and filling in missing data. Specifically, if the price of a certain product is extremely high or low, the data is removed. Missing values ​​are also filled in with the mean or median. The data stored in the database is given as input, and cleaned data is obtained as output.

[0527] Step 4:

[0528] The server runs an algorithm that calculates statistical value based on multiple indicators. It calculates the average, median, and standard deviation of price information and integrates review evaluation points. For example, it calculates the overall value by taking the average price information of a specific product and weighting it with the evaluation points from review sites. Cleaned data is given as input, and value information is obtained as output.

[0529] Step 5:

[0530] A user uses a device to input a request to find out the value of a particular product or service. For example, they might type "Find out the value of an iPhone 13" on their smartphone. The user's request is given as input, and the request is sent from the device to the server as output.

[0531] Step 6:

[0532] The server receives a request from the terminal and searches the database for value information on the corresponding product or service. The user request is given as input, and the corresponding value information is obtained from the server as output.

[0533] Step 7:

[0534] The server formats the acquired value information and returns it to the terminal. For example, detailed value information including the average price, median price, standard deviation price, review evaluation points, etc. is formatted. The acquired value information is given as input, and the formatted value information is returned to the terminal as output.

[0535] Step 8:

[0536] The terminal displays the received value information to the user. For example, for a specific electronic device, information such as "average price is 100,000 yen, and review rating is 4.8 / 5" is displayed. The value information returned from the server is given as input, and the specific value information is displayed on the user's screen as output.

[0537] Through this series of processing steps, the user can efficiently obtain highly reliable value information and make a fair and impartial decision.

[0538] (Application example 1)

[0539] 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."

[0540] Today's users face difficulties in accurately and quickly grasping the value of products and services obtained from a variety of information sources. It also takes a great deal of time and effort to find reliable data from the vast amount of information and to make a fair and impartial value assessment. Furthermore, when selecting a product or service, users are required to comprehensively evaluate multiple indicators, such as price and reviews, but this is not easy to achieve. A system that solves these problems is needed.

[0541] 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.

[0542] In this invention, the server includes means for collecting data on products, services, or location information from various data sources, means for storing the collected data in a database and performing preprocessing, means for executing an algorithm for calculating statistical value based on multiple indicators, means for receiving information requests on products or services from a user's terminal, generating value information based on the request, and returning the value information to the user's terminal, and means for triggering data collection using the barcode or name of the product or service. This enables users to quickly and efficiently perform reliable, fair, and impartial value assessments based on data obtained from various information sources.

[0543] - "Diverse data sources" refers to the means of obtaining data from various information providers on the Internet, APIs, web scraping tools, etc.

[0544] "Products" refers to physical and digital goods sold in the Marketplace.

[0545] "Services" include any activities, functions, or skills provided for a fee or free of charge.

[0546] "Location Information" refers to data relating to a geographic location or position.

[0547] A "database" is a system for efficiently storing, managing, and retrieving collected data.

[0548] "Preprocessing" refers to data quality improvement measures including data cleaning, normalization, and conversion to another format.

[0549] "Statistical value" refers to the overall evaluation of the data calculated based on the mean, median, standard deviation, and other statistical indicators.

[0550] An "algorithm" refers to a set of procedures or formulas for performing a particular calculation or operation.

[0551] "User terminal" includes devices used by users, such as smartphones, tablets, and personal computers.

[0552] An "information request" refers to an operation in which a user requests specific information through a terminal.

[0553] "Value information" refers to the evaluation results of products, services, or location information analyzed based on collected data.

[0554] A "barcode" is a visual representation of a unique sequence of numbers and / or letters used to identify a product.

[0555] "Name" means a unique word or phrase used to identify a particular product or service.

[0556] The present invention relates to a system that calculates the fair and equitable value of products, services, or location information based on data about the products, services, or location information that a user obtains from various information sources. The system is composed of components including a server, a terminal, and a user. Specific embodiments are described below.

[0557] System Overview

[0558] server

[0559] The server collects data about products, services, or location information from various data sources via the Internet. Data sources include online stores, review sites, and map services. The collected data is stored in a database, and data cleaning is performed to remove outliers and invalid data. The server also runs an algorithm that calculates statistical value using multiple indicators based on the collected data. This algorithm calculates the average, median, and standard deviation of price information and calculates the value of the product or service by integrating review evaluation points.

[0560] Terminal

[0561] The terminal receives an information request from the user and sends the request to the server. The request includes the name of the product or service and a barcode. It has the function of displaying the value information returned from the server. Specifically, a mobile device such as a smartphone or tablet is used as the terminal. The user can easily check fair and impartial value information through the terminal.

[0562] User

[0563] A user wants to know the value of a product, service, or location information, so they use their device to make an information request. Based on the returned value information, they can make a decision to purchase or use the product or service. For example, if a user wants to know the value of a certain electronic device, they can use their smartphone to enter the name or barcode of the electronic device and obtain the value information from the server.

[0564] Program processing

[0565] This program mainly handles the following processes: data collection, data cleaning, value calculation, and user request processing.

[0566] Hardware and software used

[0567] Hardware: User devices such as smartphones, tablets, and PCs

[0568] Software: Programming languages ​​and libraries such as Python, requests, statistics, numpy, etc. APIs used include online store APIs and review site APIs.

[0569] Specific examples

[0570] For example, if a user wants to know the value of an "iPhone 13," they open their smartphone and enter "iPhone 13" as the product name. The device sends this request to the server. The server collects price information and review ratings from online stores and review sites and stores them in a database. It performs data cleaning to remove outliers and invalid data, and calculates the value by combining the mean, median, standard deviation, and review rating points of the price information. The server sends the calculated value information back to the device, and the device displays the received value information to the user.

[0571] Prompt Sentence Examples

[0572] The user can use prompts such as:

[0573] "What is the value of the iPhone 13? I'd like to know a fair and impartial value based on price information and review ratings."

[0574] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0575] Step 1: Data collection

[0576] Based on the product or service name or barcode specified by the user, the server collects relevant data using online store APIs or review site APIs. Information obtained from data sources includes price information, review ratings, location information, etc. The input of this step is the user request, and the output is the collected raw data.

[0577] Step 2: Data storage and preprocessing

[0578] The server stores the collected raw data in a database and performs preprocessing, which includes data cleaning to remove outliers and invalid data. The input of this step is the collected raw data, and the output is a clean dataset.

[0579] Step 3: Data cleaning

[0580] The server runs a data cleaning process on the stored data to remove outliers and incorrect data, which may include, for example, removing unusually high or low prices. The input to this step is the stored raw data, and the output is the cleaned data.

[0581] Step 4: Value calculation

[0582] The server runs an algorithm to calculate statistical value based on the cleaned data. Specifically, it calculates the mean, median, and standard deviation of the price information and integrates the review rating points. The input of this step is the cleaned data, and the output is the calculated value information.

[0583] Step 5: User Request Processing

[0584] The terminal receives an information request from the user and sends that information to the server. The user inputs a product name or barcode, and the terminal sends that data to the server as a request. The input of this step is the user's request, and the output is the request sent to the server.

[0585] Step 6: Retrieving data based on the request

[0586] The server searches for and acquires the corresponding license information from the database based on the request received from the terminal. The input to this step is the request from the terminal, and the output is the acquired license information.

[0587] Step 7: Return and display of value information

[0588] The server returns the acquired value information to the terminal, which then displays it to the user. This allows the user to check information such as the average price, median, standard deviation, and review rating of the product or service. The input to this step is the value information from the server, and the output is the information displayed to the user.

[0589] 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.

[0590] ---

[0591] This invention combines a system that calculates the fair and equitable value of products, services, or location data obtained by users from various sources with an emotion engine that recognizes and analyzes user emotions. This system is composed of the following components: a server, a terminal, a user, and the emotion engine. A specific embodiment is shown below.

[0592] System Overview

[0593] server

[0594] The server collects data related to products, services, or location information from various data sources via the Internet. The collected data is stored in a database, and data cleaning is performed to remove outliers and invalid data. The server then runs an algorithm to calculate statistical value using multiple indicators based on the collected data and sentiment data.

[0595] Terminal

[0596] The device receives information requests and emotion information from the user and sends the requests to the server. It also has the function of displaying the value information returned from the server. The user can easily check the fair and just value information through the device.

[0597] User

[0598] When a user wants to know the value of a product, service, or location, they use their device to make an information request and express their emotions through facial expressions, voice, or text, which are then analyzed by the emotion engine.

[0599] Emotion Engine

[0600] The emotion engine recognizes emotions from the user's facial expressions, voice, or text and stores them in a database. The server then applies this emotion data to a value calculation algorithm to provide personalized value information corresponding to the user's emotions.

[0601] Program processing overview

[0602] 1. Data Collection

[0603] The server collects the necessary information from multiple data sources, such as online stores, review sites, and map services, and stores it in a database.

[0604] 2. Data storage and preprocessing

[0605] The server stores the collected data in a database and performs data cleaning to remove outliers and invalid data.

[0606] 3. Collecting Emotional Data

[0607] The terminal acquires data for recognizing emotions through the user's facial expressions, voice, or text, and sends it to the emotion engine.

[0608] 4. Sentiment analysis

[0609] The emotion engine analyzes the collected facial, voice, or text data to recognize the user's emotions, and the recognized emotion data is stored in a database.

[0610] 5. Value Calculation Algorithm

[0611] The server runs a value calculation algorithm based on the cleaned data and sentiment data, and calculates the overall value by integrating the average, median, and standard deviation of the price and review rating points.

[0612] 6. User Request Processing

[0613] The terminal receives a request from the user and transmits the request and the user's emotion data to the server.

[0614] 7. Obtaining and returning value information

[0615] The server receives the request, retrieves value information for the requested product, service, or location information from a database, and returns it to the terminal.

[0616] 8. Display of Value Information

[0617] The terminal displays the value information received from the server to the user, allowing the user to easily confirm that the value information is fair and impartial.

[0618] Specific examples

[0619] For example, if a user wants to know the value of a certain cafe,

[0620] 1. A user uses a smartphone to input a request to find out the value of a cafe.

[0621] 2. The device sends the request to the server.

[0622] 3. At the same time, the user looks at photos of the cafe and reads reviews, and the device sends the user's facial expressions and voice to the emotion engine.

[0623] 4. The emotion engine analyzes the user's emotions from their facial expressions and voice, and stores the emotion data in a database.

[0624] 5. The server collects price information and rating data related to the cafe from online stores, review sites, map services, etc. and stores it in a database.

[0625] 6. The server performs data cleaning to remove outliers and unreliable data.

[0626] 7. The server runs a value calculation algorithm and calculates the cafe's value by integrating the average, median, and standard deviation of the prices, review rating points, and sentiment data.

[0627] 8. The server returns the calculated value information to the terminal.

[0628] 9. The terminal displays the received value information to the user, who then decides whether to visit the cafe based on that information and their own feelings.

[0629] In such an embodiment, the system of the present invention can provide users with highly reliable and fair value information, and by incorporating emotional elements, can efficiently provide more personalized information.

[0630] The processing flow will be explained below.

[0631] ---

[0632] Step 1:

[0633] A server collects data about products, services, or location information from multiple data sources via the Internet, specifically, using APIs of online stores to obtain price information and reviews, and APIs of map services to obtain location information and user ratings.

[0634] Step 2:

[0635] The server stores the collected data in a central database, including pricing information, reviews, and location information.

[0636] Step 3:

[0637] The server performs data cleaning to remove outliers and fraudulent data from the stored data, filtering out price anomalies and unreliable reviews.

[0638] Step 4:

[0639] The terminal receives the user's information request and sends the request to the server. For example, the user might type, "I want to know the value of a particular cafe," and the terminal sends the information to the server.

[0640] Step 5:

[0641] The device captures the user's facial expressions, voice, or entered text and sends that information to the emotion engine, using a camera, microphone, or text input.

[0642] Step 6:

[0643] The emotion engine analyzes the user's facial expressions and voice / text data to recognize the user's emotions. For example, if the user is smiling, it will determine that the user is feeling "joy" and generate emotion data.

[0644] Step 7:

[0645] The emotion engine stores the recognized emotion data in a central database, which is then used in the value calculation algorithm.

[0646] Step 8:

[0647] The server runs a value calculation algorithm based on the stored cleaning data and sentiment data, integrating the average, median, and standard deviation of price information, review evaluation points, and sentiment data to calculate the overall value.

[0648] Step 9:

[0649] The server then returns the calculated value information to the device, including average prices, review ratings, rankings, and sentiment-based recommendations.

[0650] Step 10:

[0651] The device displays the received value information to the user. For example, it may display information such as, "This cafe has an average rating of 4.5 / 5, a price range of ¥800 - ¥1200, and user emotional data indicates a very high level of satisfaction."

[0652] Step 11:

[0653] The user makes a decision about purchasing or using a product or service based on the displayed value information and emotional data. For example, they might decide, "This cafe has high ratings and many positive emotional reviews, so it's worth visiting."

[0654] In this way, by having the server, terminal, and emotion engine work in cooperation, the system of the present invention can provide users with highly reliable and fair value information, and can also efficiently provide personalized information that takes emotional elements into account.

[0655] Example 2

[0656] 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."

[0657] Conventional systems cannot take user emotions into account when calculating statistical values ​​based on information obtained from various data sources, making it difficult to provide personalized value information for individual users. Furthermore, inaccurate or invalid data can significantly affect value calculations, reducing reliability. Therefore, there is a need for a method to provide accurate and reliable value information that incorporates user emotions.

[0658] 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.

[0659] In this invention, the server includes means for collecting data on products, services, or location information from various information sources, means for storing the collected data in a database and performing data cleaning and preprocessing, means for acquiring emotional data from a user's facial expressions, voice, or text, means for analyzing the collected emotional data and recognizing emotions, means for executing a statistical value calculation algorithm based on the cleaned data and emotional data, and means for receiving information requests from users and returning value information, thereby enabling the provision of accurate and personalized value information that takes user emotions into consideration.

[0660] "Diverse sources" refers to multiple types of data providers accessible via the Internet, such as online stores, review sites, and map services.

[0661] "Product, Service, or Location Information" means information about goods, services offered, and particular geographic locations that may be of interest to a user.

[0662] "Data collection means" refers to the combination of software and hardware used to obtain the required data from various sources via the Internet.

[0663] A "database" is a structured data storage system for storing, retrieving, and manipulating collected data.

[0664] "Means for performing data cleaning" refers to the process of removing outliers and incorrect data from collected data to improve the integrity and reliability of the data.

[0665] "Pre-processing means" refers to a series of processes that prepare the collected data in a format that can be used by the value calculation algorithm.

[0666] "Means for acquiring emotional data" refers to devices such as cameras, microphones, and text input devices for collecting the user's facial expressions, voice, or text data, as well as software for controlling them.

[0667] "Means for analyzing emotional data" refers to a machine learning model and its execution environment for processing collected emotional data and recognizing user emotions.

[0668] A "value calculation algorithm" is a set of calculation methods that calculates statistical values ​​based on collected data and analyzed emotional data.

[0669] "Means for receiving information requests" refers to a combination of software and hardware for receiving requests for information from users.

[0670] The "means for returning value information" refers to a combination of software and hardware for transmitting the calculated value information to the user's terminal and displaying it.

[0671] This invention combines a system that calculates the fair and equitable value of products, services, or location data obtained by users from various sources with an emotion engine that recognizes and analyzes user emotions. The system is composed of the following components: a server, a terminal, a user, and an emotion engine.

[0672] Server Configuration

[0673] The server collects data about products, services, or location information from various data sources via the Internet. Specifically, the server collects data from online stores, review sites, map services, etc., and stores it in a database. It also includes a process for performing data cleaning to remove outliers and fraudulent data. The data stored in the database is then used to run value calculation algorithms based on statistical indicators such as the average, median, and standard deviation of prices, and review rating points, using data analysis programming languages ​​such as Python and R.

[0674] Device configuration

[0675] The terminal is responsible for receiving information requests and emotional information from the user. The terminal is a device such as a smartphone or tablet that captures the user's facial expressions and voice through a camera and microphone and sends the user's request to the server. It also has the function of displaying the value information returned by the server. For example, if a user inputs a request into the terminal such as "Please tell me the current rating and average price of XX cafe," the request is sent to the server.

[0676] User Roles

[0677] When a user wants to know the value of a product, service, or location information, they use their device to make an information request. The user expresses their emotions through facial expressions, voice, or text, and the device sends the information to the emotion engine for emotional analysis. The emotional data collected in this way is sent to the server and reflected in the value calculation algorithm.

[0678] Emotion engine configuration

[0679] The emotion engine is responsible for recognizing emotions from the user's facial expressions, voice, or text and storing them in a database. The emotion engine uses a machine learning model (e.g., a generative AI model) to classify the user's emotions into categories such as positive, negative, or surprise. The server then feeds this emotion data into a value calculation algorithm to provide personalized value information corresponding to the user's emotions.

[0680] Specific examples

[0681] If a user wants to know the value of a certain cafe, the specific process is as follows:

[0682] 1. The user uses their smartphone to input a request to find out the value of a certain cafe. Example: "I want to know the rating and current average price of a certain cafe."

[0683] 2. The device sends the request to the server.

[0684] 3. At the same time, the user looks at photos of the cafe and reads reviews, and the device sends the user's facial expressions and voice to the emotion engine.

[0685] 4. The emotion engine analyzes the user's emotions from their facial expressions and voice, and stores the emotion data in a database.

[0686] 5. The server collects price information and rating data related to the cafe from online stores, review sites, map services, etc. and stores it in a database.

[0687] 6. The server performs data cleaning to remove outliers and unreliable data.

[0688] 7. The server runs a value calculation algorithm and calculates the cafe's value by integrating the average, median, and standard deviation of the prices, review rating points, and sentiment data.

[0689] 8. The server returns the calculated value information to the terminal.

[0690] 9. The terminal displays the received value information to the user, who then decides whether to visit the cafe based on that information and their own feelings.

[0691] This concludes the description of the embodiment of the present invention. This system provides users with highly reliable and fair value information, and by incorporating emotional elements, it efficiently provides more personalized information.

[0692] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0693] Processing step details

[0694] Step 1: Data collection

[0695] The server collects data about products, services, or location information from various data sources (e.g., online stores, review sites, map services) over the Internet.

[0696] Input: Your server configured API endpoint or web scraping script.

[0697] Processing: Sending API requests or scraping data from web pages.

[0698] Output: The retrieved data (e.g., price information, review ratings, location information).

[0699] Specific operation: The server periodically accesses each data source, collects information, and stores it in a database.

[0700] Step 2: Data storage and preprocessing

[0701] The server stores the collected data in a database and performs data cleaning to remove outliers and invalid data.

[0702] Input: The data collected in Step 1.

[0703] Processing: Inserting data into the database, checking data integrity and removing outliers using SQL queries and ETL processes.

[0704] Output: A clean and reliable dataset.

[0705] Specific operation: The server automates data preprocessing using an ETL tool (e.g., Apache NiFi, Talend).

[0706] Step 3: Collecting emotion data

[0707] The terminal acquires emotion data through the user's facial expressions, voice, or text, and transmits it to the emotion engine.

[0708] Input: User facial expression, voice, and text data.

[0709] Processing: Data capture from cameras and microphones and real-time processing of that data.

[0710] Output: Sentiment data for analysis.

[0711] Specific operation: The device captures the user's emotions using sensor devices (camera, microphone) equipped on the device and transmits the data via Wi-Fi or Bluetooth.

[0712] Step 4: Sentiment analysis

[0713] The emotion engine analyzes collected facial, voice, or text data to recognize the user's emotions.

[0714] Input: The emotion data collected in step 3.

[0715] Processing: Sentiment analysis using machine learning models (e.g., generative AI models).

[0716] Output: User's emotion category (e.g. positive, negative, surprised).

[0717] How it works: The emotion engine uses machine learning libraries (e.g., TensorFlow, PyTorch) to perform real-time analysis of data.

[0718] Step 5: Value calculation algorithm

[0719] The server runs a value calculation algorithm based on the cleaned data and emotion data.

[0720] Input: The clean dataset (Step 2) and the parsed sentiment data (Step 4).

[0721] Processing: Calculation and synthesis of statistical indicators using data analysis tools.

[0722] Output: Final value information (e.g. price mean, median, standard deviation, review rating points).

[0723] Specific operation: The server uses data analysis tools such as Pandas, NumPy, and Scikit-learn to calculate value based on the most recent data.

[0724] Step 6: User Request Processing

[0725] The terminal receives a request from the user and transmits the request and the user's emotion data to the server.

[0726] Input: User request (e.g., "I want to know the rating and current average price of XX Cafe").

[0727] Processing: Formatting and sending request information.

[0728] Output: Request sent to the server.

[0729] Specific operation: The device enters a request into a form and sends it to the server via an HTTP request or WebSocket.

[0730] Step 7: Obtaining and returning value information

[0731] The server receives the request, retrieves value information for the requested product, service, or location information from a database, and returns it to the terminal.

[0732] Input: User requests and data stored in the server.

[0733] Processing: Data extraction using SQL queries and data formatting.

[0734] Output: Value information data in JSON format.

[0735] Specific operation: The server extracts the necessary data using an SQL query, converts it into JSON format, and sends it to the terminal.

[0736] Step 8: Viewing Value Information

[0737] The terminal displays the value information received from the server to the user.

[0738] Input: Value information returned by the server.

[0739] Processing: Formatting and displaying value information.

[0740] Output: Visually display data to the user.

[0741] Specific operation: The terminal formats and displays the received data on the application screen, displaying it in graphs and text so that it is easy for the user to understand.

[0742] The above is the specific processing flow of this system.

[0743] (Application example 2)

[0744] 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."

[0745] Conventional value calculation systems calculate value solely based on price and review ratings, without taking into account the user's subjective feelings or purchasing intent. This makes it difficult to provide users with optimal information for their actual purchasing experience. Furthermore, users have few clues to determine whether the value information matches their own feelings and preferences. To solve this problem, a system is needed that integrates user emotional data and provides more personalized value information.

[0746] 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.

[0747] In this invention, the server includes means for collecting data on products, services, or location information from various data sources, means for storing the collected data in a database and performing preprocessing, means for executing an algorithm for calculating statistical value based on multiple indicators, means for receiving information requests from users and returning value information, means for acquiring emotional data from the user's facial expressions or voice using a camera function, means for adjusting parameters in the value calculation algorithm based on the acquired emotional data, and means for integrating the emotional data and the value information and displaying it to the user. This makes it possible to provide more personalized value information in real time that takes into account the user's subjective emotions.

[0748] "Data Source" means an information source on the Internet that provides product, service, or location data in a variety of formats.

[0749] A "database" is a structured information storage system for storing and managing collected data.

[0750] "Preprocessing" refers to processes such as data cleaning, filtering, and normalization that are carried out to improve the quality of collected data.

[0751] An "algorithm" is a series of calculation procedures for calculating statistical value based on multiple indicators.

[0752] An "information request" is a user's request to the system for value information about a product, service, or location.

[0753] "Value information" is information provided to users based on collected data and calculated statistical values.

[0754] "Camera function" refers to the function of a device to capture images or video.

[0755] "Emotion data" is information about emotions acquired from the user's facial expressions and voice and analyzed by the emotion engine.

[0756] A "parameter" is a variable used in calculations or adjustments in a value calculation algorithm.

[0757] An "emotion engine" is software or hardware that recognizes emotions from a user's facial expressions and voice and analyzes them as data.

[0758] An embodiment of the present invention is a system for enhancing the shopping experience, particularly in brick-and-mortar stores, by allowing users to scan products with their smartphones and collect real-time emotional data to provide personalized value information.

[0759] Program processing

[0760] Server Processing

[0761] The server collects data about products, services, or locations from various data sources, including online stores, review sites, and map services. The collected data is stored in a database and cleaned to remove outliers and invalid data. The server then runs an algorithm to calculate statistical value based on multiple indicators (such as the average price, median price, standard deviation, and review rating points). It also adjusts the parameters of the value calculation algorithm based on user sentiment data, which is reflected in the value information.

[0762] Terminal handling

[0763] When a user uses their smartphone to scan a product, a request for information about that product is sent to the server. At the same time, the smartphone's camera captures the user's facial expressions and voice, and sends the emotional data to the emotion engine. This emotional data is analyzed in real time, and the results are sent to the server. The value information returned from the server is displayed on the device, and the user makes a purchasing decision based on that information.

[0764] User Action

[0765] Users scan products in stores using their smartphones. This scan acquires product price and rating information, while the camera captures the user's facial expressions and voice. This allows the user's emotional data to be collected in real time and analyzed by the emotion engine. The analyzed emotional data is sent to a server and presented to the user as integrated value information.

[0766] Hardware and software used

[0767] Smartphone: Uses camera and network communication functions to capture the user's facial expressions and transmit emotional data.

[0768] Server: Collects data from various data sources, stores it in a database, cleans the data, and executes value calculation algorithms.

[0769] Database: Stores and manages collected data and emotion data.

[0770] Emotion Engine: Uses OpenCV and TensorFlow / Keras to recognize and analyze emotions from the user's facial expressions and voice.

[0771] Specific examples

[0772] For example, if a user scans a particular cafe product in a store, the following steps occur:

[0773] 1. A user uses a smartphone to scan a product in a cafe, and the smartphone camera captures the user's facial expressions and voice.

[0774] 2. The smartphone sends the captured emotion data to the emotion engine at the same time as requesting product information.

[0775] 3. The emotion engine analyzes the emotion data and sends the results to the server.

[0776] 4. The server retrieves product data from the database, performs data cleaning, and runs a value calculation algorithm based on the analyzed sentiment data to calculate the final value information.

[0777] 5. The terminal displays the value information sent from the server to the user, who then decides whether to purchase the cafe product based on this information.

[0778] Prompt Sentence Examples

[0779] Below are some example prompts to use in the emotion engine as input to the generative AI model.

[0780] text

[0781] Facial image: Image data path

[0782] Expected emotions: happy, anxious, sad, surprised, angry, neutral, disgust

[0783] This specific structure enables the system of the invention to provide more personalized value information that takes into account the user's emotions.

[0784] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0785] Step 1:

[0786] A user uses a smartphone to scan a product in a store. The input data is the scanned barcode or QR code of the product, and the smartphone camera captures the user's facial expressions and voice. The output is a product information request and captured emotion data.

[0787] Step 2:

[0788] The terminal sends a product information request and captured emotion data to the server. The input data are the product scan results and the user's emotion data, which are sent to the server. The output is the request and emotion data received by the server.

[0789] Step 3:

[0790] The server collects data about products, services, or locations from various data sources. The input data is information collected from online stores, review sites, map services, etc., and the output is the collected product data.

[0791] Step 4:

[0792] The server stores the collected data in a database and performs preprocessing. The input data is the collected product data, and the output is the data after preprocessing. This preprocessing includes data cleaning (removal of outliers and invalid data).

[0793] Step 5:

[0794] The server uses an emotion engine to analyze emotion data from the user's facial expressions and voice. The input data is the user's facial image and voice data, and the output is the type and intensity of the analyzed emotion. This analysis uses a facial recognition model and an emotion analysis model.

[0795] Step 6:

[0796] The server runs an algorithm that uses multiple indicators to calculate statistical value based on the collected data and analyzed sentiment data. The input data is preprocessed product data and analyzed sentiment data, and the output is statistical value information. The algorithm includes the average, median, and standard deviation of price, as well as review rating points.

[0797] Step 7:

[0798] The server returns the calculated value information to the terminal. The input data is statistical value information, and the output is value information received by the user's terminal.

[0799] Step 8:

[0800] The terminal displays the received value information to the user. The input data is the value information sent from the server, and the output is information that the user can visually confirm. Based on this, the user can decide whether or not to purchase the product.

[0801] These steps enable the system of the present invention to provide more personalized value information in real time, taking into account the user's emotions.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] [Third embodiment]

[0806] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0807] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0808] 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).

[0809] 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.

[0810] 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.

[0811] 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).

[0812] 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.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] 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."

[0818] ---

[0819] The present invention relates to a system that calculates the fair and equitable value of products, services, or location information based on data about the products, services, or location information that users obtain from various sources. This system is composed of components including a server, a terminal, and a user. A specific embodiment is described below.

[0820] System Overview

[0821] server

[0822] The server collects data related to products, services, or location information from various data sources via the Internet. The collected data is stored in a database, where data cleaning is performed to remove outliers and invalid data. The server also runs an algorithm to calculate statistical value using multiple indicators based on the collected data.

[0823] Terminal

[0824] The terminal receives information requests from users and sends them to the server. It has the function of displaying the value information returned from the server. Users can easily check fair and impartial value information through the terminal.

[0825] User

[0826] Users want to know the value of a product, service, or location information, so they use their device to make an information request and use the returned value information to make a purchase decision or use decision for the product or service.

[0827] Program processing overview

[0828] 1. Data Collection

[0829] The server uses various APIs and web scraping tools to gather the required information from data sources, such as price information from online stores, ratings from review sites, and location information from map services.

[0830] 2. Data storage and preprocessing

[0831] The server stores the collected data in a database, where data cleaning is performed to remove invalid data and outliers and improve the quality of the data.

[0832] 3. Value Calculation Algorithm

[0833] The server runs an algorithm that calculates the mean, median, and standard deviation of the price information and aggregates the review rating points to calculate the value of the product, service, or location information in question.

[0834] 4. User Request Processing

[0835] The device receives a request from the user and sends the information to the server. For example, a user wants to check the value of a "specific product" on their smartphone, and the device sends the request to the server.

[0836] 5. Presentation of value information

[0837] The server retrieves value information from the database based on the request and returns it to the terminal. The terminal displays the value information received from the server to the user. For example, information such as the average price, review rating, and ranking of the product is displayed.

[0838] Specific examples

[0839] For example, if a user wants to know the value of a certain electronic device,

[0840] 1. A user uses a smartphone to input a request to find out the value of an electronic device into the device.

[0841] 2. The device sends the request to the server.

[0842] 3. The server collects price information and evaluation data related to electronic devices from online stores, review sites, etc. and stores it in a database.

[0843] 4. The server performs data cleaning to remove outliers and unreliable data.

[0844] 5. The server runs a value calculation algorithm to calculate the value of the electronic device by combining the average, median, standard deviation, and review rating points of the price.

[0845] 6. The server returns the calculated value information to the terminal.

[0846] 7. The terminal displays the received value information to the user, who then decides whether or not to make a purchase based on that information.

[0847] By implementing such an embodiment, the system of the present invention allows users to efficiently obtain highly reliable value information from a vast number of information sources and make fair and impartial judgments.

[0848] The processing flow will be explained below.

[0849] ---

[0850] Step 1:

[0851] A server collects data about products, services, or locations from multiple data sources over the Internet, for example, using an online store's API to obtain pricing information and reviews, and a map service's API to obtain location information and user ratings.

[0852] Step 2:

[0853] The server stores the collected data in a database, where it remains raw and is saved for further processing.

[0854] Step 3:

[0855] The server performs data cleaning to remove outliers and fraudulent data from the stored data, for example filtering out abnormally high prices or impossible review ratings.

[0856] Step 4:

[0857] The server runs a value calculation algorithm based on the cleaned data, which calculates the average, median, and standard deviation of the price information, and also takes into account review evaluation points to calculate the overall value.

[0858] Step 5:

[0859] The terminal receives a request for information from a user and transmits the request to a server. For example, a user uses the terminal to input, "I want to know the value of a particular electronic device."

[0860] Step 6:

[0861] The server receives the request from the terminal and retrieves value information about the requested product or service from the database. The retrieved information includes the statistical value calculated in the previous step.

[0862] Step 7:

[0863] The server returns value information to the terminal, including the average, median, and standard deviation of detailed prices, review evaluation points, and so on.

[0864] Step 8:

[0865] The terminal displays the value information received from the server to the user, allowing the user to easily confirm that the value information is fair and impartial.

[0866] Step 9:

[0867] Users make decisions about purchasing or using products or services based on the displayed value information. For example, they might decide, "This electronic device has an average price of 50,000 yen and a review rating of 4.5 / 5, so it's worth buying."

[0868] Through the above steps, the system of the present invention can provide users with highly reliable and fair value information and support efficient decision-making.

[0869] Example 1

[0870] 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."

[0871] Conventional systems face challenges in consistently collecting data on products, services, or location information from a variety of sources and assessing its value, making it difficult for users to make accurate and fair judgments. In particular, they face challenges in ensuring the reliability and quality of data, and in lacking algorithms for calculating value using appropriate indicators based on collected data. Furthermore, they lack the functionality to quickly and accurately provide value information in response to user requests.

[0872] 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.

[0873] In this invention, the server includes means for collecting information on products, services, or location information from various information sources, means for storing the collected information in a database and performing preprocessing, means for executing an algorithm for calculating statistical value based on multiple indicators, means for receiving information requests from users and returning value information, and means for displaying the value information on user terminals, thereby enabling users to quickly obtain highly reliable value information and make accurate and fair decisions.

[0874] "Diverse sources" refers to multiple data providers that provide data about products, services, or locations.

[0875] "Product" refers to an individual or set of goods or consumer goods sold in a particular market.

[0876] "Service" refers to a transaction related to the provision of a particular activity or functionality.

[0877] "Location information" is data that indicates a geographical location, and includes coordinates and address information of a specific location.

[0878] "Means of collecting information" refers to a system configuration that automatically obtains data using APIs or web scraping tools.

[0879] "Database" means an electronic storage system that organizes and stores collected information so that it can be efficiently retrieved and used at a later time.

[0880] "Preprocessing means" refers to processing to improve the quality of collected data using methods such as data cleaning and data normalization.

[0881] "Multiple metrics" refers to different metrics or calculation methods for assessing and analyzing data characteristics and trends. Examples include mean, median, standard deviation, etc.

[0882] "Statistical value calculation algorithm" refers to a mathematical method or computational model that analyzes collected data and provides an objective value assessment.

[0883] "Means for receiving an information request and returning value information" refers to the process of searching a database in response to an inquiry from a user and returning the relevant information to the user.

[0884] "User Device" means an electronic device used by a User to enter information requests and view returned information. Examples include smartphones, tablets, and personal computers.

[0885] The present invention relates to a system that calculates the fair and equitable value of products, services, or location information based on data about the products, services, or locations that users obtain from various sources. This system consists of three components: a server, a terminal, and a user.

[0886] System Overview

[0887] server

[0888] The server collects data from various sources via the internet. Specific software used for this includes APIs and web scraping tools. For example, an API is used to obtain pricing information from online stores, and a web scraping tool is used to collect ratings from review sites. The collected data is stored in a database such as MySQL. The server then performs data cleaning to remove outliers and invalid data and improve data quality. Furthermore, the server calculates the mean, median, and standard deviation of the price information and runs algorithms that combine review rating points to calculate the value of the product, service, and location information.

[0889] Terminal

[0890] The terminal has the function of receiving information requests from users and sending those requests to a server. Specific examples of terminals include smartphones, tablets, and PCs. When a user inputs a request through the terminal, the request is sent to the server as an HTTP request. The value information returned from the server is displayed to the user by the terminal. The displayed content is diverse and includes, for example, "average product price," "review rating," and "ranking."

[0891] User

[0892] When a user wants to know the value of a particular product, service, or location, they use their device to request that information. An example of a request might be, "What is the market value of this electronic device?" They send a request and use the returned value information to make a purchasing decision on the product or service.

[0893] Specific examples

[0894] For example, if a user wants to know the value of an iPhone 13,

[0895] 1. A user uses their smartphone to enter a request such as, "I want to know the value of my iPhone 13."

[0896] 2. The device sends the request to the server. The request format will be something like "Product name: iPhone 13."

[0897] 3. The server collects price information and evaluation data related to the iPhone 13 from online stores (e.g., Amazon and Rakuten) and review sites (e.g., Kakaku.com) and stores it in a database.

[0898] 4. The server performs data cleaning to remove unreliable data and outliers.

[0899] 5. The server runs a value calculation algorithm and calculates the value of the iPhone 13 by combining the average price, median price, standard deviation, and review rating points. For example, the result is "average price is 100,000 yen, and review rating is 4.8 / 5."

[0900] 6. The server returns the calculated value information to the terminal.

[0901] 7. The terminal displays the received value information to the user, who then decides whether or not to make a purchase based on that information.

[0902] This system allows users to efficiently obtain highly reliable value information and make fair and impartial decisions.

[0903] Prompt Sentence Examples

[0904] "I'd like to know the market value of this electronic device. I'd like the market value calculated based on online store pricing, reviews, and related data."

[0905] This system's series of processes allows users to quickly obtain highly reliable value information from a vast number of information sources, enabling them to make more accurate decisions regarding purchases and usage.

[0906] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0907] Processing Steps

[0908] Step 1:

[0909] A server collects data about products, services, or locations from various sources. Specific tools used for collection include APIs and web scraping tools. For example, an online store's API can be called to obtain price information, and a web scraping tool can be used to collect rating data from review sites. The source's URL and API key are used as input, and the collected raw data is obtained as output.

[0910] Step 2:

[0911] The server stores the collected data in a database. For this, a database management system such as MySQL or PostgreSQL is used. Before storing it in the database, the data structure is unified and duplicate data is removed. Raw data is given as input, and cleaned data is stored in the database as output.

[0912] Step 3:

[0913] The server performs data cleaning on the stored data. This includes removing invalid data and outliers, and filling in missing data. Specifically, if the price of a certain product is extremely high or low, the data is removed. Missing values ​​are also filled in with the mean or median. The data stored in the database is given as input, and cleaned data is obtained as output.

[0914] Step 4:

[0915] The server runs an algorithm that calculates statistical value based on multiple indicators. It calculates the average, median, and standard deviation of price information and integrates review evaluation points. For example, it calculates the overall value by taking the average price information of a specific product and weighting it with the evaluation points from review sites. Cleaned data is given as input, and value information is obtained as output.

[0916] Step 5:

[0917] A user uses a device to input a request to find out the value of a particular product or service. For example, they might type "Find out the value of an iPhone 13" on their smartphone. The user's request is given as input, and the request is sent from the device to the server as output.

[0918] Step 6:

[0919] The server receives a request from the terminal and searches the database for value information on the corresponding product or service. The user request is given as input, and the corresponding value information is obtained from the server as output.

[0920] Step 7:

[0921] The server formats the acquired value information and returns it to the terminal. For example, detailed value information including the average price, median price, standard deviation price, review evaluation points, etc. is formatted. The acquired value information is given as input, and the formatted value information is returned to the terminal as output.

[0922] Step 8:

[0923] The terminal displays the received value information to the user. For example, for a specific electronic device, information such as "average price is 100,000 yen, and review rating is 4.8 / 5" is displayed. The value information returned from the server is given as input, and the specific value information is displayed on the user's screen as output.

[0924] Through this series of processing steps, the user can efficiently obtain highly reliable value information and make a fair and impartial decision.

[0925] (Application example 1)

[0926] 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."

[0927] Today's users face difficulties in accurately and quickly grasping the value of products and services obtained from a variety of information sources. It also takes a great deal of time and effort to find reliable data from the vast amount of information and to make a fair and impartial value assessment. Furthermore, when selecting a product or service, users are required to comprehensively evaluate multiple indicators, such as price and reviews, but this is not easy to achieve. A system that solves these problems is needed.

[0928] 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.

[0929] In this invention, the server includes means for collecting data on products, services, or location information from various data sources, means for storing the collected data in a database and performing preprocessing, means for executing an algorithm for calculating statistical value based on multiple indicators, means for receiving information requests on products or services from a user's terminal, generating value information based on the request, and returning the value information to the user's terminal, and means for triggering data collection using the barcode or name of the product or service. This enables users to quickly and efficiently perform reliable, fair, and impartial value assessments based on data obtained from various information sources.

[0930] - "Diverse data sources" refers to the means of obtaining data from various information providers on the Internet, APIs, web scraping tools, etc.

[0931] "Products" refers to physical and digital goods sold in the Marketplace.

[0932] "Services" include any activities, functions, or skills provided for a fee or free of charge.

[0933] "Location Information" refers to data relating to a geographic location or position.

[0934] A "database" is a system for efficiently storing, managing, and retrieving collected data.

[0935] "Preprocessing" refers to data quality improvement measures including data cleaning, normalization, and conversion to another format.

[0936] "Statistical value" refers to the overall evaluation of the data calculated based on the mean, median, standard deviation, and other statistical indicators.

[0937] An "algorithm" refers to a set of procedures or formulas for performing a particular calculation or operation.

[0938] "User terminal" includes devices used by users, such as smartphones, tablets, and personal computers.

[0939] An "information request" refers to an operation in which a user requests specific information through a terminal.

[0940] "Value information" refers to the evaluation results of products, services, or location information analyzed based on collected data.

[0941] A "barcode" is a visual representation of a unique sequence of numbers and / or letters used to identify a product.

[0942] "Name" means a unique word or phrase used to identify a particular product or service.

[0943] The present invention relates to a system that calculates the fair and equitable value of products, services, or location information based on data about the products, services, or location information that a user obtains from various information sources. The system is composed of components including a server, a terminal, and a user. Specific embodiments are described below.

[0944] System Overview

[0945] server

[0946] The server collects data about products, services, or location information from various data sources via the Internet. Data sources include online stores, review sites, and map services. The collected data is stored in a database, and data cleaning is performed to remove outliers and invalid data. The server also runs an algorithm that calculates statistical value using multiple indicators based on the collected data. This algorithm calculates the average, median, and standard deviation of price information and calculates the value of the product or service by integrating review evaluation points.

[0947] Terminal

[0948] The terminal receives an information request from the user and sends the request to the server. The request includes the name of the product or service and a barcode. It has the function of displaying the value information returned from the server. Specifically, a mobile device such as a smartphone or tablet is used as the terminal. The user can easily check fair and impartial value information through the terminal.

[0949] User

[0950] A user wants to know the value of a product, service, or location information, so they use their device to make an information request. Based on the returned value information, they can make a decision to purchase or use the product or service. For example, if a user wants to know the value of a certain electronic device, they can use their smartphone to enter the name or barcode of the electronic device and obtain the value information from the server.

[0951] Program processing

[0952] This program mainly handles the following processes: data collection, data cleaning, value calculation, and user request processing.

[0953] Hardware and software used

[0954] Hardware: User devices such as smartphones, tablets, and PCs

[0955] Software: Programming languages ​​and libraries such as Python, requests, statistics, numpy, etc. APIs used include online store APIs and review site APIs.

[0956] Specific examples

[0957] For example, if a user wants to know the value of an "iPhone 13," they open their smartphone and enter "iPhone 13" as the product name. The device sends this request to the server. The server collects price information and review ratings from online stores and review sites and stores them in a database. It performs data cleaning to remove outliers and invalid data, and calculates the value by combining the mean, median, standard deviation, and review rating points of the price information. The server sends the calculated value information back to the device, and the device displays the received value information to the user.

[0958] Prompt Sentence Examples

[0959] The user can use prompts such as:

[0960] "What is the value of the iPhone 13? I'd like to know a fair and impartial value based on price information and review ratings."

[0961] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0962] Step 1: Data collection

[0963] Based on the product or service name or barcode specified by the user, the server collects relevant data using online store APIs or review site APIs. Information obtained from data sources includes price information, review ratings, location information, etc. The input of this step is the user request, and the output is the collected raw data.

[0964] Step 2: Data storage and preprocessing

[0965] The server stores the collected raw data in a database and performs preprocessing, which includes data cleaning to remove outliers and invalid data. The input of this step is the collected raw data, and the output is a clean dataset.

[0966] Step 3: Data cleaning

[0967] The server runs a data cleaning process on the stored data to remove outliers and incorrect data, which may include, for example, removing unusually high or low prices. The input to this step is the stored raw data, and the output is the cleaned data.

[0968] Step 4: Value calculation

[0969] The server runs an algorithm to calculate statistical value based on the cleaned data. Specifically, it calculates the mean, median, and standard deviation of the price information and integrates the review rating points. The input of this step is the cleaned data, and the output is the calculated value information.

[0970] Step 5: User Request Processing

[0971] The terminal receives an information request from the user and sends that information to the server. The user inputs a product name or barcode, and the terminal sends that data to the server as a request. The input of this step is the user's request, and the output is the request sent to the server.

[0972] Step 6: Retrieving data based on the request

[0973] The server searches for and acquires the corresponding license information from the database based on the request received from the terminal. The input to this step is the request from the terminal, and the output is the acquired license information.

[0974] Step 7: Return and display of value information

[0975] The server returns the acquired value information to the terminal, which then displays it to the user. This allows the user to check information such as the average price, median, standard deviation, and review rating of the product or service. The input to this step is the value information from the server, and the output is the information displayed to the user.

[0976] 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.

[0977] ---

[0978] This invention combines a system that calculates the fair and equitable value of products, services, or location data obtained by users from various sources with an emotion engine that recognizes and analyzes user emotions. This system is composed of the following components: a server, a terminal, a user, and the emotion engine. A specific embodiment is shown below.

[0979] System Overview

[0980] server

[0981] The server collects data related to products, services, or location information from various data sources via the Internet. The collected data is stored in a database, and data cleaning is performed to remove outliers and invalid data. The server then runs an algorithm to calculate statistical value using multiple indicators based on the collected data and sentiment data.

[0982] Terminal

[0983] The device receives information requests and emotion information from the user and sends the requests to the server. It also has the function of displaying the value information returned from the server. The user can easily check the fair and just value information through the device.

[0984] User

[0985] When a user wants to know the value of a product, service, or location, they use their device to make an information request and express their emotions through facial expressions, voice, or text, which are then analyzed by the emotion engine.

[0986] Emotion Engine

[0987] The emotion engine recognizes emotions from the user's facial expressions, voice, or text and stores them in a database. The server then applies this emotion data to a value calculation algorithm to provide personalized value information corresponding to the user's emotions.

[0988] Program processing overview

[0989] 1. Data Collection

[0990] The server collects the necessary information from multiple data sources, such as online stores, review sites, and map services, and stores it in a database.

[0991] 2. Data storage and preprocessing

[0992] The server stores the collected data in a database and performs data cleaning to remove outliers and invalid data.

[0993] 3. Collecting Emotional Data

[0994] The terminal acquires data for recognizing emotions through the user's facial expressions, voice, or text, and sends it to the emotion engine.

[0995] 4. Sentiment analysis

[0996] The emotion engine analyzes the collected facial, voice, or text data to recognize the user's emotions, and the recognized emotion data is stored in a database.

[0997] 5. Value Calculation Algorithm

[0998] The server runs a value calculation algorithm based on the cleaned data and sentiment data, and calculates the overall value by integrating the average, median, and standard deviation of the price and review rating points.

[0999] 6. User Request Processing

[1000] The terminal receives a request from the user and transmits the request and the user's emotion data to the server.

[1001] 7. Obtaining and returning value information

[1002] The server receives the request, retrieves value information for the requested product, service, or location information from a database, and returns it to the terminal.

[1003] 8. Display of Value Information

[1004] The terminal displays the value information received from the server to the user, allowing the user to easily confirm that the value information is fair and impartial.

[1005] Specific examples

[1006] For example, if a user wants to know the value of a certain cafe,

[1007] 1. A user uses a smartphone to input a request to find out the value of a cafe.

[1008] 2. The device sends the request to the server.

[1009] 3. At the same time, the user looks at photos of the cafe and reads reviews, and the device sends the user's facial expressions and voice to the emotion engine.

[1010] 4. The emotion engine analyzes the user's emotions from their facial expressions and voice, and stores the emotion data in a database.

[1011] 5. The server collects price information and rating data related to the cafe from online stores, review sites, map services, etc. and stores it in a database.

[1012] 6. The server performs data cleaning to remove outliers and unreliable data.

[1013] 7. The server runs a value calculation algorithm and calculates the cafe's value by integrating the average, median, and standard deviation of the prices, review rating points, and sentiment data.

[1014] 8. The server returns the calculated value information to the terminal.

[1015] 9. The terminal displays the received value information to the user, who then decides whether to visit the cafe based on that information and their own feelings.

[1016] In such an embodiment, the system of the present invention can provide users with highly reliable and fair value information, and by incorporating emotional elements, can efficiently provide more personalized information.

[1017] The processing flow will be explained below.

[1018] ---

[1019] Step 1:

[1020] A server collects data about products, services, or location information from multiple data sources via the Internet, specifically, using APIs of online stores to obtain price information and reviews, and APIs of map services to obtain location information and user ratings.

[1021] Step 2:

[1022] The server stores the collected data in a central database, including pricing information, reviews, and location information.

[1023] Step 3:

[1024] The server performs data cleaning to remove outliers and fraudulent data from the stored data, filtering out price anomalies and unreliable reviews.

[1025] Step 4:

[1026] The terminal receives the user's information request and sends the request to the server. For example, the user might type, "I want to know the value of a particular cafe," and the terminal sends the information to the server.

[1027] Step 5:

[1028] The device captures the user's facial expressions, voice, or entered text and sends that information to the emotion engine, using a camera, microphone, or text input.

[1029] Step 6:

[1030] The emotion engine analyzes the user's facial expressions and voice / text data to recognize the user's emotions. For example, if the user is smiling, it will determine that the user is feeling "joy" and generate emotion data.

[1031] Step 7:

[1032] The emotion engine stores the recognized emotion data in a central database, which is then used in the value calculation algorithm.

[1033] Step 8:

[1034] The server runs a value calculation algorithm based on the stored cleaning data and sentiment data, integrating the average, median, and standard deviation of price information, review evaluation points, and sentiment data to calculate the overall value.

[1035] Step 9:

[1036] The server then returns the calculated value information to the device, including average prices, review ratings, rankings, and sentiment-based recommendations.

[1037] Step 10:

[1038] The device displays the received value information to the user. For example, it may display information such as, "This cafe has an average rating of 4.5 / 5, a price range of ¥800 - ¥1200, and user emotional data indicates a very high level of satisfaction."

[1039] Step 11:

[1040] The user makes a decision about purchasing or using a product or service based on the displayed value information and emotional data. For example, they might decide, "This cafe has high ratings and many positive emotional reviews, so it's worth visiting."

[1041] In this way, by having the server, terminal, and emotion engine work in cooperation, the system of the present invention can provide users with highly reliable and fair value information, and can also efficiently provide personalized information that takes emotional elements into account.

[1042] Example 2

[1043] 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."

[1044] Conventional systems cannot take user emotions into account when calculating statistical values ​​based on information obtained from various data sources, making it difficult to provide personalized value information for individual users. Furthermore, inaccurate or invalid data can significantly affect value calculations, reducing reliability. Therefore, there is a need for a method to provide accurate and reliable value information that incorporates user emotions.

[1045] 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.

[1046] In this invention, the server includes means for collecting data on products, services, or location information from various information sources, means for storing the collected data in a database and performing data cleaning and preprocessing, means for acquiring emotional data from a user's facial expressions, voice, or text, means for analyzing the collected emotional data and recognizing emotions, means for executing a statistical value calculation algorithm based on the cleaned data and emotional data, and means for receiving information requests from users and returning value information, thereby enabling the provision of accurate and personalized value information that takes user emotions into consideration.

[1047] "Diverse sources" refers to multiple types of data providers accessible via the Internet, such as online stores, review sites, and map services.

[1048] "Product, Service, or Location Information" means information about goods, services offered, and particular geographic locations that may be of interest to a user.

[1049] "Data collection means" refers to the combination of software and hardware used to obtain the required data from various sources via the Internet.

[1050] A "database" is a structured data storage system for storing, retrieving, and manipulating collected data.

[1051] "Means for performing data cleaning" refers to the process of removing outliers and incorrect data from collected data to improve the integrity and reliability of the data.

[1052] "Pre-processing means" refers to a series of processes that prepare the collected data in a format that can be used by the value calculation algorithm.

[1053] "Means for acquiring emotional data" refers to devices such as cameras, microphones, and text input devices for collecting the user's facial expressions, voice, or text data, as well as software for controlling them.

[1054] "Means for analyzing emotional data" refers to a machine learning model and its execution environment for processing collected emotional data and recognizing user emotions.

[1055] A "value calculation algorithm" is a set of calculation methods that calculates statistical values ​​based on collected data and analyzed emotional data.

[1056] "Means for receiving information requests" refers to a combination of software and hardware for receiving requests for information from users.

[1057] The "means for returning value information" refers to a combination of software and hardware for transmitting the calculated value information to the user's terminal and displaying it.

[1058] This invention combines a system that calculates the fair and equitable value of products, services, or location data obtained by users from various sources with an emotion engine that recognizes and analyzes user emotions. The system is composed of the following components: a server, a terminal, a user, and an emotion engine.

[1059] Server Configuration

[1060] The server collects data about products, services, or location information from various data sources via the Internet. Specifically, the server collects data from online stores, review sites, map services, etc., and stores it in a database. It also includes a process for performing data cleaning to remove outliers and fraudulent data. The data stored in the database is then used to run value calculation algorithms based on statistical indicators such as the average, median, and standard deviation of prices, and review rating points, using data analysis programming languages ​​such as Python and R.

[1061] Device configuration

[1062] The terminal is responsible for receiving information requests and emotional information from the user. The terminal is a device such as a smartphone or tablet that captures the user's facial expressions and voice through a camera and microphone and sends the user's request to the server. It also has the function of displaying the value information returned by the server. For example, if a user inputs a request into the terminal such as "Please tell me the current rating and average price of XX cafe," the request is sent to the server.

[1063] User Roles

[1064] When a user wants to know the value of a product, service, or location information, they use their device to make an information request. The user expresses their emotions through facial expressions, voice, or text, and the device sends the information to the emotion engine for emotional analysis. The emotional data collected in this way is sent to the server and reflected in the value calculation algorithm.

[1065] Emotion engine configuration

[1066] The emotion engine is responsible for recognizing emotions from the user's facial expressions, voice, or text and storing them in a database. The emotion engine uses a machine learning model (e.g., a generative AI model) to classify the user's emotions into categories such as positive, negative, or surprise. The server then feeds this emotion data into a value calculation algorithm to provide personalized value information corresponding to the user's emotions.

[1067] Specific examples

[1068] If a user wants to know the value of a certain cafe, the specific process is as follows:

[1069] 1. The user uses their smartphone to input a request to find out the value of a certain cafe. Example: "I want to know the rating and current average price of a certain cafe."

[1070] 2. The device sends the request to the server.

[1071] 3. At the same time, the user looks at photos of the cafe and reads reviews, and the device sends the user's facial expressions and voice to the emotion engine.

[1072] 4. The emotion engine analyzes the user's emotions from their facial expressions and voice, and stores the emotion data in a database.

[1073] 5. The server collects price information and rating data related to the cafe from online stores, review sites, map services, etc. and stores it in a database.

[1074] 6. The server performs data cleaning to remove outliers and unreliable data.

[1075] 7. The server runs a value calculation algorithm and calculates the cafe's value by integrating the average, median, and standard deviation of the prices, review rating points, and sentiment data.

[1076] 8. The server returns the calculated value information to the terminal.

[1077] 9. The terminal displays the received value information to the user, who then decides whether to visit the cafe based on that information and their own feelings.

[1078] This concludes the description of the embodiment of the present invention. This system provides users with highly reliable and fair value information, and by incorporating emotional elements, it efficiently provides more personalized information.

[1079] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1080] Processing step details

[1081] Step 1: Data collection

[1082] The server collects data about products, services, or location information from various data sources (e.g., online stores, review sites, map services) over the Internet.

[1083] Input: Your server configured API endpoint or web scraping script.

[1084] Processing: Sending API requests or scraping data from web pages.

[1085] Output: The retrieved data (e.g., price information, review ratings, location information).

[1086] Specific operation: The server periodically accesses each data source, collects information, and stores it in a database.

[1087] Step 2: Data storage and preprocessing

[1088] The server stores the collected data in a database and performs data cleaning to remove outliers and invalid data.

[1089] Input: The data collected in Step 1.

[1090] Processing: Inserting data into the database, checking data integrity and removing outliers using SQL queries and ETL processes.

[1091] Output: A clean and reliable dataset.

[1092] Specific operation: The server automates data preprocessing using an ETL tool (e.g., Apache NiFi, Talend).

[1093] Step 3: Collecting emotion data

[1094] The terminal acquires emotion data through the user's facial expressions, voice, or text, and transmits it to the emotion engine.

[1095] Input: User facial expression, voice, and text data.

[1096] Processing: Data capture from cameras and microphones and real-time processing of that data.

[1097] Output: Sentiment data for analysis.

[1098] Specific operation: The device captures the user's emotions using sensor devices (camera, microphone) equipped on the device and transmits the data via Wi-Fi or Bluetooth.

[1099] Step 4: Sentiment analysis

[1100] The emotion engine analyzes collected facial, voice, or text data to recognize the user's emotions.

[1101] Input: The emotion data collected in step 3.

[1102] Processing: Sentiment analysis using machine learning models (e.g., generative AI models).

[1103] Output: User's emotion category (e.g. positive, negative, surprised).

[1104] How it works: The emotion engine uses machine learning libraries (e.g., TensorFlow, PyTorch) to perform real-time analysis of data.

[1105] Step 5: Value calculation algorithm

[1106] The server runs a value calculation algorithm based on the cleaned data and emotion data.

[1107] Input: The clean dataset (Step 2) and the parsed sentiment data (Step 4).

[1108] Processing: Calculation and synthesis of statistical indicators using data analysis tools.

[1109] Output: Final value information (e.g. price mean, median, standard deviation, review rating points).

[1110] Specific operation: The server uses data analysis tools such as Pandas, NumPy, and Scikit-learn to calculate value based on the most recent data.

[1111] Step 6: User Request Processing

[1112] The terminal receives a request from the user and transmits the request and the user's emotion data to the server.

[1113] Input: User request (e.g., "I want to know the rating and current average price of XX Cafe").

[1114] Processing: Formatting and sending request information.

[1115] Output: Request sent to the server.

[1116] Specific operation: The device enters a request into a form and sends it to the server via an HTTP request or WebSocket.

[1117] Step 7: Obtaining and returning value information

[1118] The server receives the request, retrieves value information for the requested product, service, or location information from a database, and returns it to the terminal.

[1119] Input: User requests and data stored in the server.

[1120] Processing: Data extraction using SQL queries and data formatting.

[1121] Output: Value information data in JSON format.

[1122] Specific operation: The server extracts the necessary data using an SQL query, converts it into JSON format, and sends it to the terminal.

[1123] Step 8: Viewing Value Information

[1124] The terminal displays the value information received from the server to the user.

[1125] Input: Value information returned by the server.

[1126] Processing: Formatting and displaying value information.

[1127] Output: Visually display data to the user.

[1128] Specific operation: The terminal formats and displays the received data on the application screen, displaying it in graphs and text so that it is easy for the user to understand.

[1129] The above is the specific processing flow of this system.

[1130] (Application example 2)

[1131] 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."

[1132] Conventional value calculation systems calculate value solely based on price and review ratings, without taking into account the user's subjective feelings or purchasing intent. This makes it difficult to provide users with optimal information for their actual purchasing experience. Furthermore, users have few clues to determine whether the value information matches their own feelings and preferences. To solve this problem, a system is needed that integrates user emotional data and provides more personalized value information.

[1133] 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.

[1134] In this invention, the server includes means for collecting data on products, services, or location information from various data sources, means for storing the collected data in a database and performing preprocessing, means for executing an algorithm for calculating statistical value based on multiple indicators, means for receiving information requests from users and returning value information, means for acquiring emotional data from the user's facial expressions or voice using a camera function, means for adjusting parameters in the value calculation algorithm based on the acquired emotional data, and means for integrating the emotional data and the value information and displaying it to the user. This makes it possible to provide more personalized value information in real time that takes into account the user's subjective emotions.

[1135] "Data Source" means an information source on the Internet that provides product, service, or location data in a variety of formats.

[1136] A "database" is a structured information storage system for storing and managing collected data.

[1137] "Preprocessing" refers to processes such as data cleaning, filtering, and normalization that are carried out to improve the quality of collected data.

[1138] An "algorithm" is a series of calculation procedures for calculating statistical value based on multiple indicators.

[1139] An "information request" is a user's request to the system for value information about a product, service, or location.

[1140] "Value information" is information provided to users based on collected data and calculated statistical values.

[1141] "Camera function" refers to the function of a device to capture images or video.

[1142] "Emotion data" is information about emotions acquired from the user's facial expressions and voice and analyzed by the emotion engine.

[1143] A "parameter" is a variable used in calculations or adjustments in a value calculation algorithm.

[1144] An "emotion engine" is software or hardware that recognizes emotions from a user's facial expressions and voice and analyzes them as data.

[1145] An embodiment of the present invention is a system for enhancing the shopping experience, particularly in brick-and-mortar stores, by allowing users to scan products with their smartphones and collect real-time emotional data to provide personalized value information.

[1146] Program processing

[1147] Server Processing

[1148] The server collects data about products, services, or locations from various data sources, including online stores, review sites, and map services. The collected data is stored in a database and cleaned to remove outliers and invalid data. The server then runs an algorithm to calculate statistical value based on multiple indicators (such as the average price, median price, standard deviation, and review rating points). It also adjusts the parameters of the value calculation algorithm based on user sentiment data, which is reflected in the value information.

[1149] Terminal handling

[1150] When a user uses their smartphone to scan a product, a request for information about that product is sent to the server. At the same time, the smartphone's camera captures the user's facial expressions and voice, and sends the emotional data to the emotion engine. This emotional data is analyzed in real time, and the results are sent to the server. The value information returned from the server is displayed on the device, and the user makes a purchasing decision based on that information.

[1151] User Action

[1152] Users scan products in stores using their smartphones. This scan acquires product price and rating information, while the camera captures the user's facial expressions and voice. This allows the user's emotional data to be collected in real time and analyzed by the emotion engine. The analyzed emotional data is sent to a server and presented to the user as integrated value information.

[1153] Hardware and software used

[1154] Smartphone: Uses camera and network communication functions to capture the user's facial expressions and transmit emotional data.

[1155] Server: Collects data from various data sources, stores it in a database, cleans the data, and executes value calculation algorithms.

[1156] Database: Stores and manages collected data and emotion data.

[1157] Emotion Engine: Uses OpenCV and TensorFlow / Keras to recognize and analyze emotions from the user's facial expressions and voice.

[1158] Specific examples

[1159] For example, if a user scans a particular cafe product in a store, the following steps occur:

[1160] 1. A user uses a smartphone to scan a product in a cafe, and the smartphone camera captures the user's facial expressions and voice.

[1161] 2. The smartphone sends the captured emotion data to the emotion engine at the same time as requesting product information.

[1162] 3. The emotion engine analyzes the emotion data and sends the results to the server.

[1163] 4. The server retrieves product data from the database, performs data cleaning, and runs a value calculation algorithm based on the analyzed sentiment data to calculate the final value information.

[1164] 5. The terminal displays the value information sent from the server to the user, who then decides whether to purchase the cafe product based on this information.

[1165] Prompt Sentence Examples

[1166] Below are some example prompts to use in the emotion engine as input to the generative AI model.

[1167] text

[1168] Facial image: Image data path

[1169] Expected emotions: happy, anxious, sad, surprised, angry, neutral, disgust

[1170] This specific structure enables the system of the invention to provide more personalized value information that takes into account the user's emotions.

[1171] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1172] Step 1:

[1173] A user uses a smartphone to scan a product in a store. The input data is the scanned barcode or QR code of the product, and the smartphone camera captures the user's facial expressions and voice. The output is a product information request and captured emotion data.

[1174] Step 2:

[1175] The terminal sends a product information request and captured emotion data to the server. The input data are the product scan results and the user's emotion data, which are sent to the server. The output is the request and emotion data received by the server.

[1176] Step 3:

[1177] The server collects data about products, services, or locations from various data sources. The input data is information collected from online stores, review sites, map services, etc., and the output is the collected product data.

[1178] Step 4:

[1179] The server stores the collected data in a database and performs preprocessing. The input data is the collected product data, and the output is the data after preprocessing. This preprocessing includes data cleaning (removal of outliers and invalid data).

[1180] Step 5:

[1181] The server uses an emotion engine to analyze emotion data from the user's facial expressions and voice. The input data is the user's facial image and voice data, and the output is the type and intensity of the analyzed emotion. This analysis uses a facial recognition model and an emotion analysis model.

[1182] Step 6:

[1183] The server runs an algorithm that uses multiple indicators to calculate statistical value based on the collected data and analyzed sentiment data. The input data is preprocessed product data and analyzed sentiment data, and the output is statistical value information. The algorithm includes the average, median, and standard deviation of price, as well as review rating points.

[1184] Step 7:

[1185] The server returns the calculated value information to the terminal. The input data is statistical value information, and the output is value information received by the user's terminal.

[1186] Step 8:

[1187] The terminal displays the received value information to the user. The input data is the value information sent from the server, and the output is information that the user can visually confirm. Based on this, the user can decide whether or not to purchase the product.

[1188] These steps enable the system of the present invention to provide more personalized value information in real time, taking into account the user's emotions.

[1189] 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.

[1190] 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.

[1191] 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.

[1192] [Fourth embodiment]

[1193] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1194] 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.

[1195] 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).

[1196] 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.

[1197] 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.

[1198] 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).

[1199] 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.

[1200] 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.

[1201] 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.

[1202] 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.

[1203] 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.

[1204] 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.

[1205] 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."

[1206] ---

[1207] The present invention relates to a system that calculates the fair and equitable value of products, services, or location information based on data about the products, services, or location information that users obtain from various sources. This system is composed of components including a server, a terminal, and a user. A specific embodiment is described below.

[1208] System Overview

[1209] server

[1210] The server collects data related to products, services, or location information from various data sources via the Internet. The collected data is stored in a database, where data cleaning is performed to remove outliers and invalid data. The server also runs an algorithm to calculate statistical value using multiple indicators based on the collected data.

[1211] Terminal

[1212] The terminal receives information requests from users and sends them to the server. It has the function of displaying the value information returned from the server. Users can easily check fair and impartial value information through the terminal.

[1213] User

[1214] Users want to know the value of a product, service, or location information, so they use their device to make an information request and use the returned value information to make a purchase decision or use decision for the product or service.

[1215] Program processing overview

[1216] 1. Data Collection

[1217] The server uses various APIs and web scraping tools to gather the required information from data sources, such as price information from online stores, ratings from review sites, and location information from map services.

[1218] 2. Data storage and preprocessing

[1219] The server stores the collected data in a database, where data cleaning is performed to remove invalid data and outliers and improve the quality of the data.

[1220] 3. Value Calculation Algorithm

[1221] The server runs an algorithm that calculates the mean, median, and standard deviation of the price information and aggregates the review rating points to calculate the value of the product, service, or location information in question.

[1222] 4. User Request Processing

[1223] The device receives a request from the user and sends the information to the server. For example, a user wants to check the value of a "specific product" on their smartphone, and the device sends the request to the server.

[1224] 5. Presentation of value information

[1225] The server retrieves value information from the database based on the request and returns it to the terminal. The terminal displays the value information received from the server to the user. For example, information such as the average price, review rating, and ranking of the product is displayed.

[1226] Specific examples

[1227] For example, if a user wants to know the value of a certain electronic device,

[1228] 1. A user uses a smartphone to input a request to find out the value of an electronic device into the device.

[1229] 2. The device sends the request to the server.

[1230] 3. The server collects price information and evaluation data related to electronic devices from online stores, review sites, etc. and stores it in a database.

[1231] 4. The server performs data cleaning to remove outliers and unreliable data.

[1232] 5. The server runs a value calculation algorithm to calculate the value of the electronic device by combining the average, median, standard deviation, and review rating points of the price.

[1233] 6. The server returns the calculated value information to the terminal.

[1234] 7. The terminal displays the received value information to the user, who then decides whether or not to make a purchase based on that information.

[1235] By implementing such an embodiment, the system of the present invention allows users to efficiently obtain highly reliable value information from a vast number of information sources and make fair and impartial judgments.

[1236] The processing flow will be explained below.

[1237] ---

[1238] Step 1:

[1239] A server collects data about products, services, or locations from multiple data sources over the Internet, for example, using an online store's API to obtain pricing information and reviews, and a map service's API to obtain location information and user ratings.

[1240] Step 2:

[1241] The server stores the collected data in a database, where it remains raw and is saved for further processing.

[1242] Step 3:

[1243] The server performs data cleaning to remove outliers and fraudulent data from the stored data, for example filtering out abnormally high prices or impossible review ratings.

[1244] Step 4:

[1245] The server runs a value calculation algorithm based on the cleaned data, which calculates the average, median, and standard deviation of the price information, and also takes into account review evaluation points to calculate the overall value.

[1246] Step 5:

[1247] The terminal receives a request for information from a user and transmits the request to a server. For example, a user uses the terminal to input, "I want to know the value of a particular electronic device."

[1248] Step 6:

[1249] The server receives the request from the terminal and retrieves value information about the requested product or service from the database. The retrieved information includes the statistical value calculated in the previous step.

[1250] Step 7:

[1251] The server returns value information to the terminal, including the average, median, and standard deviation of detailed prices, review evaluation points, and so on.

[1252] Step 8:

[1253] The terminal displays the value information received from the server to the user, allowing the user to easily confirm that the value information is fair and impartial.

[1254] Step 9:

[1255] Users make decisions about purchasing or using products or services based on the displayed value information. For example, they might decide, "This electronic device has an average price of 50,000 yen and a review rating of 4.5 / 5, so it's worth buying."

[1256] Through the above steps, the system of the present invention can provide users with highly reliable and fair value information and support efficient decision-making.

[1257] Example 1

[1258] 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."

[1259] Conventional systems face challenges in consistently collecting data on products, services, or location information from a variety of sources and assessing its value, making it difficult for users to make accurate and fair judgments. In particular, they face challenges in ensuring the reliability and quality of data, and in lacking algorithms for calculating value using appropriate indicators based on collected data. Furthermore, they lack the functionality to quickly and accurately provide value information in response to user requests.

[1260] 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.

[1261] In this invention, the server includes means for collecting information on products, services, or location information from various information sources, means for storing the collected information in a database and performing preprocessing, means for executing an algorithm for calculating statistical value based on multiple indicators, means for receiving information requests from users and returning value information, and means for displaying the value information on user terminals, thereby enabling users to quickly obtain highly reliable value information and make accurate and fair decisions.

[1262] "Diverse sources" refers to multiple data providers that provide data about products, services, or locations.

[1263] "Product" refers to an individual or set of goods or consumer goods sold in a particular market.

[1264] "Service" refers to a transaction related to the provision of a particular activity or functionality.

[1265] "Location information" is data that indicates a geographical location, and includes coordinates and address information of a specific location.

[1266] "Means of collecting information" refers to a system configuration that automatically obtains data using APIs or web scraping tools.

[1267] "Database" means an electronic storage system that organizes and stores collected information so that it can be efficiently retrieved and used at a later time.

[1268] "Preprocessing means" refers to processing to improve the quality of collected data using methods such as data cleaning and data normalization.

[1269] "Multiple metrics" refers to different metrics or calculation methods for assessing and analyzing data characteristics and trends. Examples include mean, median, standard deviation, etc.

[1270] "Statistical value calculation algorithm" refers to a mathematical method or computational model that analyzes collected data and provides an objective value assessment.

[1271] "Means for receiving an information request and returning value information" refers to the process of searching a database in response to an inquiry from a user and returning the relevant information to the user.

[1272] "User Device" means an electronic device used by a User to enter information requests and view returned information. Examples include smartphones, tablets, and personal computers.

[1273] The present invention relates to a system that calculates the fair and equitable value of products, services, or location information based on data about the products, services, or locations that users obtain from various sources. This system consists of three components: a server, a terminal, and a user.

[1274] System Overview

[1275] server

[1276] The server collects data from various sources via the internet. Specific software used for this includes APIs and web scraping tools. For example, an API is used to obtain pricing information from online stores, and a web scraping tool is used to collect ratings from review sites. The collected data is stored in a database such as MySQL. The server then performs data cleaning to remove outliers and invalid data and improve data quality. Furthermore, the server calculates the mean, median, and standard deviation of the price information and runs algorithms that combine review rating points to calculate the value of the product, service, and location information.

[1277] Terminal

[1278] The terminal has the function of receiving information requests from users and sending those requests to a server. Specific examples of terminals include smartphones, tablets, and PCs. When a user inputs a request through the terminal, the request is sent to the server as an HTTP request. The value information returned from the server is displayed to the user by the terminal. The displayed content is diverse and includes, for example, "average product price," "review rating," and "ranking."

[1279] User

[1280] When a user wants to know the value of a particular product, service, or location, they use their device to request that information. An example of a request might be, "What is the market value of this electronic device?" They send a request and use the returned value information to make a purchasing decision on the product or service.

[1281] Specific examples

[1282] For example, if a user wants to know the value of an iPhone 13,

[1283] 1. A user uses their smartphone to enter a request such as, "I want to know the value of my iPhone 13."

[1284] 2. The device sends the request to the server. The request format will be something like "Product name: iPhone 13."

[1285] 3. The server collects price information and evaluation data related to the iPhone 13 from online stores (e.g., Amazon and Rakuten) and review sites (e.g., Kakaku.com) and stores it in a database.

[1286] 4. The server performs data cleaning to remove unreliable data and outliers.

[1287] 5. The server runs a value calculation algorithm and calculates the value of the iPhone 13 by combining the average price, median price, standard deviation, and review rating points. For example, the result is "average price is 100,000 yen, and review rating is 4.8 / 5."

[1288] 6. The server returns the calculated value information to the terminal.

[1289] 7. The terminal displays the received value information to the user, who then decides whether or not to make a purchase based on that information.

[1290] This system allows users to efficiently obtain highly reliable value information and make fair and impartial decisions.

[1291] Prompt Sentence Examples

[1292] "I'd like to know the market value of this electronic device. I'd like the market value calculated based on online store pricing, reviews, and related data."

[1293] This system's series of processes allows users to quickly obtain highly reliable value information from a vast number of information sources, enabling them to make more accurate decisions regarding purchases and usage.

[1294] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1295] Processing Steps

[1296] Step 1:

[1297] A server collects data about products, services, or locations from various sources. Specific tools used for collection include APIs and web scraping tools. For example, an online store's API can be called to obtain price information, and a web scraping tool can be used to collect rating data from review sites. The source's URL and API key are used as input, and the collected raw data is obtained as output.

[1298] Step 2:

[1299] The server stores the collected data in a database. For this, a database management system such as MySQL or PostgreSQL is used. Before storing it in the database, the data structure is unified and duplicate data is removed. Raw data is given as input, and cleaned data is stored in the database as output.

[1300] Step 3:

[1301] The server performs data cleaning on the stored data. This includes removing invalid data and outliers, and filling in missing data. Specifically, if the price of a certain product is extremely high or low, the data is removed. Missing values ​​are also filled in with the mean or median. The data stored in the database is given as input, and cleaned data is obtained as output.

[1302] Step 4:

[1303] The server runs an algorithm that calculates statistical value based on multiple indicators. It calculates the average, median, and standard deviation of price information and integrates review evaluation points. For example, it calculates the overall value by taking the average price information of a specific product and weighting it with the evaluation points from review sites. Cleaned data is given as input, and value information is obtained as output.

[1304] Step 5:

[1305] A user uses a device to input a request to find out the value of a particular product or service. For example, they might type "Find out the value of an iPhone 13" on their smartphone. The user's request is given as input, and the request is sent from the device to the server as output.

[1306] Step 6:

[1307] The server receives a request from the terminal and searches the database for value information on the corresponding product or service. The user request is given as input, and the corresponding value information is obtained from the server as output.

[1308] Step 7:

[1309] The server formats the acquired value information and returns it to the terminal. For example, detailed value information including the average price, median price, standard deviation price, review evaluation points, etc. is formatted. The acquired value information is given as input, and the formatted value information is returned to the terminal as output.

[1310] Step 8:

[1311] The terminal displays the received value information to the user. For example, for a specific electronic device, information such as "average price is 100,000 yen, and review rating is 4.8 / 5" is displayed. The value information returned from the server is given as input, and the specific value information is displayed on the user's screen as output.

[1312] Through this series of processing steps, the user can efficiently obtain highly reliable value information and make a fair and impartial decision.

[1313] (Application example 1)

[1314] 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."

[1315] Today's users face difficulties in accurately and quickly grasping the value of products and services obtained from a variety of information sources. It also takes a great deal of time and effort to find reliable data from the vast amount of information and to make a fair and impartial value assessment. Furthermore, when selecting a product or service, users are required to comprehensively evaluate multiple indicators, such as price and reviews, but this is not easy to achieve. A system that solves these problems is needed.

[1316] 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.

[1317] In this invention, the server includes means for collecting data on products, services, or location information from various data sources, means for storing the collected data in a database and performing preprocessing, means for executing an algorithm for calculating statistical value based on multiple indicators, means for receiving information requests on products or services from a user's terminal, generating value information based on the request, and returning the value information to the user's terminal, and means for triggering data collection using the barcode or name of the product or service. This enables users to quickly and efficiently perform reliable, fair, and impartial value assessments based on data obtained from various information sources.

[1318] - "Diverse data sources" refers to the means of obtaining data from various information providers on the Internet, APIs, web scraping tools, etc.

[1319] "Products" refers to physical and digital goods sold in the Marketplace.

[1320] "Services" include any activities, functions, or skills provided for a fee or free of charge.

[1321] "Location Information" refers to data relating to a geographic location or position.

[1322] A "database" is a system for efficiently storing, managing, and retrieving collected data.

[1323] "Preprocessing" refers to data quality improvement measures including data cleaning, normalization, and conversion to another format.

[1324] "Statistical value" refers to the overall evaluation of the data calculated based on the mean, median, standard deviation, and other statistical indicators.

[1325] An "algorithm" refers to a set of procedures or formulas for performing a particular calculation or operation.

[1326] "User terminal" includes devices used by users, such as smartphones, tablets, and personal computers.

[1327] An "information request" refers to an operation in which a user requests specific information through a terminal.

[1328] "Value information" refers to the evaluation results of products, services, or location information analyzed based on collected data.

[1329] A "barcode" is a visual representation of a unique sequence of numbers and / or letters used to identify a product.

[1330] "Name" means a unique word or phrase used to identify a particular product or service.

[1331] The present invention relates to a system that calculates the fair and equitable value of products, services, or location information based on data about the products, services, or location information that a user obtains from various information sources. The system is composed of components including a server, a terminal, and a user. Specific embodiments are described below.

[1332] System Overview

[1333] server

[1334] The server collects data about products, services, or location information from various data sources via the Internet. Data sources include online stores, review sites, and map services. The collected data is stored in a database, and data cleaning is performed to remove outliers and invalid data. The server also runs an algorithm that calculates statistical value using multiple indicators based on the collected data. This algorithm calculates the average, median, and standard deviation of price information and calculates the value of the product or service by integrating review evaluation points.

[1335] Terminal

[1336] The terminal receives an information request from the user and sends the request to the server. The request includes the name of the product or service and a barcode. It has the function of displaying the value information returned from the server. Specifically, a mobile device such as a smartphone or tablet is used as the terminal. The user can easily check fair and impartial value information through the terminal.

[1337] User

[1338] A user wants to know the value of a product, service, or location information, so they use their device to make an information request. Based on the returned value information, they can make a decision to purchase or use the product or service. For example, if a user wants to know the value of a certain electronic device, they can use their smartphone to enter the name or barcode of the electronic device and obtain the value information from the server.

[1339] Program processing

[1340] This program mainly handles the following processes: data collection, data cleaning, value calculation, and user request processing.

[1341] Hardware and software used

[1342] Hardware: User devices such as smartphones, tablets, and PCs

[1343] Software: Programming languages ​​and libraries such as Python, requests, statistics, numpy, etc. APIs used include online store APIs and review site APIs.

[1344] Specific examples

[1345] For example, if a user wants to know the value of an "iPhone 13," they open their smartphone and enter "iPhone 13" as the product name. The device sends this request to the server. The server collects price information and review ratings from online stores and review sites and stores them in a database. It performs data cleaning to remove outliers and invalid data, and calculates the value by combining the mean, median, standard deviation, and review rating points of the price information. The server sends the calculated value information back to the device, and the device displays the received value information to the user.

[1346] Prompt Sentence Examples

[1347] The user can use prompts such as:

[1348] "What is the value of the iPhone 13? I'd like to know a fair and impartial value based on price information and review ratings."

[1349] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1350] Step 1: Data collection

[1351] Based on the product or service name or barcode specified by the user, the server collects relevant data using online store APIs or review site APIs. Information obtained from data sources includes price information, review ratings, location information, etc. The input of this step is the user request, and the output is the collected raw data.

[1352] Step 2: Data storage and preprocessing

[1353] The server stores the collected raw data in a database and performs preprocessing, which includes data cleaning to remove outliers and invalid data. The input of this step is the collected raw data, and the output is a clean dataset.

[1354] Step 3: Data cleaning

[1355] The server runs a data cleaning process on the stored data to remove outliers and incorrect data, which may include, for example, removing unusually high or low prices. The input to this step is the stored raw data, and the output is the cleaned data.

[1356] Step 4: Value calculation

[1357] The server runs an algorithm to calculate statistical value based on the cleaned data. Specifically, it calculates the mean, median, and standard deviation of the price information and integrates the review rating points. The input of this step is the cleaned data, and the output is the calculated value information.

[1358] Step 5: User Request Processing

[1359] The terminal receives an information request from the user and sends that information to the server. The user inputs a product name or barcode, and the terminal sends that data to the server as a request. The input of this step is the user's request, and the output is the request sent to the server.

[1360] Step 6: Retrieving data based on the request

[1361] The server searches for and acquires the corresponding license information from the database based on the request received from the terminal. The input to this step is the request from the terminal, and the output is the acquired license information.

[1362] Step 7: Return and display of value information

[1363] The server returns the acquired value information to the terminal, which then displays it to the user. This allows the user to check information such as the average price, median, standard deviation, and review rating of the product or service. The input to this step is the value information from the server, and the output is the information displayed to the user.

[1364] 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.

[1365] ---

[1366] This invention combines a system that calculates the fair and equitable value of products, services, or location data obtained by users from various sources with an emotion engine that recognizes and analyzes user emotions. This system is composed of the following components: a server, a terminal, a user, and the emotion engine. A specific embodiment is shown below.

[1367] System Overview

[1368] server

[1369] The server collects data related to products, services, or location information from various data sources via the Internet. The collected data is stored in a database, and data cleaning is performed to remove outliers and invalid data. The server then runs an algorithm to calculate statistical value using multiple indicators based on the collected data and sentiment data.

[1370] Terminal

[1371] The device receives information requests and emotion information from the user and sends the requests to the server. It also has the function of displaying the value information returned from the server. The user can easily check the fair and just value information through the device.

[1372] User

[1373] When a user wants to know the value of a product, service, or location, they use their device to make an information request and express their emotions through facial expressions, voice, or text, which are then analyzed by the emotion engine.

[1374] Emotion Engine

[1375] The emotion engine recognizes emotions from the user's facial expressions, voice, or text and stores them in a database. The server then applies this emotion data to a value calculation algorithm to provide personalized value information corresponding to the user's emotions.

[1376] Program processing overview

[1377] 1. Data Collection

[1378] The server collects the necessary information from multiple data sources, such as online stores, review sites, and map services, and stores it in a database.

[1379] 2. Data storage and preprocessing

[1380] The server stores the collected data in a database and performs data cleaning to remove outliers and invalid data.

[1381] 3. Collecting Emotional Data

[1382] The terminal acquires data for recognizing emotions through the user's facial expressions, voice, or text, and sends it to the emotion engine.

[1383] 4. Sentiment analysis

[1384] The emotion engine analyzes the collected facial, voice, or text data to recognize the user's emotions, and the recognized emotion data is stored in a database.

[1385] 5. Value Calculation Algorithm

[1386] The server runs a value calculation algorithm based on the cleaned data and sentiment data, and calculates the overall value by integrating the average, median, and standard deviation of the price and review rating points.

[1387] 6. User Request Processing

[1388] The terminal receives a request from the user and transmits the request and the user's emotion data to the server.

[1389] 7. Obtaining and returning value information

[1390] The server receives the request, retrieves value information for the requested product, service, or location information from a database, and returns it to the terminal.

[1391] 8. Display of Value Information

[1392] The terminal displays the value information received from the server to the user, allowing the user to easily confirm that the value information is fair and impartial.

[1393] Specific examples

[1394] For example, if a user wants to know the value of a certain cafe,

[1395] 1. A user uses a smartphone to input a request to find out the value of a cafe.

[1396] 2. The device sends the request to the server.

[1397] 3. At the same time, the user looks at photos of the cafe and reads reviews, and the device sends the user's facial expressions and voice to the emotion engine.

[1398] 4. The emotion engine analyzes the user's emotions from their facial expressions and voice, and stores the emotion data in a database.

[1399] 5. The server collects price information and rating data related to the cafe from online stores, review sites, map services, etc. and stores it in a database.

[1400] 6. The server performs data cleaning to remove outliers and unreliable data.

[1401] 7. The server runs a value calculation algorithm and calculates the cafe's value by integrating the average, median, and standard deviation of the prices, review rating points, and sentiment data.

[1402] 8. The server returns the calculated value information to the terminal.

[1403] 9. The terminal displays the received value information to the user, who then decides whether to visit the cafe based on that information and their own feelings.

[1404] In such an embodiment, the system of the present invention can provide users with highly reliable and fair value information, and by incorporating emotional elements, can efficiently provide more personalized information.

[1405] The processing flow will be explained below.

[1406] ---

[1407] Step 1:

[1408] A server collects data about products, services, or location information from multiple data sources via the Internet, specifically, using APIs of online stores to obtain price information and reviews, and APIs of map services to obtain location information and user ratings.

[1409] Step 2:

[1410] The server stores the collected data in a central database, including pricing information, reviews, and location information.

[1411] Step 3:

[1412] The server performs data cleaning to remove outliers and fraudulent data from the stored data, filtering out price anomalies and unreliable reviews.

[1413] Step 4:

[1414] The terminal receives the user's information request and sends the request to the server. For example, the user might type, "I want to know the value of a particular cafe," and the terminal sends the information to the server.

[1415] Step 5:

[1416] The device captures the user's facial expressions, voice, or entered text and sends that information to the emotion engine, using a camera, microphone, or text input.

[1417] Step 6:

[1418] The emotion engine analyzes the user's facial expressions and voice / text data to recognize the user's emotions. For example, if the user is smiling, it will determine that the user is feeling "joy" and generate emotion data.

[1419] Step 7:

[1420] The emotion engine stores the recognized emotion data in a central database, which is then used in the value calculation algorithm.

[1421] Step 8:

[1422] The server runs a value calculation algorithm based on the stored cleaning data and sentiment data, integrating the average, median, and standard deviation of price information, review evaluation points, and sentiment data to calculate the overall value.

[1423] Step 9:

[1424] The server then returns the calculated value information to the device, including average prices, review ratings, rankings, and sentiment-based recommendations.

[1425] Step 10:

[1426] The device displays the received value information to the user. For example, it may display information such as, "This cafe has an average rating of 4.5 / 5, a price range of ¥800 - ¥1200, and user emotional data indicates a very high level of satisfaction."

[1427] Step 11:

[1428] The user makes a decision about purchasing or using a product or service based on the displayed value information and emotional data. For example, they might decide, "This cafe has high ratings and many positive emotional reviews, so it's worth visiting."

[1429] In this way, by having the server, terminal, and emotion engine work in cooperation, the system of the present invention can provide users with highly reliable and fair value information, and can also efficiently provide personalized information that takes emotional elements into account.

[1430] Example 2

[1431] 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."

[1432] Conventional systems cannot take user emotions into account when calculating statistical values ​​based on information obtained from various data sources, making it difficult to provide personalized value information for individual users. Furthermore, inaccurate or invalid data can significantly affect value calculations, reducing reliability. Therefore, there is a need for a method to provide accurate and reliable value information that incorporates user emotions.

[1433] 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.

[1434] In this invention, the server includes means for collecting data on products, services, or location information from various information sources, means for storing the collected data in a database and performing data cleaning and preprocessing, means for acquiring emotional data from a user's facial expressions, voice, or text, means for analyzing the collected emotional data and recognizing emotions, means for executing a statistical value calculation algorithm based on the cleaned data and emotional data, and means for receiving information requests from users and returning value information, thereby enabling the provision of accurate and personalized value information that takes user emotions into consideration.

[1435] "Diverse sources" refers to multiple types of data providers accessible via the Internet, such as online stores, review sites, and map services.

[1436] "Product, Service, or Location Information" means information about goods, services offered, and particular geographic locations that may be of interest to a user.

[1437] "Data collection means" refers to the combination of software and hardware used to obtain the required data from various sources via the Internet.

[1438] A "database" is a structured data storage system for storing, retrieving, and manipulating collected data.

[1439] "Means for performing data cleaning" refers to the process of removing outliers and incorrect data from collected data to improve the integrity and reliability of the data.

[1440] "Pre-processing means" refers to a series of processes that prepare the collected data in a format that can be used by the value calculation algorithm.

[1441] "Means for acquiring emotional data" refers to devices such as cameras, microphones, and text input devices for collecting the user's facial expressions, voice, or text data, as well as software for controlling them.

[1442] "Means for analyzing emotional data" refers to a machine learning model and its execution environment for processing collected emotional data and recognizing user emotions.

[1443] A "value calculation algorithm" is a set of calculation methods that calculates statistical values ​​based on collected data and analyzed emotional data.

[1444] "Means for receiving information requests" refers to a combination of software and hardware for receiving requests for information from users.

[1445] The "means for returning value information" refers to a combination of software and hardware for transmitting the calculated value information to the user's terminal and displaying it.

[1446] This invention combines a system that calculates the fair and equitable value of products, services, or location data obtained by users from various sources with an emotion engine that recognizes and analyzes user emotions. The system is composed of the following components: a server, a terminal, a user, and an emotion engine.

[1447] Server Configuration

[1448] The server collects data about products, services, or location information from various data sources via the Internet. Specifically, the server collects data from online stores, review sites, map services, etc., and stores it in a database. It also includes a process for performing data cleaning to remove outliers and fraudulent data. The data stored in the database is then used to run value calculation algorithms based on statistical indicators such as the average, median, and standard deviation of prices, and review rating points, using data analysis programming languages ​​such as Python and R.

[1449] Device configuration

[1450] The terminal is responsible for receiving information requests and emotional information from the user. The terminal is a device such as a smartphone or tablet that captures the user's facial expressions and voice through a camera and microphone and sends the user's request to the server. It also has the function of displaying the value information returned by the server. For example, if a user inputs a request into the terminal such as "Please tell me the current rating and average price of XX cafe," the request is sent to the server.

[1451] User Roles

[1452] When a user wants to know the value of a product, service, or location information, they use their device to make an information request. The user expresses their emotions through facial expressions, voice, or text, and the device sends the information to the emotion engine for emotional analysis. The emotional data collected in this way is sent to the server and reflected in the value calculation algorithm.

[1453] Emotion engine configuration

[1454] The emotion engine is responsible for recognizing emotions from the user's facial expressions, voice, or text and storing them in a database. The emotion engine uses a machine learning model (e.g., a generative AI model) to classify the user's emotions into categories such as positive, negative, or surprise. The server then feeds this emotion data into a value calculation algorithm to provide personalized value information corresponding to the user's emotions.

[1455] Specific examples

[1456] If a user wants to know the value of a certain cafe, the specific process is as follows:

[1457] 1. The user uses their smartphone to input a request to find out the value of a certain cafe. Example: "I want to know the rating and current average price of a certain cafe."

[1458] 2. The device sends the request to the server.

[1459] 3. At the same time, the user looks at photos of the cafe and reads reviews, and the device sends the user's facial expressions and voice to the emotion engine.

[1460] 4. The emotion engine analyzes the user's emotions from their facial expressions and voice, and stores the emotion data in a database.

[1461] 5. The server collects price information and rating data related to the cafe from online stores, review sites, map services, etc. and stores it in a database.

[1462] 6. The server performs data cleaning to remove outliers and unreliable data.

[1463] 7. The server runs a value calculation algorithm and calculates the cafe's value by integrating the average, median, and standard deviation of the prices, review rating points, and sentiment data.

[1464] 8. The server returns the calculated value information to the terminal.

[1465] 9. The terminal displays the received value information to the user, who then decides whether to visit the cafe based on that information and their own feelings.

[1466] This concludes the description of the embodiment of the present invention. This system provides users with highly reliable and fair value information, and by incorporating emotional elements, it efficiently provides more personalized information.

[1467] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1468] Processing step details

[1469] Step 1: Data collection

[1470] The server collects data about products, services, or location information from various data sources (e.g., online stores, review sites, map services) over the Internet.

[1471] Input: Your server configured API endpoint or web scraping script.

[1472] Processing: Sending API requests or scraping data from web pages.

[1473] Output: The retrieved data (e.g., price information, review ratings, location information).

[1474] Specific operation: The server periodically accesses each data source, collects information, and stores it in a database.

[1475] Step 2: Data storage and preprocessing

[1476] The server stores the collected data in a database and performs data cleaning to remove outliers and invalid data.

[1477] Input: The data collected in Step 1.

[1478] Processing: Inserting data into the database, checking data integrity and removing outliers using SQL queries and ETL processes.

[1479] Output: A clean and reliable dataset.

[1480] Specific operation: The server automates data preprocessing using an ETL tool (e.g., Apache NiFi, Talend).

[1481] Step 3: Collecting emotion data

[1482] The terminal acquires emotion data through the user's facial expressions, voice, or text, and transmits it to the emotion engine.

[1483] Input: User facial expression, voice, and text data.

[1484] Processing: Data capture from cameras and microphones and real-time processing of that data.

[1485] Output: Sentiment data for analysis.

[1486] Specific operation: The device captures the user's emotions using sensor devices (camera, microphone) equipped on the device and transmits the data via Wi-Fi or Bluetooth.

[1487] Step 4: Sentiment analysis

[1488] The emotion engine analyzes collected facial, voice, or text data to recognize the user's emotions.

[1489] Input: The emotion data collected in step 3.

[1490] Processing: Sentiment analysis using machine learning models (e.g., generative AI models).

[1491] Output: User's emotion category (e.g. positive, negative, surprised).

[1492] How it works: The emotion engine uses machine learning libraries (e.g., TensorFlow, PyTorch) to perform real-time analysis of data.

[1493] Step 5: Value calculation algorithm

[1494] The server runs a value calculation algorithm based on the cleaned data and emotion data.

[1495] Input: The clean dataset (Step 2) and the parsed sentiment data (Step 4).

[1496] Processing: Calculation and synthesis of statistical indicators using data analysis tools.

[1497] Output: Final value information (e.g. price mean, median, standard deviation, review rating points).

[1498] Specific operation: The server uses data analysis tools such as Pandas, NumPy, and Scikit-learn to calculate value based on the most recent data.

[1499] Step 6: User Request Processing

[1500] The terminal receives a request from the user and transmits the request and the user's emotion data to the server.

[1501] Input: User request (e.g., "I want to know the rating and current average price of XX Cafe").

[1502] Processing: Formatting and sending request information.

[1503] Output: Request sent to the server.

[1504] Specific operation: The device enters a request into a form and sends it to the server via an HTTP request or WebSocket.

[1505] Step 7: Obtaining and returning value information

[1506] The server receives the request, retrieves value information for the requested product, service, or location information from a database, and returns it to the terminal.

[1507] Input: User requests and data stored in the server.

[1508] Processing: Data extraction using SQL queries and data formatting.

[1509] Output: Value information data in JSON format.

[1510] Specific operation: The server extracts the necessary data using an SQL query, converts it into JSON format, and sends it to the terminal.

[1511] Step 8: Viewing Value Information

[1512] The terminal displays the value information received from the server to the user.

[1513] Input: Value information returned by the server.

[1514] Processing: Formatting and displaying value information.

[1515] Output: Visually display data to the user.

[1516] Specific operation: The terminal formats and displays the received data on the application screen, displaying it in graphs and text so that it is easy for the user to understand.

[1517] The above is the specific processing flow of this system.

[1518] (Application example 2)

[1519] 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."

[1520] Conventional value calculation systems calculate value solely based on price and review ratings, without taking into account the user's subjective feelings or purchasing intent. This makes it difficult to provide users with optimal information for their actual purchasing experience. Furthermore, users have few clues to determine whether the value information matches their own feelings and preferences. To solve this problem, a system is needed that integrates user emotional data and provides more personalized value information.

[1521] 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.

[1522] In this invention, the server includes means for collecting data on products, services, or location information from various data sources, means for storing the collected data in a database and performing preprocessing, means for executing an algorithm for calculating statistical value based on multiple indicators, means for receiving information requests from users and returning value information, means for acquiring emotional data from the user's facial expressions or voice using a camera function, means for adjusting parameters in the value calculation algorithm based on the acquired emotional data, and means for integrating the emotional data and the value information and displaying it to the user. This makes it possible to provide more personalized value information in real time that takes into account the user's subjective emotions.

[1523] "Data Source" means an information source on the Internet that provides product, service, or location data in a variety of formats.

[1524] A "database" is a structured information storage system for storing and managing collected data.

[1525] "Preprocessing" refers to processes such as data cleaning, filtering, and normalization that are carried out to improve the quality of collected data.

[1526] An "algorithm" is a series of calculation procedures for calculating statistical value based on multiple indicators.

[1527] An "information request" is a user's request to the system for value information about a product, service, or location.

[1528] "Value information" is information provided to users based on collected data and calculated statistical values.

[1529] "Camera function" refers to the function of a device to capture images or video.

[1530] "Emotion data" is information about emotions acquired from the user's facial expressions and voice and analyzed by the emotion engine.

[1531] A "parameter" is a variable used in calculations or adjustments in a value calculation algorithm.

[1532] An "emotion engine" is software or hardware that recognizes emotions from a user's facial expressions and voice and analyzes them as data.

[1533] An embodiment of the present invention is a system for enhancing the shopping experience, particularly in brick-and-mortar stores, by allowing users to scan products with their smartphones and collect real-time emotional data to provide personalized value information.

[1534] Program processing

[1535] Server Processing

[1536] The server collects data about products, services, or locations from various data sources, including online stores, review sites, and map services. The collected data is stored in a database and cleaned to remove outliers and invalid data. The server then runs an algorithm to calculate statistical value based on multiple indicators (such as the average price, median price, standard deviation, and review rating points). It also adjusts the parameters of the value calculation algorithm based on user sentiment data, which is reflected in the value information.

[1537] Terminal handling

[1538] When a user uses their smartphone to scan a product, a request for information about that product is sent to the server. At the same time, the smartphone's camera captures the user's facial expressions and voice, and sends the emotional data to the emotion engine. This emotional data is analyzed in real time, and the results are sent to the server. The value information returned from the server is displayed on the device, and the user makes a purchasing decision based on that information.

[1539] User Action

[1540] Users scan products in stores using their smartphones. This scan acquires product price and rating information, while the camera captures the user's facial expressions and voice. This allows the user's emotional data to be collected in real time and analyzed by the emotion engine. The analyzed emotional data is sent to a server and presented to the user as integrated value information.

[1541] Hardware and software used

[1542] Smartphone: Uses camera and network communication functions to capture the user's facial expressions and transmit emotional data.

[1543] Server: Collects data from various data sources, stores it in a database, cleans the data, and executes value calculation algorithms.

[1544] Database: Stores and manages collected data and emotion data.

[1545] Emotion Engine: Uses OpenCV and TensorFlow / Keras to recognize and analyze emotions from the user's facial expressions and voice.

[1546] Specific examples

[1547] For example, if a user scans a particular cafe product in a store, the following steps occur:

[1548] 1. A user uses a smartphone to scan a product in a cafe, and the smartphone camera captures the user's facial expressions and voice.

[1549] 2. The smartphone sends the captured emotion data to the emotion engine at the same time as requesting product information.

[1550] 3. The emotion engine analyzes the emotion data and sends the results to the server.

[1551] 4. The server retrieves product data from the database, performs data cleaning, and runs a value calculation algorithm based on the analyzed sentiment data to calculate the final value information.

[1552] 5. The terminal displays the value information sent from the server to the user, who then decides whether to purchase the cafe product based on this information.

[1553] Prompt Sentence Examples

[1554] Below are some example prompts to use in the emotion engine as input to the generative AI model.

[1555] text

[1556] Facial image: Image data path

[1557] Expected emotions: happy, anxious, sad, surprised, angry, neutral, disgust

[1558] This specific structure enables the system of the invention to provide more personalized value information that takes into account the user's emotions.

[1559] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1560] Step 1:

[1561] A user uses a smartphone to scan a product in a store. The input data is the scanned barcode or QR code of the product, and the smartphone camera captures the user's facial expressions and voice. The output is a product information request and captured emotion data.

[1562] Step 2:

[1563] The terminal sends a product information request and captured emotion data to the server. The input data are the product scan results and the user's emotion data, which are sent to the server. The output is the request and emotion data received by the server.

[1564] Step 3:

[1565] The server collects data about products, services, or locations from various data sources. The input data is information collected from online stores, review sites, map services, etc., and the output is the collected product data.

[1566] Step 4:

[1567] The server stores the collected data in a database and performs preprocessing. The input data is the collected product data, and the output is the data after preprocessing. This preprocessing includes data cleaning (removal of outliers and invalid data).

[1568] Step 5:

[1569] The server uses an emotion engine to analyze emotion data from the user's facial expressions and voice. The input data is the user's facial image and voice data, and the output is the type and intensity of the analyzed emotion. This analysis uses a facial recognition model and an emotion analysis model.

[1570] Step 6:

[1571] The server runs an algorithm that uses multiple indicators to calculate statistical value based on the collected data and analyzed sentiment data. The input data is preprocessed product data and analyzed sentiment data, and the output is statistical value information. The algorithm includes the average, median, and standard deviation of price, as well as review rating points.

[1572] Step 7:

[1573] The server returns the calculated value information to the terminal. The input data is statistical value information, and the output is value information received by the user's terminal.

[1574] Step 8:

[1575] The terminal displays the received value information to the user. The input data is the value information sent from the server, and the output is information that the user can visually confirm. Based on this, the user can decide whether or not to purchase the product.

[1576] These steps enable the system of the present invention to provide more personalized value information in real time, taking into account the user's emotions.

[1577] 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.

[1578] 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.

[1579] 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.

[1580] 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.

[1581] 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.

[1582] 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.

[1583] 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).

[1584] 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.

[1585] 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."

[1586] 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.

[1587] 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).

[1588] 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.

[1589] 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.

[1590] 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.

[1591] 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.

[1592] 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.

[1593] 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.

[1594] 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.

[1595] 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.

[1596] 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.

[1597] 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.

[1598] The following is further disclosed regarding the above embodiment.

[1599] (Claim 1)

[1600] A means of collecting product, service or location data from a variety of data sources;

[1601] A means for storing the collected data in a database and preprocessing the data;

[1602] A means for executing an algorithm that calculates a statistical value based on multiple indicators;

[1603] means for receiving an information request from a user and returning value information;

[1604] A system including:

[1605] (Claim 2)

[1606] 10. The system of claim 1, further comprising means for performing data cleaning to remove outliers and incorrect data.

[1607] (Claim 3)

[1608] 10. The system of claim 1, further comprising means for calculating a mean, median, and standard deviation of the collected price information and integrating review rating points to calculate value.

[1609] "Example 1"

[1610] (Claim 1)

[1611] A means of collecting information about products, services, or location information from a variety of sources;

[1612] a means for storing the collected information in a database and pre-processing the information;

[1613] A means for executing an algorithm that calculates a statistical value based on multiple indicators;

[1614] means for receiving an information request from a user and returning value information;

[1615] a means for displaying value information on a user terminal;

[1616] A system including:

[1617] (Claim 2)

[1618] 10. The system of claim 1, further comprising means for performing data cleaning to remove outliers and false information.

[1619] (Claim 3)

[1620] 10. The system of claim 1, further comprising means for calculating a mean, median, and standard deviation of the collected price information and integrating review rating points to calculate value.

[1621] "Application Example 1"

[1622] (Claim 1)

[1623] A means of collecting product, service or location data from a variety of data sources;

[1624] A means for storing the collected data in a database and preprocessing the data;

[1625] A means for executing an algorithm that calculates a statistical value based on multiple indicators;

[1626] means for receiving an information request for a product or service from a user terminal, generating value information based on the request, and returning the value information to the user terminal;

[1627] A means for triggering data collection using the barcode or name of the product or service;

[1628] A system including:

[1629] (Claim 2)

[1630] 10. The system of claim 1, further comprising means for performing data cleaning to remove outliers and incorrect data.

[1631] (Claim 3)

[1632] 10. The system of claim 1, further comprising means for calculating a mean, median, and standard deviation of the collected price information and integrating review rating points to calculate value.

[1633] "Example 2: Combining Emotion Engines"

[1634] (Claim 1)

[1635] A means of collecting product, service, or location-related data from a variety of sources;

[1636] A means for storing the collected data in a database and performing data cleaning and preprocessing;

[1637] A means for acquiring emotion data through a user's facial expression, voice, or text;

[1638] a means for analyzing the collected emotion data and recognizing emotions;

[1639] a means for executing a statistical value calculation algorithm based on the cleaned data and the sentiment data;

[1640] means for receiving an information request from a user and returning value information;

[1641] A system including:

[1642] (Claim 2)

[1643] 10. The system of claim 1, further comprising a data cleaning means for removing outliers and incorrect data.

[1644] (Claim 3)

[1645] 10. The system of claim 1, further comprising means for calculating a mean, median, and standard deviation of the collected price information and integrating review rating points to calculate value.

[1646] That's all.

[1647] "Application example 2 when combining emotion engines"

[1648] (Claim 1)

[1649] A means of collecting product, service or location data from a variety of data sources;

[1650] A means for storing the collected data in a database and preprocessing the data;

[1651] A means for executing an algorithm that calculates a statistical value based on multiple indicators;

[1652] means for receiving an information request from a user and returning value information;

[1653] A means for acquiring emotion data from a user's facial expression or voice using a camera function;

[1654] A means for adjusting parameters in a value calculation algorithm based on the acquired emotion data;

[1655] a means for integrating the emotion data and the value information and displaying the integrated data to a user;

[1656] A system including:

[1657] (Claim 2)

[1658] 10. The system of claim 1, further comprising means for performing data cleaning to remove outliers and incorrect data.

[1659] (Claim 3)

[1660] 10. The system of claim 1, further comprising means for calculating a mean, median, and standard deviation of the collected price information and integrating review rating points to calculate value.

[1661] (Claim 4)

[1662] 10. The system of claim 1, further comprising means for using an emotion engine to analyze the collected facial or voice data and recognize the emotion of the user.

[1663] (Claim 5)

[1664] 10. The system of claim 1, further comprising means for inferring emotions in real time using a facial recognition model and an emotion analysis model. [Explanation of symbols]

[1665] 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 of collecting product, service or location data from a variety of data sources; A means for storing the collected data in a database and preprocessing the data; A means for executing an algorithm that calculates a statistical value based on multiple indicators; means for receiving an information request from a user and returning value information; A system including:

2. The system of claim 1 , further comprising means for performing data cleaning to remove outliers and incorrect data.

3. The system of claim 1 , further comprising means for calculating the mean, median, and standard deviation of the collected price information and integrating review rating points to calculate value.

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