system

Abstract

We provide the system. [Solution] A communication means for receiving user input conditions, Information processing means for acquiring and analyzing wine data based on the said conditions, A system including a display mechanism that presents wine options to the user based on the analysis results.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] When choosing wine, it is not easy for beginners or people who are not very familiar with it to find a wine suitable for themselves from numerous options. Also, there is a problem that the choice is difficult because it takes time for the selection and requires expertise. Furthermore, there is a risk of an unexpected experience by purchasing wine without having appropriate judgment criteria.

Means for Solving the Problems

[0005] This invention provides an information processing means that receives input conditions from a user via communication means, and acquires and analyzes wine data based on those conditions. This information processing means enables comprehensive analysis utilizing big data, making it possible to present wine candidates suitable for each individual user. It also includes means for reserving or purchasing wine according to the user's selection, simplifying the purchase process to a one-click level. As a result, even beginners can quickly and easily find the perfect wine, which is expected to improve user satisfaction.

[0006] "User" refers to the end user who uses the system to select wine.

[0007] "Input conditions" refer to the requirements related to wine selection that the user specifies to the system, such as budget, preferences, and intended use.

[0008] "Communication means" refers to interfaces and protocols used to receive input conditions from users and transmit them to servers or information processing devices.

[0009] "Information processing means" refers to a device or system that acquires and analyzes wine data based on received input conditions.

[0010] "Wine data" refers to a dataset containing information about wine, specifically including grape varieties, brands, prices, reviews, and ratings.

[0011] "Analysis" refers to the process of analyzing wine data and selecting the wine that best suits the user's criteria.

[0012] "Display means" refers to an interface used to present wine options and ratings to the user.

[0013] "Candidates" refers to a list of wines that may potentially meet the user's criteria.

[0014] "Reservation or purchase procedure" refers to the process undertaken by a user to obtain the wine they have selected. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0019] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] As shown in Figure 1, the 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.

[0026] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0029] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0035] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0036] This invention is a system designed to support users, especially beginners and those with little experience, in choosing wine. The system allows users to input criteria related to wine, and through data analysis based on those criteria, it presents optimal wine candidates, simplifying the selection and purchase process.

[0037] First, the user accesses the LINE official account using their device and requests wine selection via chat. The device receives the user's input criteria and transmits them to the server via communication. The user can input criteria such as budget, preferences, and purpose, thereby defining their detailed wine preferences.

[0038] The server analyzes the received conditions and generates suitable wine candidates using big data about wine. Specifically, the server communicates with a wine database to obtain the characteristics, reviews, and ratings of wines that match the user's conditions, and uses statistical methods through information processing to create a list of optimal candidates.

[0039] Users can view wine options presented by the server on their devices. Each wine includes detailed information such as grape variety, characteristics, price range, and consumer reviews to help users make the best choice. Users can also select their preferred wine from the presented options and complete the purchase or reservation process on their devices.

[0040] The server quickly processes purchases and reservations based on the user's selection and sends a completion notification to the device. In this way, users can efficiently find wines that meet their individual criteria and proceed smoothly through the purchase process. For example, if a user is looking for a red wine under 3000 yen for a home party, the generating AI will select suitable wines from the database, and the server will analyze the information and present it. The user can then use this information to make a purchase decision.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The user opens the LINE official account and sends a message via their device to begin the wine selection process. Sending this message initiates interaction with the user.

[0044] Step 2:

[0045] The server receives the user's message and sends a message to the terminal in the form of questions to confirm conditions related to wine selection, such as budget, preferences, and intended use.

[0046] Step 3:

[0047] The user enters specific conditions (e.g., "Budget up to 3000 yen, red wine, for a home party") from their device in response to the presented question and sends them to the server.

[0048] Step 4:

[0049] The server records the user's criteria data received and uses a generative AI to access the wine database. It searches for wine candidates that match the criteria and analyzes the results.

[0050] Step 5:

[0051] Based on the data analyzed by the server, the system selects wine candidates that are considered to be the best fit for the user's criteria and creates a candidate list that includes detailed information about those wines.

[0052] Step 6:

[0053] The server sends a list of candidates to the terminal, displaying them to the user as selectable wine options. This list includes information such as the characteristics, price, and rating of each wine.

[0054] Step 7:

[0055] The user selects their preferred wine from the presented wine options and sends their selection to the server via their device.

[0056] Step 8:

[0057] The server will process the wine reservation or purchase based on the user's selection. If necessary, it will also verify payment information and arrange delivery.

[0058] Step 9:

[0059] The server notifies the terminal of the completion of the reservation or purchase process and sends a confirmation message to the user.

[0060] This entire process allows users to find a wine that perfectly matches their criteria and purchase it smoothly.

[0061] (Example 1)

[0062] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0063] Choosing the optimal beverage by considering various factors is not easy. This is especially true for novice or inexperienced consumers, who find the perfect beverage to suit their needs from a vast array of options. Furthermore, there is a lack of readily available means to ensure a quick and smooth purchase process after selection.

[0064] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0065] In this invention, the server includes communication means for receiving user input conditions, information processing means for acquiring and analyzing beverage data based on said conditions, presentation means for presenting beverage candidates to the user based on the analysis results, means for generating candidates using a generative AI model, and means for selecting candidates that match the user's conditions. This enables the user to efficiently select a beverage that meets their criteria and purchase it smoothly.

[0066] A "user" refers to an individual who uses the system to select and purchase beverages.

[0067] "Input conditions" refer to information that indicates the user's specific requirements, such as the price, type, and intended use of the beverage they desire.

[0068] "Communication method" refers to digital communication technology used to send user input conditions to a server and receive analysis results from the server.

[0069] "Beverage data" refers to a database containing information such as characteristics, reviews, and ratings of wine and other beverages.

[0070] "Analysis" refers to the process of scrutinizing beverage data based on input conditions and deriving the optimal candidate.

[0071] "Information processing means" refers to a combination of software and hardware used to perform analysis, integrate input conditions and beverage data, and generate beverage candidates suitable for the user.

[0072] "Presentation method" refers to an interface for displaying analysis results in an easily understandable way to the user.

[0073] A "generative AI model" refers to artificial intelligence technology used to analyze large-scale data and select beverages that are suitable for the input conditions.

[0074] "Candidates" refers to a list of suggested beverages that the user can select based on the input criteria.

[0075] "Selection" refers to the process of choosing the optimal candidate from the analysis results using a generative AI model.

[0076] This invention provides a system that allows users to more easily select and purchase beverages that meet their specific requirements. Users first access the system using a communication terminal and input the desired beverage criteria. For example, a user can input a prompt such as, "Please suggest a sweet red wine under 3000 yen for a home party."

[0077] The terminal receives these input conditions and transmits them to the server via communication means. The server uses information processing means to analyze the received conditions. This means includes a wide range of databases on wine and other beverages, from which the server retrieves relevant information.

[0078] The server then uses a generative AI model to generate beverage candidates that meet the specified criteria. This AI model analyzes beverage data and outputs the most suitable candidates that satisfy the user's input conditions. For example, the database contains information such as beverage type, price range, and consumer reviews, and this information is combined to narrow down the recommended beverages.

[0079] As a result, the server sends a list of beverage candidates generated based on the analysis to the terminal. The terminal presents this list to the user and displays detailed information for each candidate. Based on this information, the user can easily select the beverage that best suits them.

[0080] Once the user selects a beverage, the terminal sends that information back to the server, and the purchase process is expedited. The server completes the reservation or purchase arrangement and sends a completion notification back to the terminal. The user can obtain their beverage efficiently as the entire process proceeds smoothly.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] The user initiates communication using their device and enters prompts regarding beverage selection. They might enter specific criteria such as, "Please suggest a sweet red wine under 3000 yen for a home party." The entered information is then transmitted from the device to the server via a communication device.

[0084] Step 2:

[0085] The server analyzes the user input conditions received from the terminal. For analysis, the input data is first taken into an information processing system and compared with a beverage database. The database stores various beverage varieties, price ranges, reviews, etc., and the server retrieves this data and compares it with the user's conditions.

[0086] Step 3:

[0087] The server generates beverage candidates that best match the user's input conditions based on data acquired using a generative AI model. The AI ​​model analyzes large-scale data to narrow down the best candidates that match the input conditions. These conditions include, for example, a specific price range or taste characteristics.

[0088] Step 4:

[0089] The server sends a list of generated beverage candidates to the terminal. This list includes detailed information such as wine variety, characteristics, price, and consumer reviews. The terminal presents this information to the user, allowing them to review the candidates.

[0090] Step 5:

[0091] The user selects the beverage that best suits their preferences from the presented options. Once the selection is complete, the device sends the selection information to the server. The server then prepares to process the purchase.

[0092] Step 6:

[0093] The server quickly processes purchases and arranges reservations based on the user's selections. Once the process is complete, the server sends a completion notification to the terminal. The terminal displays this notification to the user, informing them that the purchase process has been completed smoothly.

[0094] (Application Example 1)

[0095] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0096] Modern beverage stores face challenges such as difficulty for customers to choose the flavored beverage best suited to their preferences and needs, and long waiting times for efficient beverage purchases. This is especially true for first-time customers or those unfamiliar with beverage selection, who may find themselves overwhelmed by the sheer volume of information and take too long to make a decision.

[0097] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0098] In this invention, the server includes communication means for receiving user input conditions, information processing means for acquiring and analyzing flavor beverage data based on those conditions, and display means for guiding the user to flavor beverage candidates and their in-store locations based on the analysis results. This allows customers to easily select and efficiently purchase flavor beverages that suit their preferences.

[0099] "User input conditions" refer to information such as the user's preferences, intended use, and budget when selecting a flavored beverage.

[0100] "Communication means" refers to the technology and devices used to receive conditions entered by the user and transmit them to the server.

[0101] "Flavor beverage data" refers to database information containing detailed information about a specific beverage, such as its type, characteristics, and evaluation.

[0102] "Information processing means" refers to a computer system or program for acquiring and analyzing flavor beverage data based on user input conditions.

[0103] "Display means" refers to the interface of a display or mobile device that presents information to the user based on the analysis results.

[0104] "Guiding users to the location within the store" refers to navigation technology that accurately informs users of the location of the product they have selected within the store.

[0105] A "wireless communication device" is a device used to acquire customer location information within a store and communicate with a server.

[0106] "Reservation procedures" refer to systemic processes that allow customers to reserve their chosen flavored beverages in advance, thereby increasing the efficiency of their purchase.

[0107] To implement this invention, a system is built that uses a smartphone application to improve the customer experience at stores selling flavored beverages. Specifically, the following hardware and software are used.

[0108] hardware

[0109] Smartphone: A mobile device used by customers, which is used to operate apps and perform input and selections.

[0110] Wireless communication devices: These include beacons and Wi-Fi routers used to track customer locations within a store.

[0111] software

[0112] Mobile application (iOS / ANDROID®): This is an application that customers install and use on their smartphones. This application accepts user input and presents a list of flavored beverage options.

[0113] Backend server: This server system analyzes flavor beverage data based on user conditions and returns the results to the application.

[0114] Generative AI model: This is a machine learning model used for analysis to select the most suitable flavored beverage candidate based on customer input conditions.

[0115] Data processing

[0116] The user input received by the terminal is sent to the backend server. The server uses a generative AI model to analyze flavor beverage data based on the conditions and select the best candidate. The selection result is sent to the mobile application and presented to the customer. In addition, the customer's location within the store is identified via wireless communication equipment, and the user is guided to the location of the selected product.

[0117] For example, if a user enters "a refreshing flavored beverage, under 500 yen" as selection criteria, the system analyzes the relevant flavored beverages and presents three options along with in-store displays, enabling quick selection and purchase.

[0118] Example of a prompt

[0119] "Create a new feature for a smartphone application that suggests the optimal flavored beverage based on budget, preferences, and intended use, and devise ways to improve the customer experience in physical stores."

[0120] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0121] Step 1:

[0122] The user launches a smartphone application and enters their preferences, intended use, and budget as criteria for a flavored beverage. The entered data is sent from the user's device to a backend server based on the selected criteria.

[0123] Step 2:

[0124] The server uses a generative AI model to analyze the user's input conditions. This analysis queries a flavor beverage database to select suitable candidates. The database contains information such as the characteristics and price of each product. As a result of the analysis, a list of products is generated.

[0125] Step 3:

[0126] The server generates a list of beverage options and sends it to the user's terminal. At the same time, detailed information about each option (characteristics, price, ratings, etc.) is also sent, allowing the user to consider each choice.

[0127] Step 4:

[0128] The user selects their preferred beverage from the presented options. The selected data is sent back to the server, which is then prepared to process the reservation or purchase.

[0129] Step 5:

[0130] Based on the user's selection, the server uses wireless communication equipment within the store to determine the customer's location and guides the user to the exact location of the shelf where the beverage is placed.

[0131] Step 6:

[0132] The user moves to a designated shelf within the store, confirms or picks up their selected beverage. This completes the user's selection process and the purchase.

[0133] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0134] This invention relates to a wine concierge system incorporating an emotion engine that recognizes the user's emotions. This system can suggest the most suitable wine candidates based on conditions provided by the user, and in the process, it can analyze the user's emotions and adjust the recommendations accordingly.

[0135] First, the user accesses the system using a terminal and provides information about their wine selection. The conditions entered by the user are sent to the server via communication. Based on these conditions, the server uses an emotion engine to evaluate the user's emotional state. The emotion engine detects emotions such as joy, surprise, sadness, and anger from the user's text input and voice tone.

[0136] The server analyzes emotional information obtained from the emotion engine and user input conditions using information processing tools to select the most suitable wine candidates. Specifically, it performs unique prioritization and filtering of the selected wine candidates according to the emotional state. Furthermore, it provides the user with the optimal experience by expressing the descriptions of the selected candidates in a tone appropriate to their emotions.

[0137] Users can review the wine options presented on their device and make a selection based on the displayed characteristics and ratings. Based on the user's selection, the server executes the wine reservation or purchase process. For example, if the system determines that the user is experiencing stress, it can use an emotion engine to prioritize suggesting wines that are believed to have a relaxing effect. In this way, the system aims to provide a personalized wine purchasing experience by considering the user's psychological state.

[0138] The following describes the processing flow.

[0139] Step 1:

[0140] The user accesses the LINE official account using their device and sends a message to begin the wine selection process. This initiates interaction between the user and the system.

[0141] Step 2:

[0142] The server receives the user's message and sends a message to the terminal asking for necessary information (budget, preferences, intended use, etc.). At the same time, it activates an emotion engine to analyze the user's initial emotional state.

[0143] Step 3:

[0144] The user enters detailed wine specifications via their device and sends them as a message. During this process, an emotion engine analyzes the user's input and voice tone to determine their emotional state.

[0145] Step 4:

[0146] The server integrates and analyzes the user's conditional data and emotional state using information processing tools to select the most suitable wine candidate. It prioritizes the candidates and adjusts the characteristics of the suggested wines according to the emotional state.

[0147] Step 5:

[0148] The server sends the selected wine candidates and their detailed information to the user's terminal for display. During this process, the candidates are described using emotionally charged tones and language, providing suggestions that resonate with the user's emotions.

[0149] Step 6:

[0150] The user selects their desired wine from a displayed wine list and sends their selection to the server via their device.

[0151] Step 7:

[0152] The server receives the user's selection and proceeds with the wine reservation or purchase process, while sending additional support messages tailored to the user's emotions.

[0153] Step 8:

[0154] The server notifies the user's device when the reservation or purchase process is complete and provides a final confirmation message. This allows the user to obtain the perfect wine that reflects their mood.

[0155] (Example 2)

[0156] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0157] Traditionally, when users selected beverages, many systems provided only general information without considering their individual emotional states. This made it difficult for users to make optimal choices based on their current psychological state. Furthermore, the lack of appropriate product suggestions tailored to their emotions resulted in a less-than-satisfactory user experience.

[0158] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0159] In this invention, the server includes communication means for receiving user input conditions, information processing means for acquiring and analyzing information about wine based on those conditions, and emotion recognition means for detecting and analyzing the user's emotional state. This enables personalized beverage recommendations that take the user's emotional state into account, and efficient execution of reservation or purchase procedures according to the user's selection.

[0160] "Communication means" refers to the technical configuration used to accurately receive input conditions from the user and transmit them to the server.

[0161] "Information processing means" refers to a combination of methods and apparatus for acquiring information about wine based on user input conditions and performing necessary analyses.

[0162] An "emotion recognition system" is a system for detecting and analyzing a user's emotional state from their text or voice.

[0163] "Display means" refers to a device or method for presenting beverage candidates to a user based on the analysis results.

[0164] "Natural language processing means" refers to technology that adjusts the description of beverage candidates according to the user's emotional state and displays them in appropriate language.

[0165] This invention is a system that recognizes a user's emotions and suggests beverages based on those emotions. The system consists of a server, a terminal, and communication means connecting them.

[0166] The user accesses the system using a terminal. The user inputs information about their beverage selection and provides data in text or voice. The terminal transmits this input data to the server via a communication means (e.g., an internet connection).

[0167] The server performs multiple processes based on the received data. First, it uses a database management system (e.g., MySQL® or PostgreSQL) as an information processing tool to obtain beverage information that matches the specified criteria. Then, it uses emotion recognition tools to analyze the emotions from the user's input. This analysis is performed using Natural Language Processing (NLP) technology and speech analysis technology (e.g., Google® Cloud Natural Language API or IBM Watson® Speech to Text).

[0168] Furthermore, the server uses a generative AI model to formulate optimal suggestions for the user based on emotional information and acquired beverage information. For display purposes, it provides a display optimized for the user's terminal and offers explanations in natural language that respond to emotions. This utilizes natural language processing technology.

[0169] For example, if a user enters "I want to relax today," the server analyzes the emotion of "relaxation" and prioritizes suggesting beverages that match that emotion. This allows the user to make a choice that suits their mood.

[0170] An example of a prompt is, "How can we suggest the best beverage for a user who wants to relax?" This prompt can be input into a generative AI model to obtain appropriate suggestions.

[0171] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0172] Step 1:

[0173] Users log in to the wine concierge system using a terminal and input their preferences via text or voice. This input includes the type of beverage, budget, purpose, and current mood. The terminal transmits the input data to the server via a communication method. The input data is converted to a standard format to facilitate analysis on the server.

[0174] Step 2:

[0175] The server receives user input data sent from the terminal. Based on the received data, it uses information processing tools to retrieve information about beverages using a database management system. In this process, SQL queries are used to extract candidate beverages that match the specified criteria. The input is the user's desired criteria, and the output is a list of beverage information corresponding to those criteria.

[0176] Step 3:

[0177] The server analyzes the user's emotional state using emotion recognition technology, along with the acquired beverage information. Utilizing NLP and speech analysis technologies, it estimates emotions from the user's input and determines whether they are joyful, relaxed, stressed, etc. The input is the user's text or voice data, and the output is the identified emotional state.

[0178] Step 4:

[0179] The server integrates emotional information and beverage information and inputs prompt sentences into the generative AI model. The prompt sentences are designed to obtain beverage suggestions best suited to the emotional state, and the AI ​​model prioritizes or filters the list of candidate beverages. The input is emotional information and a list of beverages, and the output is a list of suggested beverages that match the user's emotions.

[0180] Step 5:

[0181] The server sends optimized beverage options to the terminal for display. The terminal presents the beverage options along with descriptions tailored to the user's mood. The user selects the most suitable beverage based on the displayed information and then reviews the details. The input is an optimized beverage list, and the output is a display of the descriptions and beverage options presented to the user.

[0182] Step 6:

[0183] The user selects whether to purchase or reserve a beverage from the presented options. Once the selection is confirmed, the terminal sends that information back to the server. The server then processes the purchase of the selected beverage through the online payment system. The input is the user's selection data, and the output is a purchase confirmation message.

[0184] (Application Example 2)

[0185] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0186] Traditional beverage recommendation systems have faced the challenge of providing a personalized experience that responds to user emotions. In particular, the static nature of the display meant that users could not receive immediate, emotion-based recommendations in real-world settings such as stores. As a result, the user's purchasing experience was not always entirely satisfactory.

[0187] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0188] In this invention, the server includes a device for receiving user input conditions, an information processing device for acquiring and analyzing beverage data, and a device including an emotion engine for analyzing the user's emotional state. This enables users to visually receive emotion-based beverage recommendations using a wearable terminal in a physical space such as a store. This system can provide a more personalized, real-time purchasing experience and improve user satisfaction.

[0189] A "device for receiving user input conditions" is a device that receives the conditions and preferences selected by the user and transmits them to the system.

[0190] An "information processing device for acquiring and analyzing beverage data" is a device that collects information about various beverages and generates optimized results based on user conditions.

[0191] An "emotion engine that analyzes the user's emotional state" is an analytical device that evaluates the user's emotions and understands the user's psychological state.

[0192] A "display device that suggests recommended beverage candidates" is a display device that shows the user appropriate beverage candidates based on the analyzed results.

[0193] A "wearable device" is a device that a user can wear and use, and it plays a role in seamlessly presenting information in the real world.

[0194] A "communication device" is a device used to exchange information between a system and a wearable terminal or other device, enabling real-time transmission and reception of data.

[0195] To implement this invention, a system is required in which a user, a server, and a wearable terminal work in cooperation. The user uses the wearable terminal to provide input conditions to the system. The wearable terminal receives the input conditions from the user and transmits that information to the server via a communication device.

[0196] The server acquires and analyzes beverage data based on user input conditions received using an information processing device. During this process, the server analyzes the user's emotional state using an emotion engine and selects beverage candidates based on the results. The emotion engine uses specific voice analysis software and text analysis algorithms to classify the user's emotions into categories such as "joy," "surprise," and "sadness." Based on the analyzed emotional state, the server determines the priority of recommended beverages and customizes the information presented to the user.

[0197] A display device integrated into the wearable terminal visually presents the user with the most suitable beverage options transmitted from the server. This allows users to receive personalized recommendations tailored to their emotions on the spot, which is particularly useful in the wine section of physical stores.

[0198] For example, recommending sparkling wine when the user is feeling lighthearted, and a rich red wine when they are feeling calm, can enhance the user experience. Furthermore, by inputting prompts into the generative AI model, the system can perform more refined analysis and enable more accurate recommendations. In this case, an example of a prompt might be: "If the user's emotional state is classified as 'want to relax,' generate which wine is suitable. Please output a description including the wine's characteristics and the reason for the recommendation."

[0199] Implementing such a system will enable a personalized beverage selection experience based on the user's emotions.

[0200] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0201] Step 1:

[0202] The wearable terminal receives input from the user. This input consists of the user's preferences and criteria regarding wine selection. The terminal acquires this information through sensors and a touch interface and prepares to send it to the server.

[0203] Step 2:

[0204] The server receives input conditions sent from the terminal. Next, the server consults the beverage database and retrieves data that matches the conditions. During this process, the server filters similar data and constructs an initial dataset to select the most relevant items.

[0205] Step 3:

[0206] The server analyzes the user's emotional state using an emotion engine based on the received input conditions and beverage data. This process utilizes speech and text emotion analysis software to detect emotions such as joy, surprise, and sadness from the user's input. The output is the analyzed emotional state.

[0207] Step 4:

[0208] Based on the analyzed emotional state, the server re-evaluates the beverage dataset and determines emotion-based priorities. Here, it determines how well the selected beverages match the user's emotions and, as a result, creates a list of optimal beverage candidates.

[0209] Step 5:

[0210] The server sends the generated list of beverage options to a wearable terminal. The terminal visually presents the received data to the user on a display device. In this process, the terminal arranges multiple options in an easy-to-view manner to help the user make an intuitive selection.

[0211] Step 6:

[0212] The user checks the display on the device and selects their preferred beverage. This selection is then sent back to the server via the wearable device. The server confirms the received information and proceeds to the next step, either the purchase or reservation process.

[0213] This will provide a personalized beverage recommendation experience based on emotions.

[0214] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0215] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0216] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0217] [Second Embodiment]

[0218] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0219] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0220] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0221] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0222] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0223] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0224] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0225] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0226] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0227] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0228] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0229] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0230] This invention is a system designed to support users, especially beginners and those with little experience, in choosing wine. The system allows users to input criteria related to wine, and through data analysis based on those criteria, it presents optimal wine candidates, simplifying the selection and purchase process.

[0231] First, the user accesses the LINE official account using their device and requests wine selection via chat. The device receives the user's input criteria and transmits them to the server via communication. The user can input criteria such as budget, preferences, and purpose, thereby defining their detailed wine preferences.

[0232] The server analyzes the received conditions and generates suitable wine candidates using big data about wine. Specifically, the server communicates with a wine database to obtain the characteristics, reviews, and ratings of wines that match the user's conditions, and uses statistical methods through information processing to create a list of optimal candidates.

[0233] Users can view wine options presented by the server on their devices. Each wine includes detailed information such as grape variety, characteristics, price range, and consumer reviews to help users make the best choice. Users can also select their preferred wine from the presented options and complete the purchase or reservation process on their devices.

[0234] The server quickly processes purchases and reservations based on the user's selection and sends a completion notification to the device. In this way, users can efficiently find wines that meet their individual criteria and proceed smoothly through the purchase process. For example, if a user is looking for a red wine under 3000 yen for a home party, the generating AI will select suitable wines from the database, and the server will analyze the information and present it. The user can then use this information to make a purchase decision.

[0235] The following describes the processing flow.

[0236] Step 1:

[0237] The user opens the LINE official account and sends a message via their device to begin the wine selection process. Sending this message initiates interaction with the user.

[0238] Step 2:

[0239] The server receives the user's message and sends a message to the terminal in the form of questions to confirm conditions related to wine selection, such as budget, preferences, and intended use.

[0240] Step 3:

[0241] The user enters specific conditions (e.g., "Budget up to 3000 yen, red wine, for a home party") from their device in response to the presented question and sends them to the server.

[0242] Step 4:

[0243] The server records the user's criteria data received and uses a generative AI to access the wine database. It searches for wine candidates that match the criteria and analyzes the results.

[0244] Step 5:

[0245] Based on the data analyzed by the server, the system selects wine candidates that are considered to be the best fit for the user's criteria and creates a candidate list that includes detailed information about those wines.

[0246] Step 6:

[0247] The server sends a list of candidates to the terminal, displaying them to the user as selectable wine options. This list includes information such as the characteristics, price, and rating of each wine.

[0248] Step 7:

[0249] The user selects their preferred wine from the presented wine options and sends their selection to the server via their device.

[0250] Step 8:

[0251] The server will process the wine reservation or purchase based on the user's selection. If necessary, it will also verify payment information and arrange delivery.

[0252] Step 9:

[0253] The server notifies the terminal of the completion of the reservation or purchase process and sends a confirmation message to the user.

[0254] This entire process allows users to find a wine that perfectly matches their criteria and purchase it smoothly.

[0255] (Example 1)

[0256] Next, we will describe Example 1. 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".

[0257] Choosing the optimal beverage by considering various factors is not easy. This is especially true for novice or inexperienced consumers, who find the perfect beverage to suit their needs from a vast array of options. Furthermore, there is a lack of readily available means to ensure a quick and smooth purchase process after selection.

[0258] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0259] In this invention, the server includes communication means for receiving user input conditions, information processing means for acquiring and analyzing beverage data based on said conditions, presentation means for presenting beverage candidates to the user based on the analysis results, means for generating candidates using a generative AI model, and means for selecting candidates that match the user's conditions. This enables the user to efficiently select a beverage that meets their criteria and purchase it smoothly.

[0260] A "user" refers to an individual who uses the system to select and purchase beverages.

[0261] "Input conditions" refer to information that indicates the user's specific requirements, such as the price, type, and intended use of the beverage they desire.

[0262] "Communication method" refers to digital communication technology used to send user input conditions to a server and receive analysis results from the server.

[0263] "Beverage data" refers to a database containing information such as characteristics, reviews, and ratings of wine and other beverages.

[0264] "Analysis" refers to the process of scrutinizing beverage data based on input conditions and deriving the optimal candidate.

[0265] "Information processing means" refers to a combination of software and hardware used to perform analysis, integrate input conditions and beverage data, and generate beverage candidates suitable for the user.

[0266] "Presentation method" refers to an interface for displaying analysis results in an easily understandable way to the user.

[0267] A "generative AI model" refers to artificial intelligence technology used to analyze large-scale data and select beverages that are suitable for the input conditions.

[0268] "Candidates" refers to a list of suggested beverages that the user can select based on the input criteria.

[0269] "Selection" refers to the process of choosing the optimal candidate from the analysis results using a generative AI model.

[0270] This invention provides a system that allows users to more easily select and purchase beverages that meet their specific requirements. Users first access the system using a communication terminal and input the desired beverage criteria. For example, a user can input a prompt such as, "Please suggest a sweet red wine under 3000 yen for a home party."

[0271] The terminal receives these input conditions and transmits them to the server via communication means. The server uses information processing means to analyze the received conditions. This means includes a wide range of databases on wine and other beverages, from which the server retrieves relevant information.

[0272] The server then uses a generative AI model to generate beverage candidates that meet the specified criteria. This AI model analyzes beverage data and outputs the most suitable candidates that satisfy the user's input conditions. For example, the database contains information such as beverage type, price range, and consumer reviews, and this information is combined to narrow down the recommended beverages.

[0273] As a result, the server sends a list of beverage candidates generated based on the analysis to the terminal. The terminal presents this list to the user and displays detailed information for each candidate. Based on this information, the user can easily select the beverage that best suits them.

[0274] Once the user selects a beverage, the terminal sends that information back to the server, and the purchase process is expedited. The server completes the reservation or purchase arrangement and sends a completion notification back to the terminal. The user can obtain their beverage efficiently as the entire process proceeds smoothly.

[0275] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0276] Step 1:

[0277] The user initiates communication using their device and enters prompts regarding beverage selection. They might enter specific criteria such as, "Please suggest a sweet red wine under 3000 yen for a home party." The entered information is then transmitted from the device to the server via a communication device.

[0278] Step 2:

[0279] The server analyzes the user input conditions received from the terminal. For analysis, the input data is first taken into an information processing system and compared with a beverage database. The database stores various beverage varieties, price ranges, reviews, etc., and the server retrieves this data and compares it with the user's conditions.

[0280] Step 3:

[0281] Based on the data obtained by leveraging the generative AI model, the server generates beverage candidates that best match the user's input conditions. The AI model analyzes large-scale data and narrows down the optimal candidates that match the input conditions. This includes, for example, specific price ranges and taste characteristics.

[0282] Step 4:

[0283] The server sends the list of generated beverage candidates to the terminal. This list includes detailed information such as the variety, characteristics, price, and consumer reviews of the wine. The terminal presents the information to the user so that the user can check the candidates.

[0284] Step 5:

[0285] The user selects the beverage that best suits their preference from the presented candidates. Once the selection is complete, the terminal sends the selection information to the server. The server proceeds to prepare for the purchase procedure.

[0286] Step 6:

[0287] Based on the user's selection, the server quickly arranges the purchase procedure or reservation. When the procedure is completed, the server sends a completion notice to the terminal. The terminal displays the notice to the user, informing them that the purchase process has ended smoothly.

[0288] (Application Example 1)

[0289] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0290] In modern beverage stores, it is difficult for customers to choose the flavor beverage that best suits their preferences and uses, and there is also the problem of long waiting times for efficiently purchasing beverages in the store. Especially for beginners or customers who are not used to choosing beverages, there is too much information and it may take time to make a selection.

[0291] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0292] In this invention, the server includes communication means for receiving user input conditions, information processing means for acquiring and analyzing flavor beverage data based on those conditions, and display means for guiding the user to flavor beverage candidates and their in-store locations based on the analysis results. This allows customers to easily select and efficiently purchase flavor beverages that suit their preferences.

[0293] "User input conditions" refer to information such as the user's preferences, intended use, and budget when selecting a flavored beverage.

[0294] "Communication means" refers to the technology and devices used to receive conditions entered by the user and transmit them to the server.

[0295] "Flavor beverage data" refers to database information containing detailed information about a specific beverage, such as its type, characteristics, and evaluation.

[0296] "Information processing means" refers to a computer system or program for acquiring and analyzing flavor beverage data based on user input conditions.

[0297] "Display means" refers to the interface of a display or mobile device that presents information to the user based on the analysis results.

[0298] "Guiding users to the location within the store" refers to navigation technology that accurately informs users of the location of the product they have selected within the store.

[0299] A "wireless communication device" is a device used to acquire customer location information within a store and communicate with a server.

[0300] The "reservation procedure" is a system procedure for customers to secure in advance the flavored beverages they have selected and enhance the efficiency of purchases.

[0301] To implement this invention, a system is constructed using a smartphone application to improve the customer experience in stores selling flavored beverages. Specifically, the following hardware and software are utilized.

[0302] Hardware

[0303] Smartphone: A mobile device used by customers, which is a device for operating the application to make inputs and selections.

[0304] Wireless communication device: Such as beacons and Wi-Fi routers used to determine the positions of customers within the store.

[0305] Software

[0306] Mobile application (iOS / Android): An application installed and used by customers on their smartphones. This application accepts the input conditions of users and presents candidates for flavored beverages.

[0307] Backend server: A server system that analyzes flavored beverage data based on user conditions and returns the results to the application.

[0308] Generated AI model: A machine learning model used for analysis to select the optimal candidates for flavored beverages from the input conditions of customers.

[0309] Data processing

[0310] The user input received by the terminal is sent to the backend server. The server uses a generative AI model to analyze flavor beverage data based on the conditions and select the best candidate. The selection result is sent to the mobile application and presented to the customer. In addition, the customer's location within the store is identified via wireless communication equipment, and the user is guided to the location of the selected product.

[0311] For example, if a user enters "a refreshing flavored beverage, under 500 yen" as selection criteria, the system analyzes the relevant flavored beverages and presents three options along with in-store displays, enabling quick selection and purchase.

[0312] Example of a prompt

[0313] "Create a new feature for a smartphone application that suggests the optimal flavored beverage based on budget, preferences, and intended use, and devise ways to improve the customer experience in physical stores."

[0314] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0315] Step 1:

[0316] The user launches a smartphone application and enters their preferences, intended use, and budget as criteria for a flavored beverage. The entered data is sent from the user's device to a backend server based on the selected criteria.

[0317] Step 2:

[0318] The server uses a generative AI model to analyze the user's input conditions. This analysis queries a flavor beverage database to select suitable candidates. The database contains information such as the characteristics and price of each product. As a result of the analysis, a list of products is generated.

[0319] Step 3:

[0320] The server generates a list of beverage options and sends it to the user's terminal. At the same time, detailed information about each option (characteristics, price, ratings, etc.) is also sent, allowing the user to consider each choice.

[0321] Step 4:

[0322] The user selects their preferred beverage from the presented options. The selected data is sent back to the server, which is then prepared to process the reservation or purchase.

[0323] Step 5:

[0324] Based on the user's selection, the server uses wireless communication equipment within the store to determine the customer's location and guides the user to the exact location of the shelf where the beverage is placed.

[0325] Step 6:

[0326] The user moves to a designated shelf within the store, confirms or picks up their selected beverage. This completes the user's selection process and the purchase.

[0327] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0328] This invention relates to a wine concierge system incorporating an emotion engine that recognizes the user's emotions. This system can suggest the most suitable wine candidates based on conditions provided by the user, and in the process, it can analyze the user's emotions and adjust the recommendations accordingly.

[0329] First, the user accesses the system using a terminal and provides information about their wine selection. The conditions entered by the user are sent to the server via communication. Based on these conditions, the server uses an emotion engine to evaluate the user's emotional state. The emotion engine detects emotions such as joy, surprise, sadness, and anger from the user's text input and voice tone.

[0330] The server analyzes emotional information obtained from the emotion engine and user input conditions using information processing tools to select the most suitable wine candidates. Specifically, it performs unique prioritization and filtering of the selected wine candidates according to the emotional state. Furthermore, it provides the user with the optimal experience by expressing the descriptions of the selected candidates in a tone appropriate to their emotions.

[0331] Users can review the wine options presented on their device and make a selection based on the displayed characteristics and ratings. Based on the user's selection, the server executes the wine reservation or purchase process. For example, if the system determines that the user is experiencing stress, it can use an emotion engine to prioritize suggesting wines that are believed to have a relaxing effect. In this way, the system aims to provide a personalized wine purchasing experience by considering the user's psychological state.

[0332] The following describes the processing flow.

[0333] Step 1:

[0334] The user accesses the LINE official account using their device and sends a message to begin the wine selection process. This initiates interaction between the user and the system.

[0335] Step 2:

[0336] The server receives the user's message and sends a message to the terminal asking for necessary information (budget, preferences, intended use, etc.). At the same time, it activates an emotion engine to analyze the user's initial emotional state.

[0337] Step 3:

[0338] The user enters detailed wine specifications via their device and sends them as a message. During this process, an emotion engine analyzes the user's input and voice tone to determine their emotional state.

[0339] Step 4:

[0340] The server integrates and analyzes the user's conditional data and emotional state using information processing tools to select the most suitable wine candidate. It prioritizes the candidates and adjusts the characteristics of the suggested wines according to the emotional state.

[0341] Step 5:

[0342] The server sends the selected wine candidates and their detailed information to the user's terminal for display. During this process, the candidates are described using emotionally charged tones and language, providing suggestions that resonate with the user's emotions.

[0343] Step 6:

[0344] The user selects their desired wine from a displayed wine list and sends their selection to the server via their device.

[0345] Step 7:

[0346] The server receives the user's selection and proceeds with the wine reservation or purchase process, while sending additional support messages tailored to the user's emotions.

[0347] Step 8:

[0348] The server notifies the user's device when the reservation or purchase process is complete and provides a final confirmation message. This allows the user to obtain the perfect wine that reflects their mood.

[0349] (Example 2)

[0350] Next, we will describe Example 2. 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".

[0351] Traditionally, when users selected beverages, many systems provided only general information without considering their individual emotional states. This made it difficult for users to make optimal choices based on their current psychological state. Furthermore, the lack of appropriate product suggestions tailored to their emotions resulted in a less-than-satisfactory user experience.

[0352] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0353] In this invention, the server includes communication means for receiving user input conditions, information processing means for acquiring and analyzing information about wine based on those conditions, and emotion recognition means for detecting and analyzing the user's emotional state. This enables personalized beverage recommendations that take the user's emotional state into account, and efficient execution of reservation or purchase procedures according to the user's selection.

[0354] "Communication means" refers to the technical configuration used to accurately receive input conditions from the user and transmit them to the server.

[0355] "Information processing means" refers to a combination of methods and apparatus for acquiring information about wine based on user input conditions and performing necessary analyses.

[0356] An "emotion recognition system" is a system for detecting and analyzing a user's emotional state from their text or voice.

[0357] "Display means" refers to a device or method for presenting beverage candidates to a user based on the analysis results.

[0358] "Natural language processing means" refers to technology that adjusts the description of beverage candidates according to the user's emotional state and displays them in appropriate language.

[0359] This invention is a system that recognizes a user's emotions and suggests beverages based on those emotions. The system consists of a server, a terminal, and communication means connecting them.

[0360] The user accesses the system using a terminal. The user inputs information about their beverage selection and provides data in text or voice. The terminal transmits this input data to the server via a communication means (e.g., an internet connection).

[0361] The server performs multiple processes based on the received data. First, it uses a database management system (e.g., MySQL or PostgreSQL) as an information processing tool to obtain beverage information that matches the specified criteria. Then, it uses emotion recognition tools to analyze the emotions from the user's input. This analysis is performed using Natural Language Processing (NLP) technology and speech analysis technology (e.g., Google Cloud Natural Language API or IBM Watson Speech to Text).

[0362] Furthermore, the server uses a generative AI model to formulate optimal suggestions for the user based on emotional information and acquired beverage information. For display purposes, it provides a display optimized for the user's terminal and offers explanations in natural language that respond to emotions. This utilizes natural language processing technology.

[0363] For example, if a user enters "I want to relax today," the server analyzes the emotion of "relaxation" and prioritizes suggesting beverages that match that emotion. This allows the user to make a choice that suits their mood.

[0364] An example of a prompt is, "How can we suggest the best beverage for a user who wants to relax?" This prompt can be input into a generative AI model to obtain appropriate suggestions.

[0365] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0366] Step 1:

[0367] Users log in to the wine concierge system using a terminal and input their preferences via text or voice. This input includes the type of beverage, budget, purpose, and current mood. The terminal transmits the input data to the server via a communication method. The input data is converted to a standard format to facilitate analysis on the server.

[0368] Step 2:

[0369] The server receives user input data sent from the terminal. Based on the received data, it uses information processing tools to retrieve information about beverages using a database management system. In this process, SQL queries are used to extract candidate beverages that match the specified criteria. The input is the user's desired criteria, and the output is a list of beverage information corresponding to those criteria.

[0370] Step 3:

[0371] The server analyzes the user's emotional state using emotion recognition technology, along with the acquired beverage information. Utilizing NLP and speech analysis technologies, it estimates emotions from the user's input and determines whether they are joyful, relaxed, stressed, etc. The input is the user's text or voice data, and the output is the identified emotional state.

[0372] Step 4:

[0373] The server integrates emotional information and beverage information and inputs prompt sentences into the generative AI model. The prompt sentences are designed to obtain beverage suggestions best suited to the emotional state, and the AI ​​model prioritizes or filters the list of candidate beverages. The input is emotional information and a list of beverages, and the output is a list of suggested beverages that match the user's emotions.

[0374] Step 5:

[0375] The server sends optimized beverage options to the terminal for display. The terminal presents the beverage options along with descriptions tailored to the user's mood. The user selects the most suitable beverage based on the displayed information and then reviews the details. The input is an optimized beverage list, and the output is a display of the descriptions and beverage options presented to the user.

[0376] Step 6:

[0377] The user selects whether to purchase or reserve a beverage from the presented options. Once the selection is confirmed, the terminal sends that information back to the server. The server then processes the purchase of the selected beverage through the online payment system. The input is the user's selection data, and the output is a purchase confirmation message.

[0378] (Application Example 2)

[0379] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0380] Traditional beverage recommendation systems have faced the challenge of providing a personalized experience that responds to user emotions. In particular, the static nature of the display meant that users could not receive immediate, emotion-based recommendations in real-world settings such as stores. As a result, the user's purchasing experience was not always entirely satisfactory.

[0381] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0382] In this invention, the server includes a device for receiving user input conditions, an information processing device for acquiring and analyzing beverage data, and a device including an emotion engine for analyzing the user's emotional state. This enables users to visually receive emotion-based beverage recommendations using a wearable terminal in a physical space such as a store. This system can provide a more personalized, real-time purchasing experience and improve user satisfaction.

[0383] A "device for receiving user input conditions" is a device that receives the conditions and preferences selected by the user and transmits them to the system.

[0384] An "information processing device for acquiring and analyzing beverage data" is a device that collects information about various beverages and generates optimized results based on user conditions.

[0385] An "emotion engine that analyzes the user's emotional state" is an analytical device that evaluates the user's emotions and understands the user's psychological state.

[0386] A "display device that suggests recommended beverage candidates" is a display device that shows the user appropriate beverage candidates based on the analyzed results.

[0387] A "wearable device" is a device that a user can wear and use, and it plays a role in seamlessly presenting information in the real world.

[0388] A "communication device" is a device used to exchange information between a system and a wearable terminal or other device, enabling real-time transmission and reception of data.

[0389] To implement this invention, a system is required in which a user, a server, and a wearable terminal work in cooperation. The user uses the wearable terminal to provide input conditions to the system. The wearable terminal receives the input conditions from the user and transmits that information to the server via a communication device.

[0390] The server acquires and analyzes beverage data based on user input conditions received using an information processing device. During this process, the server analyzes the user's emotional state using an emotion engine and selects beverage candidates based on the results. The emotion engine uses specific voice analysis software and text analysis algorithms to classify the user's emotions into categories such as "joy," "surprise," and "sadness." Based on the analyzed emotional state, the server determines the priority of recommended beverages and customizes the information presented to the user.

[0391] A display device integrated into the wearable terminal visually presents the user with the most suitable beverage options transmitted from the server. This allows users to receive personalized recommendations tailored to their emotions on the spot, which is particularly useful in the wine section of physical stores.

[0392] For example, recommending sparkling wine when the user is feeling lighthearted, and a rich red wine when they are feeling calm, can enhance the user experience. Furthermore, by inputting prompts into the generative AI model, the system can perform more refined analysis and enable more accurate recommendations. In this case, an example of a prompt might be: "If the user's emotional state is classified as 'want to relax,' generate which wine is suitable. Please output a description including the wine's characteristics and the reason for the recommendation."

[0393] Implementing such a system will enable a personalized beverage selection experience based on the user's emotions.

[0394] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0395] Step 1:

[0396] The wearable terminal receives input from the user. This input consists of the user's preferences and criteria regarding wine selection. The terminal acquires this information through sensors and a touch interface and prepares to send it to the server.

[0397] Step 2:

[0398] The server receives input conditions sent from the terminal. Next, the server consults the beverage database and retrieves data that matches the conditions. During this process, the server filters similar data and constructs an initial dataset to select the most relevant items.

[0399] Step 3:

[0400] The server analyzes the user's emotional state using an emotion engine based on the received input conditions and beverage data. This process utilizes speech and text emotion analysis software to detect emotions such as joy, surprise, and sadness from the user's input. The output is the analyzed emotional state.

[0401] Step 4:

[0402] Based on the analyzed emotional state, the server re-evaluates the beverage dataset and determines emotion-based priorities. Here, it determines how well the selected beverages match the user's emotions and, as a result, creates a list of optimal beverage candidates.

[0403] Step 5:

[0404] The server sends the generated list of beverage options to a wearable terminal. The terminal visually presents the received data to the user on a display device. In this process, the terminal arranges multiple options in an easy-to-view manner to help the user make an intuitive selection.

[0405] Step 6:

[0406] The user checks the display on the device and selects their preferred beverage. This selection is then sent back to the server via the wearable device. The server confirms the received information and proceeds to the next step, either the purchase or reservation process.

[0407] This will provide a personalized beverage recommendation experience based on emotions.

[0408] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0409] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0410] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0411] [Third Embodiment]

[0412] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0413] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0414] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0415] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0416] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0417] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0418] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0419] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0420] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0421] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0422] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0423] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0424] This invention is a system designed to support users, especially beginners and those with little experience, in choosing wine. The system allows users to input criteria related to wine, and through data analysis based on those criteria, it presents optimal wine candidates, simplifying the selection and purchase process.

[0425] First, the user accesses the LINE official account using their device and requests wine selection via chat. The device receives the user's input criteria and transmits them to the server via communication. The user can input criteria such as budget, preferences, and purpose, thereby defining their detailed wine preferences.

[0426] The server analyzes the received conditions and generates suitable wine candidates using big data about wine. Specifically, the server communicates with a wine database to obtain the characteristics, reviews, and ratings of wines that match the user's conditions, and uses statistical methods through information processing to create a list of optimal candidates.

[0427] Users can view wine options presented by the server on their devices. Each wine includes detailed information such as grape variety, characteristics, price range, and consumer reviews to help users make the best choice. Users can also select their preferred wine from the presented options and complete the purchase or reservation process on their devices.

[0428] The server quickly processes purchases and reservations based on the user's selection and sends a completion notification to the device. In this way, users can efficiently find wines that meet their individual criteria and proceed smoothly through the purchase process. For example, if a user is looking for a red wine under 3000 yen for a home party, the generating AI will select suitable wines from the database, and the server will analyze the information and present it. The user can then use this information to make a purchase decision.

[0429] The following describes the processing flow.

[0430] Step 1:

[0431] The user opens the LINE official account and sends a message via their device to begin the wine selection process. Sending this message initiates interaction with the user.

[0432] Step 2:

[0433] The server receives the user's message and sends a message to the terminal in the form of questions to confirm conditions related to wine selection, such as budget, preferences, and intended use.

[0434] Step 3:

[0435] The user enters specific conditions (e.g., "Budget up to 3000 yen, red wine, for a home party") from their device in response to the presented question and sends them to the server.

[0436] Step 4:

[0437] The server records the user's criteria data received and uses a generative AI to access the wine database. It searches for wine candidates that match the criteria and analyzes the results.

[0438] Step 5:

[0439] Based on the data analyzed by the server, the system selects wine candidates that are considered to be the best fit for the user's criteria and creates a candidate list that includes detailed information about those wines.

[0440] Step 6:

[0441] The server sends a list of candidates to the terminal, displaying them to the user as selectable wine options. This list includes information such as the characteristics, price, and rating of each wine.

[0442] Step 7:

[0443] The user selects their preferred wine from the presented wine options and sends their selection to the server via their device.

[0444] Step 8:

[0445] The server will process the wine reservation or purchase based on the user's selection. If necessary, it will also verify payment information and arrange delivery.

[0446] Step 9:

[0447] The server notifies the terminal of the completion of the reservation or purchase process and sends a confirmation message to the user.

[0448] This entire process allows users to find a wine that perfectly matches their criteria and purchase it smoothly.

[0449] (Example 1)

[0450] Next, we will describe Example 1. 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."

[0451] Choosing the optimal beverage by considering various factors is not easy. This is especially true for novice or inexperienced consumers, who find the perfect beverage to suit their needs from a vast array of options. Furthermore, there is a lack of readily available means to ensure a quick and smooth purchase process after selection.

[0452] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0453] In this invention, the server includes communication means for receiving user input conditions, information processing means for acquiring and analyzing beverage data based on said conditions, presentation means for presenting beverage candidates to the user based on the analysis results, means for generating candidates using a generative AI model, and means for selecting candidates that match the user's conditions. This enables the user to efficiently select a beverage that meets their criteria and purchase it smoothly.

[0454] A "user" refers to an individual who uses the system to select and purchase beverages.

[0455] "Input conditions" refer to information that indicates the user's specific requirements, such as the price, type, and intended use of the beverage they desire.

[0456] "Communication method" refers to digital communication technology used to send user input conditions to a server and receive analysis results from the server.

[0457] "Beverage data" refers to a database containing information such as characteristics, reviews, and ratings of wine and other beverages.

[0458] "Analysis" refers to the process of scrutinizing beverage data based on input conditions and deriving the optimal candidate.

[0459] "Information processing means" refers to a combination of software and hardware used to perform analysis, integrate input conditions and beverage data, and generate beverage candidates suitable for the user.

[0460] "Presentation method" refers to an interface for displaying analysis results in an easily understandable way to the user.

[0461] A "generative AI model" refers to artificial intelligence technology used to analyze large-scale data and select beverages that are suitable for the input conditions.

[0462] "Candidates" refers to a list of suggested beverages that users can select based on the input criteria.

[0463] "Selection" refers to the process of choosing the optimal candidate from the analysis results using a generative AI model.

[0464] This invention provides a system that allows users to more easily select and purchase beverages that meet their specific requirements. Users first access the system using a communication terminal and input the desired beverage criteria. For example, a user can input a prompt such as, "Please suggest a sweet red wine under 3000 yen for a home party."

[0465] The terminal receives these input conditions and transmits them to the server via communication means. The server uses information processing means to analyze the received conditions. This means includes a wide range of databases on wine and other beverages, from which the server retrieves relevant information.

[0466] The server then uses a generative AI model to generate beverage candidates that meet the specified criteria. This AI model analyzes beverage data and outputs the most suitable candidates that satisfy the user's input conditions. For example, the database contains information such as beverage type, price range, and consumer reviews, and this information is combined to narrow down the recommended beverages.

[0467] As a result, the server sends a list of beverage candidates generated based on the analysis to the terminal. The terminal presents this list to the user and displays detailed information for each candidate. Based on this information, the user can easily select the beverage that best suits them.

[0468] Once the user selects a beverage, the terminal sends that information back to the server, and the purchase process is expedited. The server completes the reservation or purchase arrangement and sends a completion notification back to the terminal. The user can obtain their beverage efficiently as the entire process proceeds smoothly.

[0469] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0470] Step 1:

[0471] The user initiates communication using their device and enters prompts regarding beverage selection. They might enter specific criteria such as, "Please suggest a sweet red wine under 3000 yen for a home party." The entered information is then transmitted from the device to the server via a communication device.

[0472] Step 2:

[0473] The server analyzes the user input conditions received from the terminal. For analysis, the input data is first taken into an information processing system and compared with a beverage database. The database stores various beverage varieties, price ranges, reviews, etc., and the server retrieves this data and compares it with the user's conditions.

[0474] Step 3:

[0475] The server generates beverage candidates that best match the user's input conditions based on data acquired using a generative AI model. The AI ​​model analyzes large-scale data to narrow down the best candidates that match the input conditions. These conditions include, for example, a specific price range or taste characteristics.

[0476] Step 4:

[0477] The server sends a list of generated beverage candidates to the terminal. This list includes detailed information such as wine variety, characteristics, price, and consumer reviews. The terminal presents this information to the user, allowing them to review the candidates.

[0478] Step 5:

[0479] The user selects the beverage that best suits their preferences from the presented options. Once the selection is complete, the device sends the selection information to the server. The server then prepares to process the purchase.

[0480] Step 6:

[0481] The server quickly processes purchases and arranges reservations based on the user's selections. Once the process is complete, the server sends a completion notification to the terminal. The terminal displays this notification to the user, informing them that the purchase process has been completed smoothly.

[0482] (Application Example 1)

[0483] Next, we will explain Application Example 1. In the following explanation, 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."

[0484] Modern beverage stores face challenges such as difficulty for customers to choose the flavored beverage best suited to their preferences and needs, and long waiting times for efficient beverage purchases. This is especially true for first-time customers or those unfamiliar with beverage selection, who may find themselves overwhelmed by the sheer volume of information and take too long to make a decision.

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

[0486] In this invention, the server includes communication means for receiving user input conditions, information processing means for acquiring and analyzing flavor beverage data based on those conditions, and display means for guiding the user to flavor beverage candidates and their in-store locations based on the analysis results. This allows customers to easily select and efficiently purchase flavor beverages that suit their preferences.

[0487] "User input conditions" refer to information such as the user's preferences, intended use, and budget when selecting a flavored beverage.

[0488] "Communication means" refers to the technology and devices used to receive conditions entered by the user and transmit them to the server.

[0489] "Flavor beverage data" refers to database information containing detailed information about a specific beverage, such as its type, characteristics, and evaluation.

[0490] "Information processing means" refers to a computer system or program for acquiring and analyzing flavor beverage data based on user input conditions.

[0491] "Display means" refers to the interface of a display or mobile device that presents information to the user based on the analysis results.

[0492] "Guiding users to the location within the store" refers to navigation technology that accurately informs users of the location of the product they have selected within the store.

[0493] A "wireless communication device" is a device used to acquire customer location information within a store and communicate with a server.

[0494] "Reservation procedures" refer to systemic processes that allow customers to reserve their chosen flavored beverages in advance, thereby increasing the efficiency of their purchase.

[0495] To implement this invention, a system is built that uses a smartphone application to improve the customer experience at stores selling flavored beverages. Specifically, the following hardware and software are used.

[0496] hardware

[0497] Smartphone: A mobile device used by customers, which is used to operate apps and perform input and selections.

[0498] Wireless communication devices: These include beacons and Wi-Fi routers used to track customer locations within a store.

[0499] software

[0500] Mobile application (iOS / Android): This is an app that customers install and use on their smartphones. The app accepts user input and presents suggested flavored beverages.

[0501] Backend server: This server system analyzes flavor beverage data based on user conditions and returns the results to the application.

[0502] Generative AI model: This is a machine learning model used for analysis to select the most suitable flavored beverage candidate based on customer input conditions.

[0503] Data processing

[0504] The user input received by the terminal is sent to the backend server. The server uses a generative AI model to analyze flavor beverage data based on the conditions and select the best candidate. The selection result is sent to the mobile application and presented to the customer. In addition, the customer's location within the store is identified via wireless communication equipment, and the user is guided to the location of the selected product.

[0505] For example, if a user enters "a refreshing flavored beverage, under 500 yen" as selection criteria, the system analyzes the relevant flavored beverages and presents three options along with in-store displays, enabling quick selection and purchase.

[0506] Example of a prompt

[0507] "Create a new feature for a smartphone application that suggests the optimal flavored beverage based on budget, preferences, and intended use, and devise ways to improve the customer experience in physical stores."

[0508] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0509] Step 1:

[0510] The user launches a smartphone application and enters their preferences, intended use, and budget as criteria for a flavored beverage. The entered data is sent from the user's device to a backend server based on the selected criteria.

[0511] Step 2:

[0512] The server uses a generative AI model to analyze the user's input conditions. This analysis queries a flavor beverage database to select suitable candidates. The database contains information such as the characteristics and price of each product. As a result of the analysis, a list of products is generated.

[0513] Step 3:

[0514] The server generates a list of beverage options and sends it to the user's terminal. At the same time, detailed information about each option (characteristics, price, ratings, etc.) is also sent, allowing the user to consider each choice.

[0515] Step 4:

[0516] The user selects their preferred beverage from the presented options. The selected data is sent back to the server, which is then prepared to process the reservation or purchase.

[0517] Step 5:

[0518] Based on the user's selection, the server uses wireless communication equipment within the store to determine the customer's location and guides the user to the exact location of the shelf where the beverage is placed.

[0519] Step 6:

[0520] The user moves to a designated shelf within the store, confirms or picks up their selected beverage. This completes the user's selection process and the purchase.

[0521] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0522] This invention relates to a wine concierge system incorporating an emotion engine that recognizes the user's emotions. This system can suggest the most suitable wine candidates based on conditions provided by the user, and in the process, it can analyze the user's emotions and adjust the recommendations accordingly.

[0523] First, the user accesses the system using a terminal and provides information about their wine selection. The conditions entered by the user are sent to the server via communication. Based on these conditions, the server uses an emotion engine to evaluate the user's emotional state. The emotion engine detects emotions such as joy, surprise, sadness, and anger from the user's text input and voice tone.

[0524] The server analyzes emotional information obtained from the emotion engine and user input conditions using information processing tools to select the most suitable wine candidates. Specifically, it performs unique prioritization and filtering of the selected wine candidates according to the emotional state. Furthermore, it provides the user with the optimal experience by expressing the descriptions of the selected candidates in a tone appropriate to their emotions.

[0525] Users can review the wine options presented on their device and make a selection based on the displayed characteristics and ratings. Based on the user's selection, the server executes the wine reservation or purchase process. For example, if the system determines that the user is experiencing stress, it can use an emotion engine to prioritize suggesting wines that are believed to have a relaxing effect. In this way, the system aims to provide a personalized wine purchasing experience by considering the user's psychological state.

[0526] The following describes the processing flow.

[0527] Step 1:

[0528] The user accesses the LINE official account using their device and sends a message to begin the wine selection process. This initiates interaction between the user and the system.

[0529] Step 2:

[0530] The server receives the user's message and sends a message to the terminal asking for necessary information (budget, preferences, intended use, etc.). At the same time, it activates an emotion engine to analyze the user's initial emotional state.

[0531] Step 3:

[0532] The user enters detailed wine specifications via their device and sends them as a message. During this process, an emotion engine analyzes the user's input and voice tone to determine their emotional state.

[0533] Step 4:

[0534] The server integrates and analyzes the user's conditional data and emotional state using information processing tools to select the most suitable wine candidate. It prioritizes the candidates and adjusts the characteristics of the suggested wines according to the emotional state.

[0535] Step 5:

[0536] The server sends the selected wine candidates and their detailed information to the user's terminal for display. During this process, the candidates are described using emotionally charged tones and language, providing suggestions that resonate with the user's emotions.

[0537] Step 6:

[0538] The user selects their desired wine from a displayed wine list and sends their selection to the server via their device.

[0539] Step 7:

[0540] The server receives the user's selection and proceeds with the wine reservation or purchase process, while sending additional support messages tailored to the user's emotions.

[0541] Step 8:

[0542] The server notifies the user's device when the reservation or purchase process is complete and provides a final confirmation message. This allows the user to obtain the perfect wine that reflects their mood.

[0543] (Example 2)

[0544] Next, we will describe Example 2. 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."

[0545] Traditionally, when users selected beverages, many systems provided only general information without considering their individual emotional states. This made it difficult for users to make optimal choices based on their current psychological state. Furthermore, the lack of appropriate product suggestions tailored to their emotions resulted in a less-than-satisfactory user experience.

[0546] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0547] In this invention, the server includes communication means for receiving user input conditions, information processing means for acquiring and analyzing information about wine based on those conditions, and emotion recognition means for detecting and analyzing the user's emotional state. This enables personalized beverage recommendations that take the user's emotional state into account, and efficient execution of reservation or purchase procedures according to the user's selection.

[0548] "Communication means" refers to the technical configuration used to accurately receive input conditions from the user and transmit them to the server.

[0549] "Information processing means" refers to a combination of methods and apparatus for acquiring information about wine based on user input conditions and performing necessary analyses.

[0550] An "emotion recognition system" is a system for detecting and analyzing a user's emotional state from their text or voice.

[0551] "Display means" refers to a device or method for presenting beverage candidates to a user based on the analysis results.

[0552] "Natural language processing means" refers to technology that adjusts the description of beverage candidates according to the user's emotional state and displays them in appropriate language.

[0553] This invention is a system that recognizes a user's emotions and suggests beverages based on those emotions. The system consists of a server, a terminal, and communication means connecting them.

[0554] The user accesses the system using a terminal. The user inputs information about their beverage selection and provides data in text or voice. The terminal transmits this input data to the server via a communication means (e.g., an internet connection).

[0555] The server performs multiple processes based on the received data. First, it uses a database management system (e.g., MySQL or PostgreSQL) as an information processing tool to obtain beverage information that matches the specified criteria. Then, it uses emotion recognition tools to analyze the emotions from the user's input. This analysis is performed using Natural Language Processing (NLP) technology and speech analysis technology (e.g., Google Cloud Natural Language API or IBM Watson Speech to Text).

[0556] Furthermore, the server uses a generative AI model to formulate optimal suggestions for the user based on emotional information and acquired beverage information. For display purposes, it provides a display optimized for the user's terminal and offers explanations in natural language that respond to emotions. This utilizes natural language processing technology.

[0557] For example, if a user enters "I want to relax today," the server analyzes the emotion of "relaxation" and prioritizes suggesting beverages that match that emotion. This allows the user to make a choice that suits their mood.

[0558] An example of a prompt is, "How can we suggest the best beverage for a user who wants to relax?" This prompt can be input into a generative AI model to obtain appropriate suggestions.

[0559] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0560] Step 1:

[0561] Users log in to the wine concierge system using a terminal and input their preferences via text or voice. This input includes the type of beverage, budget, purpose, and current mood. The terminal transmits the input data to the server via a communication method. The input data is converted to a standard format to facilitate analysis on the server.

[0562] Step 2:

[0563] The server receives user input data sent from the terminal. Based on the received data, it uses information processing tools to retrieve information about beverages using a database management system. In this process, SQL queries are used to extract candidate beverages that match the specified criteria. The input is the user's desired criteria, and the output is a list of beverage information corresponding to those criteria.

[0564] Step 3:

[0565] The server analyzes the user's emotional state using emotion recognition technology, along with the acquired beverage information. Utilizing NLP and speech analysis technologies, it estimates emotions from the user's input and determines whether they are joyful, relaxed, stressed, etc. The input is the user's text or voice data, and the output is the identified emotional state.

[0566] Step 4:

[0567] The server integrates emotional information and beverage information and inputs prompt sentences into the generative AI model. The prompt sentences are designed to obtain beverage suggestions best suited to the emotional state, and the AI ​​model prioritizes or filters the list of candidate beverages. The input is emotional information and a list of beverages, and the output is a list of suggested beverages that match the user's emotions.

[0568] Step 5:

[0569] The server sends optimized beverage options to the terminal for display. The terminal presents the beverage options along with descriptions tailored to the user's mood. The user selects the most suitable beverage based on the displayed information and then reviews the details. The input is an optimized beverage list, and the output is a display of the descriptions and beverage options presented to the user.

[0570] Step 6:

[0571] The user selects whether to purchase or reserve a beverage from the presented options. Once the selection is confirmed, the terminal sends that information back to the server. The server then processes the purchase of the selected beverage through the online payment system. The input is the user's selection data, and the output is a purchase confirmation message.

[0572] (Application Example 2)

[0573] Next, we will explain application example 2. In the following explanation, 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."

[0574] Traditional beverage recommendation systems have faced the challenge of providing a personalized experience that responds to user emotions. In particular, the static nature of the display meant that users could not receive immediate, emotion-based recommendations in real-world settings such as stores. As a result, the user's purchasing experience was not always entirely satisfactory.

[0575] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0576] In this invention, the server includes a device for receiving user input conditions, an information processing device for acquiring and analyzing beverage data, and a device including an emotion engine for analyzing the user's emotional state. This enables users to visually receive emotion-based beverage recommendations using a wearable terminal in a physical space such as a store. This system can provide a more personalized, real-time purchasing experience and improve user satisfaction.

[0577] A "device for receiving user input conditions" is a device that receives the conditions and preferences selected by the user and transmits them to the system.

[0578] An "information processing device for acquiring and analyzing beverage data" is a device that collects information about various beverages and generates optimized results based on user conditions.

[0579] An "emotion engine that analyzes the user's emotional state" is an analytical device that evaluates the user's emotions and understands the user's psychological state.

[0580] A "display device that suggests recommended beverage candidates" is a display device that shows the user appropriate beverage candidates based on the analyzed results.

[0581] A "wearable device" is a device that a user can wear and use, and it plays a role in seamlessly presenting information in the real world.

[0582] A "communication device" is a device used to exchange information between a system and a wearable terminal or other device, enabling real-time transmission and reception of data.

[0583] To implement this invention, a system is required in which a user, a server, and a wearable terminal work in cooperation. The user uses the wearable terminal to provide input conditions to the system. The wearable terminal receives the input conditions from the user and transmits that information to the server via a communication device.

[0584] The server acquires and analyzes beverage data based on user input conditions received using an information processing device. During this process, the server analyzes the user's emotional state using an emotion engine and selects beverage candidates based on the results. The emotion engine uses specific voice analysis software and text analysis algorithms to classify the user's emotions into categories such as "joy," "surprise," and "sadness." Based on the analyzed emotional state, the server determines the priority of recommended beverages and customizes the information presented to the user.

[0585] A display device integrated into the wearable terminal visually presents the user with the most suitable beverage options transmitted from the server. This allows users to receive personalized recommendations tailored to their emotions on the spot, which is particularly useful in the wine section of physical stores.

[0586] For example, recommending sparkling wine when the user is feeling lighthearted, and a rich red wine when they are feeling calm, can enhance the user experience. Furthermore, by inputting prompts into the generative AI model, the system can perform more refined analysis and enable more accurate recommendations. In this case, an example of a prompt might be: "If the user's emotional state is classified as 'want to relax,' generate which wine is suitable. Please output a description including the wine's characteristics and the reason for the recommendation."

[0587] Implementing such a system will enable a personalized beverage selection experience based on the user's emotions.

[0588] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0589] Step 1:

[0590] The wearable terminal receives input from the user. This input consists of the user's preferences and criteria regarding wine selection. The terminal acquires this information through sensors and a touch interface and prepares to send it to the server.

[0591] Step 2:

[0592] The server receives input conditions sent from the terminal. Next, the server consults the beverage database and retrieves data that matches the conditions. During this process, the server filters similar data and constructs an initial dataset to select the most relevant items.

[0593] Step 3:

[0594] The server analyzes the user's emotional state using an emotion engine based on the received input conditions and beverage data. This process utilizes speech and text emotion analysis software to detect emotions such as joy, surprise, and sadness from the user's input. The output is the analyzed emotional state.

[0595] Step 4:

[0596] Based on the analyzed emotional state, the server re-evaluates the beverage dataset and determines emotion-based priorities. Here, it determines how well the selected beverages match the user's emotions and, as a result, creates a list of optimal beverage candidates.

[0597] Step 5:

[0598] The server sends the generated list of beverage options to a wearable terminal. The terminal visually presents the received data to the user on a display device. In this process, the terminal arranges multiple options in an easy-to-view manner to help the user make an intuitive selection.

[0599] Step 6:

[0600] The user checks the display on the device and selects their preferred beverage. This selection is then sent back to the server via the wearable device. The server confirms the received information and proceeds to the next step, either the purchase or reservation process.

[0601] This will provide a personalized beverage recommendation experience based on emotions.

[0602] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0603] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0604] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0605] [Fourth Embodiment]

[0606] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0607] As shown in Figure 7, the 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.

[0608] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0609] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0610] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0611] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0612] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0613] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0614] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0615] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0616] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0617] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0618] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0619] This invention is a system designed to support users, especially beginners and those with little experience, in choosing wine. The system allows users to input criteria related to wine, and through data analysis based on those criteria, it presents optimal wine candidates, simplifying the selection and purchase process.

[0620] First, the user accesses the LINE official account using their device and requests wine selection via chat. The device receives the user's input criteria and transmits them to the server via communication. The user can input criteria such as budget, preferences, and purpose, thereby defining their detailed wine preferences.

[0621] The server analyzes the received conditions and generates suitable wine candidates using big data about wine. Specifically, the server communicates with a wine database to obtain the characteristics, reviews, and ratings of wines that match the user's conditions, and uses statistical methods through information processing to create a list of optimal candidates.

[0622] Users can view wine options presented by the server on their devices. Each wine includes detailed information such as grape variety, characteristics, price range, and consumer reviews to help users make the best choice. Users can also select their preferred wine from the presented options and complete the purchase or reservation process on their devices.

[0623] The server quickly processes purchases and reservations based on the user's selection and sends a completion notification to the device. In this way, users can efficiently find wines that meet their individual criteria and proceed smoothly through the purchase process. For example, if a user is looking for a red wine under 3000 yen for a home party, the generating AI will select suitable wines from the database, and the server will analyze the information and present it. The user can then use this information to make a purchase decision.

[0624] The following describes the processing flow.

[0625] Step 1:

[0626] The user opens the LINE official account and sends a message via their device to begin the wine selection process. Sending this message initiates interaction with the user.

[0627] Step 2:

[0628] The server receives the user's message and sends a message to the terminal in the form of questions to confirm conditions related to wine selection, such as budget, preferences, and intended use.

[0629] Step 3:

[0630] The user enters specific conditions (e.g., "Budget up to 3000 yen, red wine, for a home party") from their device in response to the presented question and sends them to the server.

[0631] Step 4:

[0632] The server records the user's criteria data received and uses a generative AI to access the wine database. It searches for wine candidates that match the criteria and analyzes the results.

[0633] Step 5:

[0634] Based on the data analyzed by the server, the system selects wine candidates that are considered to be the best fit for the user's criteria and creates a candidate list that includes detailed information about those wines.

[0635] Step 6:

[0636] The server sends a list of candidates to the terminal, displaying them to the user as selectable wine options. This list includes information such as the characteristics, price, and rating of each wine.

[0637] Step 7:

[0638] The user selects their preferred wine from the presented wine options and sends their selection to the server via their device.

[0639] Step 8:

[0640] The server will process the wine reservation or purchase based on the user's selection. If necessary, it will also verify payment information and arrange delivery.

[0641] Step 9:

[0642] The server notifies the terminal of the completion of the reservation or purchase process and sends a confirmation message to the user.

[0643] This entire process allows users to find a wine that perfectly matches their criteria and purchase it smoothly.

[0644] (Example 1)

[0645] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0646] Choosing the optimal beverage by considering various factors is not easy. This is especially true for novice or inexperienced consumers, who find the perfect beverage to suit their needs from a vast array of options. Furthermore, there is a lack of readily available means to ensure a quick and smooth purchase process after selection.

[0647] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0648] In this invention, the server includes communication means for receiving user input conditions, information processing means for acquiring and analyzing beverage data based on said conditions, presentation means for presenting beverage candidates to the user based on the analysis results, means for generating candidates using a generative AI model, and means for selecting candidates that match the user's conditions. This enables the user to efficiently select a beverage that meets their criteria and purchase it smoothly.

[0649] A "user" refers to an individual who uses the system to select and purchase beverages.

[0650] "Input conditions" refer to information that indicates the user's specific requirements, such as the price, type, and intended use of the beverage they desire.

[0651] "Communication method" refers to digital communication technology used to send user input conditions to a server and receive analysis results from the server.

[0652] "Beverage data" refers to a database containing information such as characteristics, reviews, and ratings of wine and other beverages.

[0653] "Analysis" refers to the process of scrutinizing beverage data based on input conditions and deriving the optimal candidate.

[0654] "Information processing means" refers to a combination of software and hardware used to perform analysis, integrate input conditions and beverage data, and generate beverage candidates suitable for the user.

[0655] "Presentation method" refers to an interface for displaying analysis results in an easily understandable way to the user.

[0656] A "generative AI model" refers to artificial intelligence technology used to analyze large-scale data and select beverages that are suitable for the input conditions.

[0657] "Candidates" refers to a list of suggested beverages that users can select based on the input criteria.

[0658] "Selection" refers to the process of choosing the optimal candidate from the analysis results using a generative AI model.

[0659] This invention provides a system that allows users to more easily select and purchase beverages that meet their specific requirements. Users first access the system using a communication terminal and input the desired beverage criteria. For example, a user can input a prompt such as, "Please suggest a sweet red wine under 3000 yen for a home party."

[0660] The terminal receives these input conditions and transmits them to the server via communication means. The server uses information processing means to analyze the received conditions. This means includes a wide range of databases on wine and other beverages, from which the server retrieves relevant information.

[0661] The server then uses a generative AI model to generate beverage candidates that meet the specified criteria. This AI model analyzes beverage data and outputs the most suitable candidates that satisfy the user's input conditions. For example, the database contains information such as beverage type, price range, and consumer reviews, and this information is combined to narrow down the recommended beverages.

[0662] As a result, the server sends a list of beverage candidates generated based on the analysis to the terminal. The terminal presents this list to the user and displays detailed information for each candidate. Based on this information, the user can easily select the beverage that best suits them.

[0663] Once the user selects a beverage, the terminal sends that information back to the server, and the purchase process is expedited. The server completes the reservation or purchase arrangement and sends a completion notification back to the terminal. The user can obtain their beverage efficiently as the entire process proceeds smoothly.

[0664] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0665] Step 1:

[0666] The user initiates communication using their device and enters prompts regarding beverage selection. They might enter specific criteria such as, "Please suggest a sweet red wine under 3000 yen for a home party." The entered information is then transmitted from the device to the server via a communication device.

[0667] Step 2:

[0668] The server analyzes the user input conditions received from the terminal. For analysis, the input data is first taken into an information processing system and compared with a beverage database. The database stores various beverage varieties, price ranges, reviews, etc., and the server retrieves this data and compares it with the user's conditions.

[0669] Step 3:

[0670] The server generates beverage candidates that best match the user's input conditions based on data acquired using a generative AI model. The AI ​​model analyzes large-scale data to narrow down the best candidates that match the input conditions. These conditions include, for example, a specific price range or taste characteristics.

[0671] Step 4:

[0672] The server sends a list of generated beverage candidates to the terminal. This list includes detailed information such as wine variety, characteristics, price, and consumer reviews. The terminal presents this information to the user, allowing them to review the candidates.

[0673] Step 5:

[0674] The user selects the beverage that best suits their preferences from the presented options. Once the selection is complete, the device sends the selection information to the server. The server then prepares to process the purchase.

[0675] Step 6:

[0676] The server quickly processes purchases and arranges reservations based on the user's selections. Once the process is complete, the server sends a completion notification to the terminal. The terminal displays this notification to the user, informing them that the purchase process has been completed smoothly.

[0677] (Application Example 1)

[0678] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0679] Modern beverage stores face challenges such as difficulty for customers to choose the flavored beverage best suited to their preferences and needs, and long waiting times for efficient beverage purchases. This is especially true for first-time customers or those unfamiliar with beverage selection, who may find themselves overwhelmed by the sheer volume of information and take too long to make a decision.

[0680] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0681] In this invention, the server includes communication means for receiving user input conditions, information processing means for acquiring and analyzing flavor beverage data based on those conditions, and display means for guiding the user to flavor beverage candidates and their in-store locations based on the analysis results. This allows customers to easily select and efficiently purchase flavor beverages that suit their preferences.

[0682] "User input conditions" refer to information such as the user's preferences, intended use, and budget when selecting a flavored beverage.

[0683] "Communication means" refers to the technology and devices used to receive conditions entered by the user and transmit them to the server.

[0684] "Flavor beverage data" refers to database information containing detailed information about a specific beverage, such as its type, characteristics, and evaluation.

[0685] "Information processing means" refers to a computer system or program for acquiring and analyzing flavor beverage data based on user input conditions.

[0686] "Display means" refers to the interface of a display or mobile device that presents information to the user based on the analysis results.

[0687] "Guiding users to the location within the store" refers to navigation technology that accurately communicates the location of the product selected by the user within the store.

[0688] A "wireless communication device" is a device used to acquire customer location information within a store and communicate with a server.

[0689] "Reservation procedures" refer to systemic processes that allow customers to reserve their chosen flavored beverages in advance, thereby increasing the efficiency of their purchase.

[0690] To implement this invention, a system is built that uses a smartphone application to improve the customer experience at stores selling flavored beverages. Specifically, the following hardware and software are used.

[0691] hardware

[0692] Smartphone: A mobile device used by customers, which is used to input and select information by operating apps.

[0693] Wireless communication devices: These include beacons and Wi-Fi routers used to track customer locations within a store.

[0694] software

[0695] Mobile application (iOS / Android): This is an app that customers install and use on their smartphones. The app accepts user input and presents suggested flavored beverages.

[0696] Backend server: This server system analyzes flavor beverage data based on user conditions and returns the results to the application.

[0697] Generative AI model: This is a machine learning model used for analysis to select the most suitable flavored beverage candidate based on customer input conditions.

[0698] Data processing

[0699] The user input received by the terminal is sent to the backend server. The server uses a generative AI model to analyze flavor beverage data based on the conditions and select the best candidate. The selection result is sent to the mobile application and presented to the customer. In addition, the customer's location within the store is identified via wireless communication equipment, and the user is guided to the location of the selected product.

[0700] For example, if a user enters "a refreshing flavored beverage, under 500 yen" as selection criteria, the system analyzes the relevant flavored beverages and presents three options along with in-store displays, enabling quick selection and purchase.

[0701] Example of a prompt

[0702] "Create a new feature for a smartphone application that suggests the optimal flavored beverage based on budget, preferences, and intended use, and devise ways to improve the customer experience in physical stores."

[0703] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0704] Step 1:

[0705] The user launches a smartphone application and enters their preferences, intended use, and budget as criteria for a flavored beverage. The entered data is sent from the user's device to a backend server based on the selected criteria.

[0706] Step 2:

[0707] The server uses a generative AI model to analyze the user's input conditions. This analysis queries a flavor beverage database to select relevant candidates. The database contains information such as the characteristics and price of each product. As a result of the analysis, a list of products is generated.

[0708] Step 3:

[0709] The server generates a list of beverage options and sends it to the user's terminal. At the same time, detailed information about each option (characteristics, price, ratings, etc.) is also sent, allowing the user to consider each choice.

[0710] Step 4:

[0711] The user selects their preferred beverage from the presented options. The selected data is sent back to the server, which is then prepared to process the reservation or purchase.

[0712] Step 5:

[0713] Based on the user's selection, the server uses wireless communication equipment within the store to determine the customer's location and guides the user to the exact location of the shelf where the beverage is placed.

[0714] Step 6:

[0715] The user moves to a designated shelf within the store, confirms or picks up their selected beverage. This completes the user's selection process and the purchase.

[0716] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0717] This invention relates to a wine concierge system incorporating an emotion engine that recognizes the user's emotions. This system can suggest the most suitable wine candidates based on conditions provided by the user, and in the process, it can analyze the user's emotions and adjust the recommendations accordingly.

[0718] First, the user accesses the system using a terminal and provides information about their wine selection. The conditions entered by the user are sent to the server via communication. Based on these conditions, the server uses an emotion engine to evaluate the user's emotional state. The emotion engine detects emotions such as joy, surprise, sadness, and anger from the user's text input and voice tone.

[0719] The server analyzes emotional information obtained from the emotion engine and user input conditions using information processing tools to select the most suitable wine candidates. Specifically, it performs unique prioritization and filtering of the selected wine candidates according to the emotional state. Furthermore, it provides the user with the optimal experience by expressing the descriptions of the selected candidates in a tone appropriate to their emotions.

[0720] Users can review the wine options presented on their device and make a selection based on the displayed characteristics and ratings. Based on the user's selection, the server executes the wine reservation or purchase process. For example, if the system determines that the user is experiencing stress, it can use an emotion engine to prioritize suggesting wines that are believed to have a relaxing effect. In this way, the system aims to provide a personalized wine purchasing experience by considering the user's psychological state.

[0721] The following describes the processing flow.

[0722] Step 1:

[0723] The user accesses the LINE official account using their device and sends a message to begin the wine selection process. This initiates interaction between the user and the system.

[0724] Step 2:

[0725] The server receives the user's message and sends a message to the terminal asking for necessary information (budget, preferences, intended use, etc.). At the same time, it activates an emotion engine to analyze the user's initial emotional state.

[0726] Step 3:

[0727] The user enters detailed wine specifications via their device and sends them as a message. During this process, the emotion engine analyzes the user's input and voice tone to determine their emotional state.

[0728] Step 4:

[0729] The server integrates and analyzes the user's conditional data and emotional state using information processing tools to select the most suitable wine candidate. It prioritizes the candidates and adjusts the characteristics of the suggested wines according to the emotional state.

[0730] Step 5:

[0731] The server sends the selected wine candidates and their detailed information to the user's terminal for display. During this process, the candidates are described using emotionally charged tones and language, providing suggestions that resonate with the user's emotions.

[0732] Step 6:

[0733] The user selects their desired wine from a displayed wine list and sends their selection to the server via their device.

[0734] Step 7:

[0735] The server receives the user's selection and proceeds with the wine reservation or purchase process, while sending additional support messages tailored to the user's emotions.

[0736] Step 8:

[0737] The server notifies the user's device when the reservation or purchase process is complete and provides a final confirmation message. This allows the user to obtain the perfect wine that reflects their mood.

[0738] (Example 2)

[0739] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0740] Traditionally, when users selected beverages, many systems provided only general information without considering their individual emotional states. This made it difficult for users to make optimal choices based on their current psychological state. Furthermore, the lack of appropriate product suggestions tailored to their emotions resulted in a less-than-satisfactory user experience.

[0741] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0742] In this invention, the server includes communication means for receiving user input conditions, information processing means for acquiring and analyzing information about wine based on those conditions, and emotion recognition means for detecting and analyzing the user's emotional state. This enables personalized beverage recommendations that take the user's emotional state into account, and efficient execution of reservation or purchase procedures according to the user's selection.

[0743] "Communication means" refers to the technical configuration used to accurately receive input conditions from the user and transmit them to the server.

[0744] "Information processing means" refers to a combination of methods and apparatus for acquiring information about wine based on user input conditions and performing necessary analyses.

[0745] An "emotion recognition system" is a system for detecting and analyzing a user's emotional state from their text or voice.

[0746] "Display means" refers to a device or method for presenting beverage candidates to a user based on the analysis results.

[0747] "Natural language processing means" refers to technology that adjusts the description of beverage candidates according to the user's emotional state and displays them in appropriate language.

[0748] This invention is a system that recognizes a user's emotions and suggests beverages based on those emotions. The system consists of a server, a terminal, and communication means connecting them.

[0749] The user accesses the system using a terminal. The user inputs information about their beverage selection and provides data in text or voice. The terminal transmits this input data to the server via a communication means (e.g., an internet connection).

[0750] The server performs multiple processes based on the received data. First, it uses a database management system (e.g., MySQL or PostgreSQL) as an information processing tool to obtain beverage information that matches the specified criteria. Then, it uses emotion recognition tools to analyze the emotions from the user's input. This analysis is performed using Natural Language Processing (NLP) technology and speech analysis technology (e.g., Google Cloud Natural Language API or IBM Watson Speech to Text).

[0751] Furthermore, the server uses a generative AI model to formulate optimal suggestions for the user based on emotional information and acquired beverage information. For display purposes, it provides a display optimized for the user's terminal and offers explanations in natural language that respond to emotions. This utilizes natural language processing technology.

[0752] For example, if a user enters "I want to relax today," the server analyzes the emotion of "relaxation" and prioritizes suggesting beverages that match that emotion. This allows the user to make a choice that suits their mood.

[0753] An example of a prompt is, "How can we suggest the best beverage for a user who wants to relax?" This prompt can be input into a generative AI model to obtain appropriate suggestions.

[0754] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0755] Step 1:

[0756] Users log in to the wine concierge system using a terminal and input their preferences via text or voice. This input includes the type of beverage, budget, purpose, and current mood. The terminal transmits the input data to the server via a communication method. The input data is converted to a standard format to facilitate analysis on the server.

[0757] Step 2:

[0758] The server receives user input data sent from the terminal. Based on the received data, it uses information processing tools to retrieve information about beverages using a database management system. In this process, SQL queries are used to extract candidate beverages that match the specified criteria. The input is the user's desired criteria, and the output is a list of beverage information corresponding to those criteria.

[0759] Step 3:

[0760] The server analyzes the user's emotional state using emotion recognition technology, along with the acquired beverage information. Utilizing NLP and speech analysis technologies, it estimates emotions from the user's input and determines whether they are joyful, relaxed, stressed, etc. The input is the user's text or voice data, and the output is the identified emotional state.

[0761] Step 4:

[0762] The server integrates emotional information and beverage information and inputs prompt sentences into the generative AI model. The prompt sentences are designed to obtain beverage suggestions best suited to the emotional state, and the AI ​​model prioritizes or filters the list of candidate beverages. The input is emotional information and a list of beverages, and the output is a list of suggested beverages that match the user's emotions.

[0763] Step 5:

[0764] The server sends optimized beverage options to the terminal for display. The terminal presents the beverage options along with descriptions tailored to the user's mood. The user selects the most suitable beverage based on the displayed information and then reviews the details. The input is an optimized beverage list, and the output is a display of the descriptions and beverage options presented to the user.

[0765] Step 6:

[0766] The user selects whether to purchase or reserve a beverage from the presented options. Once the selection is confirmed, the terminal sends that information back to the server. The server then processes the purchase of the selected beverage through the online payment system. The input is the user's selection data, and the output is a purchase confirmation message.

[0767] (Application Example 2)

[0768] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0769] Traditional beverage recommendation systems have faced the challenge of providing a personalized experience that responds to user emotions. In particular, the static nature of the display meant that users could not receive immediate, emotion-based recommendations in real-world settings such as stores. As a result, the user's purchasing experience was not always entirely satisfactory.

[0770] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0771] In this invention, the server includes a device for receiving user input conditions, an information processing device for acquiring and analyzing beverage data, and a device including an emotion engine for analyzing the user's emotional state. This enables users to visually receive emotion-based beverage recommendations using a wearable terminal in a physical space such as a store. This system can provide a more personalized, real-time purchasing experience and improve user satisfaction.

[0772] A "device for receiving user input conditions" is a device that receives the conditions and preferences selected by the user and transmits them to the system.

[0773] An "information processing device for acquiring and analyzing beverage data" is a device that collects information about various beverages and generates optimized results based on user conditions.

[0774] An "emotion engine that analyzes the user's emotional state" is an analytical device that evaluates the user's emotions and understands the user's psychological state.

[0775] A "display device that suggests recommended beverage candidates" is a display device that shows the user appropriate beverage candidates based on the analyzed results.

[0776] A "wearable device" is a device that a user can wear and use, and it plays a role in seamlessly presenting information in the real world.

[0777] A "communication device" is a device used to exchange information between a system and a wearable terminal or other device, enabling real-time transmission and reception of data.

[0778] To implement this invention, a system is required in which a user, a server, and a wearable terminal work in cooperation. The user uses the wearable terminal to provide input conditions to the system. The wearable terminal receives the input conditions from the user and transmits that information to the server via a communication device.

[0779] The server acquires and analyzes beverage data based on user input conditions received using an information processing device. During this process, the server analyzes the user's emotional state using an emotion engine and selects beverage candidates based on the results. The emotion engine uses specific voice analysis software and text analysis algorithms to classify the user's emotions into categories such as "joy," "surprise," and "sadness." Based on the analyzed emotional state, the server determines the priority of recommended beverages and customizes the information presented to the user.

[0780] A display device integrated into the wearable terminal visually presents the user with the most suitable beverage options transmitted from the server. This allows users to receive personalized recommendations tailored to their emotions on the spot, which is particularly useful in the wine section of physical stores.

[0781] For example, recommending sparkling wine when the user is feeling lighthearted, and a rich red wine when they are feeling calm, can enhance the user experience. Furthermore, by inputting prompts into the generative AI model, the system can perform more refined analysis and enable more accurate recommendations. In this case, an example of a prompt might be: "If the user's emotional state is classified as 'want to relax,' generate which wine is suitable. Please output a description including the wine's characteristics and the reason for the recommendation."

[0782] Implementing such a system will enable a personalized beverage selection experience based on the user's emotions.

[0783] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0784] Step 1:

[0785] The wearable terminal receives input from the user. This input consists of the user's preferences and criteria regarding wine selection. The terminal acquires this information through sensors and a touch interface and prepares to send it to the server.

[0786] Step 2:

[0787] The server receives input conditions sent from the terminal. Next, the server consults the beverage database and retrieves data that matches the conditions. During this process, the server filters similar data and constructs an initial dataset to select the most relevant items.

[0788] Step 3:

[0789] The server analyzes the user's emotional state using an emotion engine based on the received input conditions and beverage data. This process utilizes speech and text emotion analysis software to detect emotions such as joy, surprise, and sadness from the user's input. The output is the analyzed emotional state.

[0790] Step 4:

[0791] Based on the analyzed emotional state, the server re-evaluates the beverage dataset and determines emotion-based priorities. Here, it determines how well the selected beverages match the user's emotions and, as a result, creates a list of optimal beverage candidates.

[0792] Step 5:

[0793] The server sends the generated list of beverage options to a wearable terminal. The terminal visually presents the received data to the user on a display device. In this process, the terminal arranges multiple options in an easy-to-view manner to help the user make an intuitive selection.

[0794] Step 6:

[0795] The user checks the display on the device and selects their preferred beverage. This selection is then sent back to the server via the wearable device. The server confirms the received information and proceeds to the next step, either the purchase or reservation process.

[0796] This will provide a personalized beverage recommendation experience based on emotions.

[0797] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0798] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0799] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0800] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0801] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0802] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0803] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0804] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0805] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0806] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0807] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0808] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0809] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0810] 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.

[0811] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0812] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0813] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0814] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0815] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0816] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0817] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0818] The following is further disclosed regarding the embodiments described above.

[0819] (Claim 1)

[0820] A communication means for receiving user input conditions,

[0821] Information processing means for acquiring and analyzing wine data based on the said conditions,

[0822] A system including a display mechanism that presents wine options to the user based on the analysis results.

[0823] (Claim 2)

[0824] The system according to claim 1, further comprising means for reserving or purchasing wine based on the user's selection.

[0825] (Claim 3)

[0826] The system according to claim 1, characterized in that it displays the characteristics and evaluation of the presented wine candidates to the user.

[0827] "Example 1"

[0828] (Claim 1)

[0829] A communication means for receiving user input conditions,

[0830] Information processing means for acquiring and analyzing beverage data based on the said conditions,

[0831] A presentation means that presents beverage options to the user based on the analysis results,

[0832] A means of generating candidates using a generative AI model,

[0833] A means of selecting candidates that match the user's criteria,

[0834] A system that includes this.

[0835] (Claim 2)

[0836] The system according to claim 1, further comprising means for reserving or purchasing beverages based on the user's selection.

[0837] (Claim 3)

[0838] The system according to claim 1, characterized in that it displays the characteristics and evaluation of the presented beverage candidates to the user.

[0839] "Application Example 1"

[0840] (Claim 1)

[0841] A communication means for receiving user input conditions,

[0842] Information processing means for acquiring and analyzing flavor beverage data based on the said conditions,

[0843] A display means that guides the user to a selection of flavored beverages and their location in the store based on the analysis results,

[0844] A means of sharing customer location information based on wireless communication devices in the store,

[0845] A means for users to reserve flavored beverages and reduce waiting times,

[0846] A system that includes this.

[0847] (Claim 2)

[0848] The system according to claim 1, further comprising means for reserving or purchasing a flavored beverage based on the user's selection.

[0849] (Claim 3)

[0850] The system according to claim 1, characterized in that it displays the characteristics and evaluation of the presented flavor beverage candidates to the user.

[0851] "Example 2 of combining an emotion engine"

[0852] (Claim 1)

[0853] A communication means for receiving user input conditions,

[0854] Information processing means for acquiring and analyzing information about wine based on the said conditions,

[0855] An emotion recognition means for detecting and analyzing the user's emotional state,

[0856] A display means that presents beverage options to the user based on analysis results and emotional state,

[0857] A natural language processing tool that adjusts the descriptions of the presented beverage candidates,

[0858] A system that includes this.

[0859] (Claim 2)

[0860] The system according to claim 1, further comprising means for reserving or purchasing beverages based on user selection.

[0861] (Claim 3)

[0862] The system according to claim 1, characterized in that it displays the characteristics and evaluations of the presented beverage candidates to the user and provides personalized results.

[0863] "Application example 2 when combining with an emotional engine"

[0864] (Claim 1)

[0865] A device that receives user input conditions,

[0866] An information processing device that acquires and analyzes beverage data based on the said conditions,

[0867] A device including an emotion engine that analyzes the user's emotional state,

[0868] A display device that presents a list of beverages to recommend to the user based on the emotional state analyzed by the aforementioned emotion engine,

[0869] A communication device that uses a wearable terminal to visually display beverage options to the user in the real world,

[0870] A system that includes this.

[0871] (Claim 2)

[0872] The system according to claim 1, further comprising means for reserving or purchasing beverages based on the user's selection.

[0873] (Claim 3)

[0874] The system according to claim 1, characterized in that it displays the characteristics and evaluation of the presented beverage candidates to the user. [Explanation of symbols]

[0875] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A communication means for receiving user input conditions, Information processing means for acquiring and analyzing wine data based on the said conditions, A system including a display mechanism that presents wine options to the user based on the analysis results.

2. The system according to claim 1, further comprising means for reserving or purchasing wine based on the user's selection.

3. The system according to claim 1, characterized in that it displays the characteristics and evaluation of the presented wine candidates to the user.

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