system

Abstract

We provide the system. [Solution] A means having a computing device that collects and analyzes individual consumption activity data, A means having a communication device that collects promotional information related to electronic payment methods and notifies the user of it based on individual consumption patterns, It has a display device that shows collected data and promotional information, and means for real-time consumption management, A system that includes this.

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 as a 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] In modern consumer society, it is essential for individuals to effectively utilize electronic payment means. However, it is difficult to find the most suitable information for oneself from a vast amount of expenditure data and diverse promotion information. For this reason, there is a problem that many consumers cannot fully enjoy the convenience of electronic payment means. In addition, the lack of appropriate information provision to improve consumers' financial literacy is also an issue.

Means for Solving the Problems

[0005] This invention provides a system including a computing device that collects and analyzes individual consumption activity data, a communication device that collects promotional information related to electronic payment methods and notifies the user based on individual consumption patterns, and a display device that displays the collected data and promotional information and performs consumption management in real time. This system allows users to understand the optimal payment method according to their spending tendencies and effectively utilize various promotions. Furthermore, it can provide educational content to improve users' financial literacy.

[0006] "Individual consumer activity data" refers to data related to the expenditures incurred when individual consumers purchase goods and services.

[0007] A "processing unit" is a device that acquires data, performs analysis and calculations based on that data, and derives meaningful information.

[0008] "Electronic payment methods" refer to methods of payment other than cash, such as electronic money, credit cards, and mobile payments.

[0009] "Promotional information" refers to information related to campaigns and offers provided to encourage the use of specific services or products.

[0010] A "communication device" is a device that has the function of sending and receiving various types of data.

[0011] A "consumption pattern" is a pattern of behavior that shows the tendencies and characteristics of an individual's spending.

[0012] A "display device" is a device used to present information to a user visually.

[0013] "Real-time consumption management" means instantly tracking and managing ongoing consumption activities.

[0014] "Financial literacy" refers to the knowledge and ability that individuals possess to understand and implement how to handle money and make economic decisions. [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), etc.

[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 aims to effectively manage the consumption activities of individual users and propose the most suitable electronic payment method. It also aims to provide educational content to support the improvement of users' financial literacy. Specific embodiments for implementing this invention are described below.

[0037] Server Processing

[0038] The server is equipped with a computing device that continuously collects and analyzes user spending data. For example, the server classifies each spending item based on the user's spending history and generates spending patterns for each category. Based on these patterns, it provides the user with the most suitable electronic payment methods and the latest promotional information. Promotional information is obtained from external sources via APIs, and those that match the user's spending habits are prioritized.

[0039] Specific example

[0040] The server detects that the user has made significant spending on transportation and dining out in the past month. It then identifies e-money services offering discounts related to these spending and sends that information to the user.

[0041] Terminal processing

[0042] The terminal has a display device that receives information transmitted from the server and presents it visually to the user. The user can manage their spending based on this information. The display device updates spending information in real time, providing an interface that allows the user to easily understand their spending habits. Furthermore, educational content such as videos and articles are available to increase financial knowledge.

[0043] Specific example

[0044] When a user launches the application on their smartphone, their spending for the month is displayed on a dashboard. Furthermore, simulation results for using specific e-money services and videos offering money-saving tips are recommended.

[0045] User actions

[0046] Users manage their spending habits through their devices. Based on reward information provided by the server, they can select electronic payment methods and optimize their spending. They can also exchange information with other users using the forum function.

[0047] Specific example

[0048] The user decides to use electronic money for shopping at a specific supermarket, taking advantage of the reward information displayed on their device. Later, the user shares their experience on a forum and receives similar experiences and advice from other users.

[0049] In this way, the present invention intelligently supports users' consumption activities and promotes the use of electronic payment methods.

[0050] The following describes the processing flow.

[0051] Step 1:

[0052] The server collects daily transaction data from users' bank accounts and e-money accounts. This transaction data includes information such as the date and time of purchase, store name, amount, and category.

[0053] Step 2:

[0054] The server analyzes user spending patterns based on collected transaction data. Specifically, an AI model identifies spending trends and calculates spending percentages for each category. It also identifies user interests from past history and extracts categories that should be targeted for promotion.

[0055] Step 3:

[0056] The server accesses an external promotional database to retrieve the latest promotional information that matches the user's spending patterns. This information includes details about discounts and point-boosting campaigns at specific stores.

[0057] Step 4:

[0058] The terminal visually presents the analysis results and promotional information received from the server to the user in a dashboard format. The dashboard displays spending graphs and guidance on the optimal use of electronic money.

[0059] Step 5:

[0060] Users make decisions to manage their spending based on the information displayed. They aim to save money by checking promotional information and adjusting payment methods and purchase plans.

[0061] Step 6:

[0062] Users view educational content provided through their devices. The goal is to improve their financial literacy and acquire knowledge to enhance their consumer behavior.

[0063] Step 7:

[0064] Users can use the system's forums to share experiences and information with other users, thereby gaining further tips and advice on consumption management.

[0065] (Example 1)

[0066] 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."

[0067] In today's consumer environment, consumers often fail to fully utilize diverse payment methods and a wealth of promotional information. As a result, individual consumers may have difficulty managing their spending and may not be able to engage in effective consumption. Furthermore, there is a current situation where consumers' financial literacy is not sufficiently improved. This invention aims to solve these problems.

[0068] 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.

[0069] In this invention, the server includes means equipped with an information processing device that acquires and analyzes consumer spending activity data; means equipped with a communication device that collects reward information related to electronic payment methods and notifies consumers based on their individual spending trends; means equipped with a display device that displays the acquired data and reward information and performs immediate spending management; and means equipped with a function that optimizes the generated recommendation information using a generation AI model. This enables consumers to effectively utilize optimal payment methods and promotional information while managing their spending in real time. Furthermore, by supporting the improvement of consumers' financial literacy, it is possible to promote smarter spending activities.

[0070] "Consumer activity data" refers to information about consumers' purchasing behavior, including data that shows consumers' spending patterns and purchase history.

[0071] An "information processing device" is an electronic device used to collect, analyze, and store data, and includes computers and servers.

[0072] "Communication equipment" refers to devices that send and receive data and transmit information with consumers, enabling communication via the internet.

[0073] "Display devices" are devices used to output information visually, and include displays and screens.

[0074] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to analyze data and generate new information.

[0075] "Promotional information" refers to information about discounts and benefits that consumers can use when purchasing goods or services.

[0076] This invention is a system aimed at optimally managing consumer spending activities and effectively utilizing electronic payment methods. The system consists of an information processing device, a communication device, and a display device. Specific embodiments of this system are described below.

[0077] The server functions as an information processing device, responsible for collecting, storing, and analyzing consumer spending data. Specifically, the server retrieves bank transaction history, credit card statements, and electronic payment data using APIs and stores them in a database. Data analysis is supported by programming languages ​​such as Python and machine learning algorithms, which visualize consumption patterns and spending trends.

[0078] The terminal, acting as a communication device, receives promotional and spending information from the server. Users can check their spending management information in real time via the terminal's display. The terminal includes smartphones and tablets, and the information is presented graphically to allow users to understand it intuitively. It is also possible to provide educational content to support the improvement of users' financial literacy. The educational content is provided in the form of videos and interactive materials.

[0079] Users can optimize their spending based on the information displayed on their devices. They can use promotional information to, for example, select the appropriate e-money for shopping at a specific store, thereby saving money. They can also use the forum function to exchange opinions with other users and share advice and experiences related to spending.

[0080] The generative AI model dynamically generates optimal promotional information for consumers based on analyzed data. An example of a specific prompt is: "Based on the user's past spending data, please suggest the most suitable e-money promotional information. Please prioritize spending on transportation and dining out." Using this prompt, it becomes possible to provide information tailored to the individual needs of consumers.

[0081] In this way, this system supports consumer spending and promotes the use of more effective electronic payment methods.

[0082] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0083] Step 1:

[0084] The server collects consumer activity data. Inputs include bank transaction history, credit card statements, and electronic payment data. The server retrieves this data via an API and stores it in a database. The data is normalized and standardized for subsequent analysis.

[0085] Step 2:

[0086] The server analyzes the collected data. The input is consumer activity data stored in a database, and the output is spending patterns and trends for each consumer. The server uses machine learning algorithms to analyze the data and visualize spending trends for each category, such as transportation and dining out. The analysis results are visualized and used in subsequent steps.

[0087] Step 3:

[0088] The server generates promotional information using a generative AI model. The input is analyzed consumer spending patterns, and the output is optimal promotional information. The generative AI model dynamically selects the most effective promotions using prompts and lists them.

[0089] Step 4:

[0090] The server sends recommended promotional information to the device. The input is a list of promotions, and the output is a notification to the device. The server pushes the selected promotional information to the user's device in real time.

[0091] Step 5:

[0092] The terminal displays received promotional information to the user. Input is notifications from the server, and output is the visual presentation of information to the user. The terminal uses a graphical interface to display promotional information on a dashboard, making it easy for the user to understand.

[0093] Step 6:

[0094] Users optimize their spending based on the information they receive. Inputs include promotional information displayed on their device and their own spending history. Outputs include an optimized spending plan and selected electronic payment method. Users can leverage reward information to engage in efficient spending.

[0095] (Application Example 1)

[0096] 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."

[0097] In individual consumer activities, there is a need for efficient transaction management and the provision of optimal market information. However, current systems have challenges in adequately analyzing individual user purchasing patterns and insufficient sharing of appropriate educational content and information. Therefore, it is necessary to build a system that more effectively supports users' consumer activities.

[0098] 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.

[0099] In this invention, the server includes means having an information processing device for collecting and analyzing individual transaction data, means having a communication device for acquiring market information related to electronic payment methods and notifying the user of this information based on individual purchasing patterns, and means having a display means for displaying the acquired information and market information, and for performing consumption management immediately. As a result, users can receive optimal market information tailored to their consumption patterns, intelligently manage their own transactions, and share information with other users.

[0100] "Personal transaction data" refers to detailed information about purchases and payments made by a user, including data such as the date and time, amount, and the goods or services used.

[0101] An "information processing device" is a computer that has the function of analyzing collected data and finding specific patterns or trends based on that analysis.

[0102] "Electronic payment methods" refer to electromagnetic methods used to pay for goods and services without using cash or banknotes, and include credit cards, electronic money, and online payments.

[0103] "Market information" refers to various types of information related to current commercial activities, including promotional information, campaigns, discount information, and other content that stimulates consumer purchasing intent.

[0104] A "communication device" is a device used to send and receive data between a server and a user's terminal, and it utilizes wired or wireless network technology.

[0105] A "purchase pattern" is a set of characteristics that indicate a user's consumption tendencies and preferences, derived from their past transactions.

[0106] "Notifying" refers to the act of sending specific information to a user and informing them of that information visually or audibly.

[0107] "Display means" refers to technologies and devices for visually displaying information on screens such as those of computers and smartphones.

[0108] "Immediate consumption management" refers to users being able to grasp information about their own consumption activities in real time and manage it as needed.

[0109] To implement this invention, the server uses an information processing device that collects and analyzes individual transaction data. The information processing device analyzes the user's purchase history stored in the database and extracts specific patterns and purchasing trends. This data analysis reveals the user's individual purchasing patterns, and based on these, optimal market information is obtained.

[0110] Next, the server uses a communication device to notify the user's terminal of the acquired market information. This market information is obtained through an external API, and the server selects and notifies the user of the most relevant information. This information is prioritized based on the user's purchasing patterns and is constantly updated in real time.

[0111] The acquired information is displayed on the user's device. Examples of display methods include smartphones and tablet devices with high-definition displays, ensuring that the information is presented visually and clearly. Based on this information, users can select appropriate transactions and efficiently manage their spending. Furthermore, educational content to improve financial literacy is also displayed on the device, allowing users to deepen their knowledge by viewing videos and articles.

[0112] For example, if a user spends a high amount in a particular category, they can instantly receive discount information and promotions related to that category. This information includes campaign details, duration, and how to use them. Users can then use this information to make financially advantageous choices.

[0113] An example of a prompt using a generative AI model would be: "Suggest available discount promotions based on the user's dining-out spending. If the spending in the dining-out category is $100, please provide the best promotional information for that condition."

[0114] The system based on this invention utilizes data analysis techniques and real-time communication technologies to provide advanced support for users' consumption activities and further offer added value in terms of education.

[0115] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0116] Step 1:

[0117] The server collects users' personal transaction data, including their purchase history and payment information. The server retrieves this data from financial institutions and online stores via the network and stores it in a database. The input is transaction history data, and the output is the transaction data stored in the database.

[0118] Step 2:

[0119] The server analyzes the accumulated transaction data. The information processing device uses algorithms to process the data and extract user purchasing patterns and consumption trends. The processing utilizes data mining techniques, classifying and organizing the data using statistical methods. The input is transaction data stored in the database, and the output is the analyzed purchasing patterns.

[0120] Step 3:

[0121] The server obtains the latest market information via external APIs. This includes promotional information and discount campaigns. Using communication equipment, it collects this information and selects the most suitable information for the user's purchasing patterns. The input is the analyzed purchasing patterns and the acquired market information, and the output is the optimal market information for the user.

[0122] Step 4:

[0123] The server notifies the user's terminal of the selected market information. Promotional information is sent to the user's terminal using a communication method. This information is displayed visually on the terminal, allowing the user to confirm the notification. The input is the selected market information, and the output is the notification information displayed on the terminal.

[0124] Step 5:

[0125] Users manage their spending based on information displayed on their devices. Through the device's interface, they review displayed promotional information and determine which transaction is most advantageous. Here, users make optimal purchasing decisions based on the displayed information. The input is the notification information displayed on the device, and the output is the user's purchasing behavior.

[0126] Step 6:

[0127] Users can view educational content provided on their devices. The devices display educational videos and articles sent from the server, helping users improve their financial knowledge. The input is the educational content from the server, and the output is the user's educational experience.

[0128] In this way, a system is formed in which servers, terminals, and users cooperate to optimize user consumption activities and provide educational value.

[0129] 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.

[0130] This invention relates to a system that recognizes emotions related to a user's consumption activities and provides customized information based on those emotions. The following describes specific embodiments of this invention.

[0131] Server Processing

[0132] The server first acquires user consumption activity data. This data includes the user's spending history and information about purchased items. In addition, the server is equipped with an emotion engine to analyze user emotions from user interaction and behavioral data. The emotion engine analyzes, for example, the language used in reviews and comments, changes in spending, and recent consumption behavior to evaluate the user's emotions.

[0133] Specific example

[0134] If a user makes a large purchase of a product and then posts a negative review, the server analyzes this using an emotion engine and determines that the user's satisfaction level is low.

[0135] Processing of communication devices

[0136] The communication device customizes individual promotional information based on the user's emotions analyzed by the server. By prioritizing and notifying users of campaign information related to categories in which they have shown positive emotions, it further stimulates their purchasing intent.

[0137] Specific example

[0138] If a user has previously expressed high satisfaction with outdoor equipment purchases, the communication device will prioritize notifying them of discount information on new outdoor equipment.

[0139] Terminal processing

[0140] The device has a function to display information that is relevant to the user's emotions in a timely manner. It automatically adjusts the displayed content and interface style according to changes in the user's emotional state. Furthermore, if the device determines that the user's reaction to consumer behavior is not positive, it provides content that offers encouragement or helpful money-saving tips.

[0141] Specific example

[0142] When a user opens an app, if the emotion engine determines that their recent spending habits are causing stress, the device will display content that helps reduce stress or budget management tools.

[0143] In this way, the present invention, which combines an emotion engine, enables the provision of more detailed services tailored to the individual needs of users, thereby improving the consumer experience.

[0144] The following describes the processing flow.

[0145] Step 1:

[0146] The server collects user consumption data and behavioral data such as feedback and reviews provided by users. This data includes the user's spending history, purchased items, and in-store behavior history.

[0147] Step 2:

[0148] The server's emotion engine analyzes collected data and uses natural language processing to assess the user's emotions. It detects the frequency of positive and negative words, as well as sudden changes in spending trends, to determine the user's current emotional state.

[0149] Step 3:

[0150] The communication device creates customized promotional information based on the user's emotional state obtained by the server. It is configured to provide special discount information for products in categories where the user has expressed joy, and relaxation-related product information in areas where the user is experiencing stress.

[0151] Step 4:

[0152] The device displays promotional information and customized content transmitted from the communication device to the user in real time. The displayed content may use different designs and messages than usual based on the determined emotional state.

[0153] Step 5:

[0154] Users can review information and suggestions provided through their devices, purchase products as needed, or create new payment plans. They can also record their feelings about their daily spending habits as feedback.

[0155] Step 6:

[0156] The server receives new feedback from users, analyzes it again using the sentiment engine, and uses it to improve future promotional information. The feedback is reflected in improving the accuracy of information provision and refining sentiment analysis.

[0157] (Example 2)

[0158] 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".

[0159] In today's consumer society, the sheer volume of information related to individual consumer activities makes it difficult to provide personalized and relevant information. Furthermore, promotional information and content that consider users' emotional states are often lacking, highlighting the need for efficient methods to enhance consumer satisfaction.

[0160] 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.

[0161] In this invention, the server includes means having a computing device that collects individual consumer activity data and performs sentiment analysis; means having a communication device that customizes and notifies relevant promotional information for each user based on the analyzed sentiment data; and means having a display device that adjusts the display content and interface according to the user's emotional state and displays the information. This makes it possible to provide individualized information based on the user's emotions and consumption patterns. It also makes it possible to provide services that improve the user's consumption experience.

[0162] "Personal consumption activity data" refers to information about an individual's consumption behavior, such as a user's spending history, purchased items, and transaction dates and times.

[0163] "Sentiment analysis" refers to the process of evaluating a user's emotional state using natural language processing and algorithms based on data such as user posts, reviews, and changes in spending.

[0164] A "processing unit" refers to a computer system or device used for collecting, processing, and analyzing data.

[0165] "Communication device" refers to a device or system that transmits and receives digital information and provides notifications to users.

[0166] A "display device" refers to a device that has a digital screen or interface for providing visual information to a user.

[0167] "Customization" refers to the process of adjusting and optimizing information and services based on the individual user's conditions and needs.

[0168] "Emotional state" refers to the state that represents the user's current psychological or emotional condition.

[0169] This invention relates to a system that provides customized information using a user's personal consumption activity data. The following details the implementation of this system.

[0170] The server collects user consumption activity data. This data is obtained through APIs and databases and includes the user's spending history, purchased items, and related metadata. The server uses a sentiment engine equipped with natural language processing (NLP) technology to perform sentiment analysis using the collected data. The sentiment engine analyzes the context of reviews and comments and evaluates user sentiment. This analysis process uses natural language processing libraries with programming languages ​​such as Python.

[0171] The communication device identifies and customizes promotional information tailored to the user's preferences based on sentiment data analyzed by the server. The selected information is immediately notified to the user. Specifically, the communication device considers the user's past behavior patterns and sends highly relevant campaign information via push notifications or email. Communication interfaces such as the Gmail API may be used in this process.

[0172] The device displays received information in a timely manner. It has the ability to dynamically adjust the UI design and displayed content according to the user's emotional state. Based on the analysis results of the emotion engine, the screen's color scheme and message tone are changed, providing a flexible response that matches the user's mood. For example, the user interface can be varied using frameworks such as React Native.

[0173] This system aims to enrich the user's consumption experience, improving consumer satisfaction through customized information delivery based on sentiment analysis. Furthermore, it uses prompt statements to instruct the generating AI model, enabling even more optimized information delivery. Specific examples of prompt statements used include:

[0174] "If a user has a purchase history of outdoor equipment and has left positive reviews, what kind of promotional information should be sent to them?"

[0175] In this way, the invention combines data analysis technology and communication technology to provide personalized information to individual users, thereby promoting consumer engagement.

[0176] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0177] Step 1:

[0178] The server collects individual consumer activity data. Specifically, it retrieves users' purchase and spending history through APIs and databases, and prepares it as input data for sentiment analysis. This step involves data preprocessing, such as formatting and normalization of the data.

[0179] Step 2:

[0180] The server feeds the collected consumer activity data into an emotion engine to analyze user emotions. This process involves using natural language processing techniques to analyze the context of reviews and comments. The analysis results in scores and metrics that represent the user's emotional state. This output data is used to customize subsequent promotional information.

[0181] Step 3:

[0182] The communication device selects and customizes promotional information suitable for the user based on the results of sentiment analysis. It uses the acquired sentiment data as input to extract relevant campaign and product discount information. This output information is then formatted as promotional content to be notified to the user.

[0183] Step 4:

[0184] The communication device notifies the user's device of customized promotional information. This process involves sending information instantly via push notifications or email. A specific example of this operation is sending notifications in email format using the Gmail API.

[0185] Step 5:

[0186] The device adjusts the content and style of the user interface based on the promotional information it receives, and displays the information accordingly. It receives a sentiment score and notified information as input, and adjusts the color settings of the display screen and the tone of the message before presenting it to the user. This output is visually appealing to the user and may include stress-reducing content or money-saving tips.

[0187] Step 6:

[0188] Users act based on the information displayed. In this step, actions such as clicks and purchases are taken to indicate their reaction to the provided promotions and content. This data is collected again within the system and used for future sentiment analysis and promotion customization.

[0189] (Application Example 2)

[0190] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0191] In individual consumer activities, users often fail to fully understand their own emotional state and purchasing patterns, leading to inappropriate spending. This can result in consumer activities becoming a source of anxiety and stress, making it difficult to enjoy a productive consumer experience. Furthermore, if personalized information tailored to the user's emotions is not provided, it may fail to adequately stimulate their purchasing intent, potentially leading to decreased customer satisfaction.

[0192] 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.

[0193] In this invention, the server includes means having a computing processing unit that collects individual consumption activity data and evaluates the emotional state using an emotion analysis engine; means having a communication device that collects promotional information related to electronic payment methods and provides personalized notifications based on the user's emotional state; and means having a display device that displays the collected data, promotional information, and savings guidelines, and adjusts the interface according to the emotional state, and performs consumption management in real time. This enables intelligent consumption management based on the user's emotional state, reduces stress caused by consumption activities, and improves customer satisfaction.

[0194] "Consumer activity data" refers to information about an individual's spending, including purchase history and product selection information.

[0195] An "emotion analysis engine" refers to software or algorithms that analyze a user's language expressions and consumer behavior to evaluate their emotional state.

[0196] "Personalized notifications" refer to sending individual information and messages tailored to a user's specific emotions or consumption patterns.

[0197] A "processing device" refers to an electronic device or system that performs data analysis and calculations, and includes computers.

[0198] "Communication equipment" refers to devices or systems used for sending and receiving data, and is used to provide information to users via a network.

[0199] A "display device" refers to a device equipped with a screen or display for showing visual information to a user.

[0200] "Real-time consumption management" refers to a process that instantly processes and displays information about a user's consumption activities, and continuously manages and optimizes them.

[0201] "Interface adjustment" refers to dynamically changing the appearance and usability of the user interface in response to the user's emotional state.

[0202] "Savings guidelines" refer to specific advice and tips for users to manage their funds efficiently and reduce unnecessary spending.

[0203] The system implementing this invention mainly consists of a server, a communication device, and a display device. The server collects user consumption activity data and uses an emotion analysis engine to evaluate the user's emotional state from that data. This process uses programming languages ​​such as Python and JavaScript (registered trademark), and artificial intelligence frameworks such as TENSORFLOW (registered trademark) are used for emotion analysis.

[0204] The communication device provides personalized promotional information relevant to the user based on sentiment information obtained from the server. This is achieved by sending push notifications via Firebase Cloud Messaging (FCM). These notifications include information on campaigns and savings tips that are most relevant to the user's emotional state.

[0205] The display device is responsible for dynamically adjusting the interface according to the user's emotional state. Using Python or React Native, the interface style is adjusted to display emotionally relevant information in a timely manner. For example, if a user expresses high satisfaction after purchasing a travel-related product, travel-related promotional information will be prioritized.

[0206] In using the generative AI model, an example of a prompt might be, "Based on this user's recent purchase history and reviews, assess their emotional state and suggest some appropriate saving tips." In this way, the system facilitates the management of consumer activity and emotional state, improving the user's consumer experience.

[0207] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0208] Step 1:

[0209] The server collects user consumption activity data via the network. Inputs include user purchase history, spending amounts, and purchased items. Based on this data, the processing unit organizes the data and extracts consumption trends and patterns.

[0210] Step 2:

[0211] Based on the collected consumption activity data, the server uses an emotion analysis engine to evaluate the user's emotional state. The input is the consumption data organized in the previous step, and the emotion analysis engine uses natural language processing technology to analyze text data such as reviews and comments, and outputs the user's emotions as a numerical value.

[0212] Step 3:

[0213] Based on the user's emotional state analyzed by the server, the communication device customizes promotional information to suit the user's needs. It takes numerical data of the emotional state as input, prioritizes selecting the most relevant advertisements and promotions, and outputs that information.

[0214] Step 4:

[0215] The communication device sends customized promotional information to the user's smartphone via Firebase Cloud Messaging as push notifications. These notifications include money-saving tips and campaign information tailored to the user's current situation, aiming to increase the user's purchasing intent.

[0216] Step 5:

[0217] The device dynamically adjusts the interface style and displayed content to match the user's emotional state based on information obtained from push notifications. This process uses user emotional data and notification content as input, and adjusts the UI using React Native. The output is an interface that is most visually appealing and easy to operate for the user.

[0218] Step 6:

[0219] Ultimately, the device displays savings tips and promotional information on a customized interface for the user. Furthermore, the user experience is enhanced by passing a prompt message, such as "Based on this user's recent purchase history and reviews, assess their emotional state and suggest some appropriate savings tips," to the generating AI model.

[0220] 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.

[0221] 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.

[0222] 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.

[0223] [Second Embodiment]

[0224] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0225] 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.

[0226] 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).

[0227] 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.

[0228] 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.

[0229] 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).

[0230] 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.

[0231] 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.

[0232] 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.

[0233] 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.

[0234] 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.

[0235] 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".

[0236] This invention aims to effectively manage the consumption activities of individual users and propose the most suitable electronic payment method. It also aims to provide educational content to support the improvement of users' financial literacy. Specific embodiments for implementing this invention are described below.

[0237] Server Processing

[0238] The server is equipped with a computing device that continuously collects and analyzes user spending data. For example, the server classifies each spending item based on the user's spending history and generates spending patterns for each category. Based on these patterns, it provides the user with the most suitable electronic payment methods and the latest promotional information. Promotional information is obtained from external sources via APIs, and those that match the user's spending habits are prioritized.

[0239] Specific example

[0240] The server detects that the user has made significant spending on transportation and dining out in the past month. It then identifies e-money services offering discounts related to these spending and sends that information to the user.

[0241] Terminal processing

[0242] The terminal has a display device that receives information transmitted from the server and presents it visually to the user. The user can manage their spending based on this information. The display device updates spending information in real time, providing an interface that allows the user to easily understand their spending habits. Furthermore, educational content such as videos and articles are available to increase financial knowledge.

[0243] Specific example

[0244] When a user launches the application on their smartphone, their spending for the month is displayed on a dashboard. Furthermore, simulation results for using specific e-money services and videos offering money-saving tips are recommended.

[0245] User actions

[0246] Users manage their spending habits through their devices. Based on reward information provided by the server, they can select electronic payment methods and optimize their spending. They can also exchange information with other users using the forum function.

[0247] Specific example

[0248] The user decides to use electronic money for shopping at a specific supermarket, taking advantage of the reward information displayed on their device. Later, the user shares their experience on a forum and receives similar experiences and advice from other users.

[0249] In this way, the present invention intelligently supports users' consumption activities and promotes the use of electronic payment methods.

[0250] The following describes the processing flow.

[0251] Step 1:

[0252] The server collects daily transaction data from users' bank accounts and e-money accounts. This transaction data includes information such as the date and time of purchase, store name, amount, and category.

[0253] Step 2:

[0254] The server analyzes user spending patterns based on collected transaction data. Specifically, an AI model identifies spending trends and calculates spending percentages for each category. It also identifies user interests from past history and extracts categories that should be targeted for promotion.

[0255] Step 3:

[0256] The server accesses an external promotional database to retrieve the latest promotional information that matches the user's spending patterns. This information includes details about discounts and point-boosting campaigns at specific stores.

[0257] Step 4:

[0258] The terminal visually presents the analysis results and promotional information received from the server to the user in a dashboard format. The dashboard displays spending graphs and guidance on the optimal use of electronic money.

[0259] Step 5:

[0260] Users make decisions to manage their spending based on the information displayed. They aim to save money by checking promotional information and adjusting payment methods and purchase plans.

[0261] Step 6:

[0262] Users view educational content provided through their devices. The goal is to improve their financial literacy and acquire knowledge to enhance their consumer behavior.

[0263] Step 7:

[0264] Users can use the system's forums to share experiences and information with other users, thereby gaining further tips and advice on consumption management.

[0265] (Example 1)

[0266] 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."

[0267] In today's consumer environment, consumers often fail to fully utilize diverse payment methods and a wealth of promotional information. As a result, individual consumers may have difficulty managing their spending and may not be able to engage in effective consumption. Furthermore, there is a current situation where consumers' financial literacy is not sufficiently improved. This invention aims to solve these problems.

[0268] 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.

[0269] In this invention, the server includes means equipped with an information processing device that acquires and analyzes consumer spending activity data; means equipped with a communication device that collects reward information related to electronic payment methods and notifies consumers based on their individual spending trends; means equipped with a display device that displays the acquired data and reward information and performs immediate spending management; and means equipped with a function that optimizes the generated recommendation information using a generation AI model. This enables consumers to effectively utilize optimal payment methods and promotional information while managing their spending in real time. Furthermore, by supporting the improvement of consumers' financial literacy, it is possible to promote smarter spending activities.

[0270] "Consumer activity data" refers to information about consumers' purchasing behavior, including data that shows consumers' spending patterns and purchase history.

[0271] An "information processing device" is an electronic device used to collect, analyze, and store data, and includes computers and servers.

[0272] "Communication equipment" refers to devices that send and receive data and transmit information with consumers, enabling communication via the internet.

[0273] "Display devices" are devices used to output information visually, and include displays and screens.

[0274] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to analyze data and generate new information.

[0275] "Promotional information" refers to information about discounts and benefits that consumers can use when purchasing goods or services.

[0276] This invention is a system aimed at optimally managing consumer spending activities and effectively utilizing electronic payment methods. The system consists of an information processing device, a communication device, and a display device. Specific embodiments of this system are described below.

[0277] The server functions as an information processing device, responsible for collecting, storing, and analyzing consumer spending data. Specifically, the server retrieves bank transaction history, credit card statements, and electronic payment data using APIs and stores them in a database. Data analysis is supported by programming languages ​​such as Python and machine learning algorithms, which visualize consumption patterns and spending trends.

[0278] The terminal, acting as a communication device, receives promotional and spending information from the server. Users can check their spending management information in real time via the terminal's display. The terminal includes smartphones and tablets, and the information is presented graphically to allow users to understand it intuitively. It is also possible to provide educational content to support the improvement of users' financial literacy. The educational content is provided in the form of videos and interactive materials.

[0279] Users can optimize their spending based on the information displayed on their devices. They can use promotional information to, for example, select the appropriate e-money for shopping at a specific store, thereby saving money. They can also use the forum function to exchange opinions with other users and share advice and experiences related to spending.

[0280] The generative AI model dynamically generates optimal promotional information for consumers based on analyzed data. An example of a specific prompt is: "Based on the user's past spending data, please suggest the most suitable e-money promotional information. Please prioritize spending on transportation and dining out." Using this prompt, it becomes possible to provide information tailored to the individual needs of consumers.

[0281] In this way, the system supports consumers' consumption activities and promotes the use of more effective electronic payment methods.

[0282] The flow of the specific process in Example 1 will be described using FIG. 11.

[0283] Step 1:

[0284] The server collects consumption activity data. The inputs are bank transaction histories, credit card usage details, and electronic payment data. The server obtains this through an API and stores it in a database. The data is normalized for subsequent analysis and the format is unified.

[0285] Step 2:

[0286] The server analyzes the collected data. The input is the consumption activity data stored in the database, and the output is the expenditure pattern and tendency for each consumer. The server analyzes the data using machine learning algorithms and illustrates the expenditure tendency for each category such as transportation expenses and dining expenses. The analysis results are visualized and used in later steps.

[0287] Step 3:

[0288] The server uses a generative AI model to generate promotion information. The input is the analyzed expenditure pattern of the consumer, and the output is the optimal promotion information. The generative AI model dynamically selects the most effective promotion using a prompt sentence and lists it.

[0289] Step 4:

[0290] The server sends the recommended promotion information to the terminal. The input is the promotion list, and the output is a notification to the terminal. The server pushes the selected promotion information to the user's terminal in real time.

[0291] Step 5:

[0292] The terminal displays received promotional information to the user. Input is notifications from the server, and output is the visual presentation of information to the user. The terminal uses a graphical interface to display promotional information on a dashboard, making it easy for the user to understand.

[0293] Step 6:

[0294] Users optimize their spending based on the information they receive. Inputs include promotional information displayed on their device and their own spending history. Outputs include an optimized spending plan and selected electronic payment method. Users can leverage reward information to engage in efficient spending.

[0295] (Application Example 1)

[0296] 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 glasses 214 will be referred to as the "terminal."

[0297] In individual consumer activities, there is a need for efficient transaction management and the provision of optimal market information. However, current systems have challenges in adequately analyzing individual user purchasing patterns and insufficient sharing of appropriate educational content and information. Therefore, it is necessary to build a system that more effectively supports users' consumer activities.

[0298] 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.

[0299] In this invention, the server includes means having an information processing device for collecting and analyzing individual transaction data, means having a communication device for acquiring market information related to electronic payment methods and notifying the user of this information based on individual purchasing patterns, and means having a display means for displaying the acquired information and market information, and for performing consumption management immediately. As a result, users can receive optimal market information tailored to their consumption patterns, intelligently manage their own transactions, and share information with other users.

[0300] "Personal transaction data" refers to detailed information about purchases and payments made by a user, including data such as the date and time, amount, and the goods or services used.

[0301] An "information processing device" is a computer that has the function of analyzing collected data and finding specific patterns or trends based on that analysis.

[0302] "Electronic payment methods" refer to electromagnetic methods used to pay for goods and services without using cash or banknotes, and include credit cards, electronic money, and online payments.

[0303] "Market information" refers to various types of information related to current commercial activities, including promotional information, campaigns, discount information, and other content that stimulates consumer purchasing intent.

[0304] A "communication device" is a device used to send and receive data between a server and a user's terminal, and it utilizes wired or wireless network technology.

[0305] A "purchase pattern" is a set of characteristics that indicate a user's consumption tendencies and preferences, derived from their past transactions.

[0306] "Notifying" refers to the act of sending specific information to a user and informing them of that information visually or audibly.

[0307] The "display means" refers to the technology or device for visually displaying information on the screen of a computer, smartphone, or the like.

[0308] "Performing immediate consumption management" means that the user grasps information about their own consumption activities in real time and appropriately conducts such management.

[0309] To implement this invention, the server uses an information processing device that collects and analyzes personal transaction data. The information processing device analyzes the user's purchase history stored in a database and extracts specific patterns and purchase trends. Through this data analysis, the user's individual purchase patterns become clear, and based on this, optimal market information is obtained.

[0310] Next, the server uses a communication device to notify the user's terminal of the obtained market information. The market information obtains the latest promotion information through an external API, selects information highly relevant to the user, and notifies it. This information is set with priorities based on the user's purchase patterns and is constantly updated in real time.

[0311] The information obtained is displayed on the terminal used by the user. The display means can take, for example, a smartphone or a tablet terminal equipped with a high-definition display, and the information is presented visually in an easy-to-understand manner. Based on this information, the user can select appropriate transactions and efficiently manage their consumption activities. Also, on the terminal, educational content for improving financial literacy is displayed, and the user can deepen their knowledge by viewing videos and articles.

[0312] As a specific example, when the user has a high expenditure on a specific category, they can immediately receive discount information and promotions related to that category. This information includes the details of the campaign, the offering period, and the method of use. The user can make economically advantageous choices using this information.

[0313] An example of a prompt using a generative AI model would be: "Suggest available discount promotions based on the user's dining-out spending. If the spending in the dining-out category is $100, please provide the best promotional information for that condition."

[0314] The system based on this invention utilizes data analysis techniques and real-time communication technologies to provide advanced support for users' consumption activities and further offer added value in terms of education.

[0315] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0316] Step 1:

[0317] The server collects users' personal transaction data, including their purchase history and payment information. The server retrieves this data from financial institutions and online stores via the network and stores it in a database. The input is transaction history data, and the output is the transaction data stored in the database.

[0318] Step 2:

[0319] The server analyzes the accumulated transaction data. The information processing device uses algorithms to process the data and extract user purchasing patterns and consumption trends. The processing utilizes data mining techniques, classifying and organizing the data using statistical methods. The input is transaction data stored in the database, and the output is the analyzed purchasing patterns.

[0320] Step 3:

[0321] The server obtains the latest market information via external APIs. This includes promotional information and discount campaigns. Using communication equipment, it collects this information and selects the most suitable information for the user's purchasing patterns. The input is the analyzed purchasing patterns and the acquired market information, and the output is the optimal market information for the user.

[0322] Step 4:

[0323] The server notifies the user's terminal of the selected market information. Promotional information is sent to the user's terminal using a communication method. This information is displayed visually on the terminal, allowing the user to confirm the notification. The input is the selected market information, and the output is the notification information displayed on the terminal.

[0324] Step 5:

[0325] Users manage their spending based on information displayed on their devices. Through the device's interface, they review displayed promotional information and determine which transaction is most advantageous. Here, users make optimal purchasing decisions based on the displayed information. The input is the notification information displayed on the device, and the output is the user's purchasing behavior.

[0326] Step 6:

[0327] Users can view educational content provided on their devices. The devices display educational videos and articles sent from the server, helping users improve their financial knowledge. The input is the educational content from the server, and the output is the user's educational experience.

[0328] In this way, a system is formed in which servers, terminals, and users cooperate to optimize user consumption activities and provide educational value.

[0329] 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.

[0330] This invention relates to a system that recognizes emotions related to a user's consumption activities and provides customized information based on those emotions. The following describes specific embodiments of this invention.

[0331] Server Processing

[0332] The server first acquires user consumption activity data. This data includes the user's spending history and information about purchased items. In addition, the server is equipped with an emotion engine to analyze user emotions from user interaction and behavioral data. The emotion engine analyzes, for example, the language used in reviews and comments, changes in spending, and recent consumption behavior to evaluate the user's emotions.

[0333] Specific example

[0334] If a user makes a large purchase of a product and then posts a negative review, the server analyzes this using an emotion engine and determines that the user's satisfaction level is low.

[0335] Processing of communication devices

[0336] The communication device customizes individual promotional information based on the user's emotions analyzed by the server. By prioritizing and notifying users of campaign information related to categories in which they have shown positive emotions, it further stimulates their purchasing intent.

[0337] Specific example

[0338] If a user has previously expressed high satisfaction with outdoor equipment purchases, the communication device will prioritize notifying them of discount information on new outdoor equipment.

[0339] Terminal processing

[0340] The device has a function to display information that is relevant to the user's emotions in a timely manner. It automatically adjusts the displayed content and interface style according to changes in the user's emotional state. Furthermore, if the device determines that the user's reaction to consumer behavior is not positive, it provides content that offers encouragement or helpful money-saving tips.

[0341] Specific example

[0342] When a user opens an app, if the emotion engine determines that their recent spending habits are causing stress, the device will display content that helps reduce stress or budget management tools.

[0343] In this way, the present invention, which combines an emotion engine, enables the provision of more detailed services tailored to the individual needs of users, thereby improving the consumer experience.

[0344] The following describes the processing flow.

[0345] Step 1:

[0346] The server collects user consumption data and behavioral data such as feedback and reviews provided by users. This data includes the user's spending history, purchased items, and in-store behavior history.

[0347] Step 2:

[0348] The server's emotion engine analyzes collected data and uses natural language processing to assess the user's emotions. It detects the frequency of positive and negative words, as well as sudden changes in spending trends, to determine the user's current emotional state.

[0349] Step 3:

[0350] The communication device creates customized promotional information based on the user's emotional state obtained by the server. It is configured to provide special discount information for products in categories where the user has expressed joy, and relaxation-related product information in areas where the user is experiencing stress.

[0351] Step 4:

[0352] The device displays promotional information and customized content transmitted from the communication device to the user in real time. The displayed content may use different designs and messages than usual based on the determined emotional state.

[0353] Step 5:

[0354] Users can review information and suggestions provided through their devices, purchase products as needed, or create new payment plans. They can also record their feelings about their daily spending habits as feedback.

[0355] Step 6:

[0356] The server receives new feedback from users, analyzes it again using the sentiment engine, and uses it to improve future promotional information. The feedback is reflected in improving the accuracy of information provision and refining sentiment analysis.

[0357] (Example 2)

[0358] 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".

[0359] In today's consumer society, the sheer volume of information related to individual consumer activities makes it difficult to provide personalized and relevant information. Furthermore, promotional information and content that consider users' emotional states are often lacking, highlighting the need for efficient methods to enhance consumer satisfaction.

[0360] 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.

[0361] In this invention, the server includes means having a computing device that collects individual consumer activity data and performs sentiment analysis; means having a communication device that customizes and notifies relevant promotional information for each user based on the analyzed sentiment data; and means having a display device that adjusts the display content and interface according to the user's emotional state and displays the information. This makes it possible to provide individualized information based on the user's emotions and consumption patterns. It also makes it possible to provide services that improve the user's consumption experience.

[0362] "Personal consumption activity data" refers to information about an individual's consumption behavior, such as a user's spending history, purchased items, and transaction dates and times.

[0363] "Sentiment analysis" refers to the process of evaluating a user's emotional state using natural language processing and algorithms based on data such as user posts, reviews, and changes in spending.

[0364] A "processing unit" refers to a computer system or device used for collecting, processing, and analyzing data.

[0365] "Communication device" refers to a device or system that transmits and receives digital information and provides notifications to users.

[0366] A "display device" refers to a device that has a digital screen or interface for providing visual information to a user.

[0367] "Customization" refers to the process of adjusting and optimizing information and services based on the individual user's conditions and needs.

[0368] "Emotional state" refers to the state that represents the user's current psychological or emotional condition.

[0369] This invention relates to a system that provides customized information using a user's personal consumption activity data. The following details the implementation of this system.

[0370] The server collects user consumption activity data. This data is obtained through APIs and databases and includes the user's spending history, purchased items, and related metadata. The server uses a sentiment engine equipped with natural language processing (NLP) technology to perform sentiment analysis using the collected data. The sentiment engine analyzes the context of reviews and comments and evaluates user sentiment. This analysis process uses natural language processing libraries with programming languages ​​such as Python.

[0371] The communication device identifies and customizes promotional information tailored to the user's preferences based on sentiment data analyzed by the server. The selected information is immediately notified to the user. Specifically, the communication device considers the user's past behavior patterns and sends highly relevant campaign information via push notifications or email. Communication interfaces such as the Gmail API may be used in this process.

[0372] The device displays received information in a timely manner. It has the ability to dynamically adjust the UI design and displayed content according to the user's emotional state. Based on the analysis results of the emotion engine, the screen's color scheme and message tone are changed, providing a flexible response that matches the user's mood. For example, the user interface can be varied using frameworks such as React Native.

[0373] This system aims to enrich the user's consumption experience, improving consumer satisfaction through customized information delivery based on sentiment analysis. Furthermore, it uses prompt statements to instruct the generating AI model, enabling even more optimized information delivery. Specific examples of prompt statements used include:

[0374] "If a user has a purchase history of outdoor equipment and has left positive reviews, what kind of promotional information should be sent to them?"

[0375] In this way, the invention combines data analysis technology and communication technology to provide personalized information to individual users, thereby promoting consumer engagement.

[0376] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0377] Step 1:

[0378] The server collects individual consumer activity data. Specifically, it retrieves users' purchase and spending history through APIs and databases, and prepares it as input data for sentiment analysis. This step involves data preprocessing, such as formatting and normalization of the data.

[0379] Step 2:

[0380] The server feeds the collected consumer activity data into an emotion engine to analyze user emotions. This process involves using natural language processing techniques to analyze the context of reviews and comments. The analysis results in scores and metrics that represent the user's emotional state. This output data is used to customize subsequent promotional information.

[0381] Step 3:

[0382] The communication device selects and customizes promotional information suitable for the user based on the results of sentiment analysis. It uses the acquired sentiment data as input to extract relevant campaign and product discount information. This output information is then formatted as promotional content to be notified to the user.

[0383] Step 4:

[0384] The communication device notifies the user's device of customized promotional information. This process involves sending information instantly via push notifications or email. A specific example of this operation is sending notifications in email format using the Gmail API.

[0385] Step 5:

[0386] The device adjusts the content and style of the user interface based on the promotional information it receives, and displays the information accordingly. It receives a sentiment score and notified information as input, and adjusts the color settings of the display screen and the tone of the message before presenting it to the user. This output is visually appealing to the user and may include stress-reducing content or money-saving tips.

[0387] Step 6:

[0388] Users act based on the information displayed. In this step, actions such as clicks and purchases are taken to indicate their reaction to the provided promotions and content. This data is collected again within the system and used for future sentiment analysis and promotion customization.

[0389] (Application Example 2)

[0390] 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."

[0391] In individual consumer activities, users often fail to fully understand their own emotional state and purchasing patterns, leading to inappropriate spending. This can result in consumer activities becoming a source of anxiety and stress, making it difficult to enjoy a productive consumer experience. Furthermore, if personalized information tailored to the user's emotions is not provided, it may fail to adequately stimulate their purchasing intent, potentially leading to decreased customer satisfaction.

[0392] 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.

[0393] In this invention, the server includes means having a computing processing unit that collects individual consumption activity data and evaluates the emotional state using an emotion analysis engine; means having a communication device that collects promotional information related to electronic payment methods and provides personalized notifications based on the user's emotional state; and means having a display device that displays the collected data, promotional information, and savings guidelines, and adjusts the interface according to the emotional state, and performs consumption management in real time. This enables intelligent consumption management based on the user's emotional state, reduces stress caused by consumption activities, and improves customer satisfaction.

[0394] "Consumer activity data" refers to information about an individual's spending, including purchase history and product selection information.

[0395] An "emotion analysis engine" refers to software or algorithms that analyze a user's language expressions and consumer behavior to evaluate their emotional state.

[0396] "Personalized notifications" refer to sending individual information and messages tailored to a user's specific emotions or consumption patterns.

[0397] A "processing device" refers to an electronic device or system that performs data analysis and calculations, and includes computers.

[0398] "Communication equipment" refers to devices or systems used for sending and receiving data, and is used to provide information to users via a network.

[0399] A "display device" refers to a device equipped with a screen or display for showing visual information to a user.

[0400] "Real-time consumption management" refers to a process that instantly processes and displays information about a user's consumption activities, and continuously manages and optimizes them.

[0401] "Interface adjustment" refers to dynamically changing the appearance and usability of the user interface in response to the user's emotional state.

[0402] "Savings guidelines" refer to specific advice and tips for users to manage their funds efficiently and reduce unnecessary spending.

[0403] The system implementing this invention mainly consists of a server, a communication device, and a display device. The server collects user consumption activity data and uses an emotion analysis engine to evaluate the user's emotional state from that data. This process uses programming languages ​​such as Python and JavaScript, and artificial intelligence frameworks such as TensorFlow are utilized for emotion analysis.

[0404] The communication device provides personalized promotional information relevant to the user based on sentiment information obtained from the server. This is achieved by sending push notifications via Firebase Cloud Messaging (FCM). These notifications include information on campaigns and savings tips that are most relevant to the user's emotional state.

[0405] The display device is responsible for dynamically adjusting the interface according to the user's emotional state. Using Python or React Native, the interface style is adjusted to display emotionally relevant information in a timely manner. For example, if a user expresses high satisfaction after purchasing a travel-related product, travel-related promotional information will be prioritized.

[0406] In using the generative AI model, an example of a prompt might be, "Based on this user's recent purchase history and reviews, assess their emotional state and suggest some appropriate saving tips." In this way, the system facilitates the management of consumer activity and emotional state, improving the user's consumer experience.

[0407] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0408] Step 1:

[0409] The server collects user consumption activity data via the network. Inputs include user purchase history, spending amounts, and purchased items. Based on this data, the processing unit organizes the data and extracts consumption trends and patterns.

[0410] Step 2:

[0411] Based on the collected consumption activity data, the server uses an emotion analysis engine to evaluate the user's emotional state. The input is the consumption data organized in the previous step, and the emotion analysis engine uses natural language processing technology to analyze text data such as reviews and comments, and outputs the user's emotions as a numerical value.

[0412] Step 3:

[0413] Based on the user's emotional state analyzed by the server, the communication device customizes promotional information to suit the user's needs. It takes numerical data of the emotional state as input, prioritizes selecting the most relevant advertisements and promotions, and outputs that information.

[0414] Step 4:

[0415] The communication device sends customized promotional information to the user's smartphone via Firebase Cloud Messaging as push notifications. These notifications include money-saving tips and campaign information tailored to the user's current situation, aiming to increase the user's purchasing intent.

[0416] Step 5:

[0417] The device dynamically adjusts the interface style and displayed content to match the user's emotional state based on information obtained from push notifications. This process uses user emotional data and notification content as input, and adjusts the UI using React Native. The output is an interface that is most visually appealing and easy to operate for the user.

[0418] Step 6:

[0419] Ultimately, the device displays savings tips and promotional information on a customized interface for the user. Furthermore, the user experience is enhanced by passing a prompt message, such as "Based on this user's recent purchase history and reviews, assess their emotional state and suggest some appropriate savings tips," to the generating AI model.

[0420] 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.

[0421] 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.

[0422] 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.

[0423] [Third Embodiment]

[0424] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0425] 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.

[0426] 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).

[0427] 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.

[0428] 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.

[0429] 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).

[0430] 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.

[0431] 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.

[0432] 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.

[0433] 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.

[0434] 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.

[0435] 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".

[0436] This invention aims to effectively manage the consumption activities of individual users and propose the most suitable electronic payment method. It also aims to provide educational content to support the improvement of users' financial literacy. Specific embodiments for implementing this invention are described below.

[0437] Server Processing

[0438] The server is equipped with a computing device that continuously collects and analyzes user spending data. For example, the server classifies each spending item based on the user's spending history and generates spending patterns for each category. Based on these patterns, it provides the user with the most suitable electronic payment methods and the latest promotional information. Promotional information is obtained from external sources via APIs, and those that match the user's spending habits are prioritized.

[0439] Specific example

[0440] The server detects that the user has made significant spending on transportation and dining out in the past month. It then identifies e-money services offering discounts related to these spending and sends that information to the user.

[0441] Terminal processing

[0442] The terminal has a display device that receives information transmitted from the server and presents it visually to the user. The user can manage their spending based on this information. The display device updates spending information in real time, providing an interface that allows the user to easily understand their spending habits. Furthermore, educational content such as videos and articles are available to increase financial knowledge.

[0443] Specific example

[0444] When a user launches the application on their smartphone, their spending for the month is displayed on a dashboard. Furthermore, simulation results for using specific e-money services and videos offering money-saving tips are recommended.

[0445] User actions

[0446] Users manage their spending habits through their devices. Based on reward information provided by the server, they can select electronic payment methods and optimize their spending. They can also exchange information with other users using the forum function.

[0447] Specific example

[0448] The user decides to use electronic money for shopping at a specific supermarket, taking advantage of the reward information displayed on their device. Later, the user shares their experience on a forum and receives similar experiences and advice from other users.

[0449] In this way, the present invention intelligently supports users' consumption activities and promotes the use of electronic payment methods.

[0450] The following describes the processing flow.

[0451] Step 1:

[0452] The server collects daily transaction data from users' bank accounts and e-money accounts. This transaction data includes information such as the date and time of purchase, store name, amount, and category.

[0453] Step 2:

[0454] The server analyzes user spending patterns based on collected transaction data. Specifically, an AI model identifies spending trends and calculates spending percentages for each category. It also identifies user interests from past history and extracts categories that should be targeted for promotion.

[0455] Step 3:

[0456] The server accesses an external promotional database to retrieve the latest promotional information that matches the user's spending patterns. This information includes details about discounts and point-boosting campaigns at specific stores.

[0457] Step 4:

[0458] The terminal visually presents the analysis results and promotional information received from the server to the user in a dashboard format. The dashboard displays spending graphs and guidance on the optimal use of electronic money.

[0459] Step 5:

[0460] Users make decisions to manage their spending based on the information displayed. They aim to save money by checking promotional information and adjusting payment methods and purchase plans.

[0461] Step 6:

[0462] Users view educational content provided through their devices. The goal is to improve their financial literacy and acquire knowledge to enhance their consumer behavior.

[0463] Step 7:

[0464] Users can use the system's forums to share experiences and information with other users, thereby gaining further tips and advice on consumption management.

[0465] (Example 1)

[0466] 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."

[0467] In today's consumer environment, consumers often fail to fully utilize diverse payment methods and a wealth of promotional information. As a result, individual consumers may have difficulty managing their spending and may not be able to engage in effective consumption. Furthermore, there is a current situation where consumers' financial literacy is not sufficiently improved. This invention aims to solve these problems.

[0468] 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.

[0469] In this invention, the server includes means equipped with an information processing device that acquires and analyzes consumer spending activity data; means equipped with a communication device that collects reward information related to electronic payment methods and notifies consumers based on their individual spending trends; means equipped with a display device that displays the acquired data and reward information and performs immediate spending management; and means equipped with a function that optimizes the generated recommendation information using a generation AI model. This enables consumers to effectively utilize optimal payment methods and promotional information while managing their spending in real time. Furthermore, by supporting the improvement of consumers' financial literacy, it is possible to promote smarter spending activities.

[0470] "Consumer activity data" refers to information about consumers' purchasing behavior, including data that shows consumers' spending patterns and purchase history.

[0471] An "information processing device" is an electronic device used to collect, analyze, and store data, and includes computers and servers.

[0472] "Communication equipment" refers to devices that send and receive data and transmit information with consumers, enabling communication via the internet.

[0473] "Display devices" are devices used to output information visually, and include displays and screens.

[0474] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to analyze data and generate new information.

[0475] "Promotional information" refers to information about discounts and benefits that consumers can use when purchasing goods or services.

[0476] This invention is a system aimed at optimally managing consumer spending activities and effectively utilizing electronic payment methods. The system consists of an information processing device, a communication device, and a display device. Specific embodiments of this system are described below.

[0477] The server functions as an information processing device, responsible for collecting, storing, and analyzing consumer spending data. Specifically, the server retrieves bank transaction history, credit card statements, and electronic payment data using APIs and stores them in a database. Data analysis is supported by programming languages ​​such as Python and machine learning algorithms, which visualize consumption patterns and spending trends.

[0478] The terminal, acting as a communication device, receives promotional and spending information from the server. Users can check their spending management information in real time via the terminal's display. The terminal includes smartphones and tablets, and the information is presented graphically to allow users to understand it intuitively. It is also possible to provide educational content to support the improvement of users' financial literacy. The educational content is provided in the form of videos and interactive materials.

[0479] Users can optimize their spending based on the information displayed on their devices. They can use promotional information to, for example, select the appropriate e-money for shopping at a specific store, thereby saving money. They can also use the forum function to exchange opinions with other users and share advice and experiences related to spending.

[0480] The generative AI model dynamically generates optimal promotional information for consumers based on analyzed data. An example of a specific prompt is: "Based on the user's past spending data, please suggest the most suitable e-money promotional information. Please prioritize spending on transportation and dining out." Using this prompt, it becomes possible to provide information tailored to the individual needs of consumers.

[0481] In this way, this system supports consumer spending and promotes the use of more effective electronic payment methods.

[0482] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0483] Step 1:

[0484] The server collects consumer activity data. Inputs include bank transaction history, credit card statements, and electronic payment data. The server retrieves this data via an API and stores it in a database. The data is normalized and standardized for subsequent analysis.

[0485] Step 2:

[0486] The server analyzes the collected data. The input is consumer activity data stored in a database, and the output is spending patterns and trends for each consumer. The server uses machine learning algorithms to analyze the data and visualize spending trends for each category, such as transportation and dining out. The analysis results are visualized and used in subsequent steps.

[0487] Step 3:

[0488] The server generates promotional information using a generative AI model. The input is analyzed consumer spending patterns, and the output is optimal promotional information. The generative AI model dynamically selects the most effective promotions using prompts and lists them.

[0489] Step 4:

[0490] The server sends recommended promotional information to the device. The input is a list of promotions, and the output is a notification to the device. The server pushes the selected promotional information to the user's device in real time.

[0491] Step 5:

[0492] The terminal displays received promotional information to the user. Input is notifications from the server, and output is the visual presentation of information to the user. The terminal uses a graphical interface to display promotional information on a dashboard, making it easy for the user to understand.

[0493] Step 6:

[0494] Users optimize their spending based on the information they receive. Inputs include promotional information displayed on their device and their own spending history. Outputs include an optimized spending plan and selected electronic payment method. Users can leverage reward information to engage in efficient spending.

[0495] (Application Example 1)

[0496] 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."

[0497] In individual consumer activities, there is a need for efficient transaction management and the provision of optimal market information. However, current systems have challenges in adequately analyzing individual user purchasing patterns and insufficient sharing of appropriate educational content and information. Therefore, it is necessary to build a system that more effectively supports users' consumer activities.

[0498] 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.

[0499] In this invention, the server includes means having an information processing device for collecting and analyzing individual transaction data, means having a communication device for acquiring market information related to electronic payment methods and notifying the user of this information based on individual purchasing patterns, and means having a display means for displaying the acquired information and market information, and for performing consumption management immediately. As a result, users can receive optimal market information tailored to their consumption patterns, intelligently manage their own transactions, and share information with other users.

[0500] "Personal transaction data" refers to detailed information about purchases and payments made by a user, including data such as the date and time, amount, and the goods or services used.

[0501] An "information processing device" is a computer that has the function of analyzing collected data and finding specific patterns or trends based on that analysis.

[0502] "Electronic payment methods" refer to electromagnetic methods used to pay for goods and services without using cash or banknotes, and include credit cards, electronic money, and online payments.

[0503] "Market information" refers to various types of information related to current commercial activities, including promotional information, campaigns, discount information, and other content that stimulates consumer purchasing intent.

[0504] A "communication device" is a device used to send and receive data between a server and a user's terminal, and it utilizes wired or wireless network technology.

[0505] A "purchase pattern" is a set of characteristics that indicate a user's consumption tendencies and preferences, derived from their past transactions.

[0506] "Notifying" refers to the act of sending specific information to a user and informing them of that information visually or audibly.

[0507] "Display means" refers to technologies and devices for visually displaying information on screens such as those of computers and smartphones.

[0508] "Immediate consumption management" refers to users being able to grasp information about their own consumption activities in real time and manage it as needed.

[0509] To implement this invention, the server uses an information processing device that collects and analyzes individual transaction data. The information processing device analyzes the user's purchase history stored in the database and extracts specific patterns and purchasing trends. This data analysis reveals the user's individual purchasing patterns, and based on these, optimal market information is obtained.

[0510] Next, the server uses a communication device to notify the user's terminal of the acquired market information. This market information is obtained through an external API, and the server selects and notifies the user of the most relevant information. This information is prioritized based on the user's purchasing patterns and is constantly updated in real time.

[0511] The acquired information is displayed on the user's device. Examples of display methods include smartphones and tablet devices with high-definition displays, ensuring that the information is presented visually and clearly. Based on this information, users can select appropriate transactions and efficiently manage their spending. Furthermore, educational content to improve financial literacy is also displayed on the device, allowing users to deepen their knowledge by viewing videos and articles.

[0512] For example, if a user spends a high amount in a particular category, they can instantly receive discount information and promotions related to that category. This information includes campaign details, duration, and how to use them. Users can then use this information to make financially advantageous choices.

[0513] An example of a prompt using a generative AI model would be: "Suggest available discount promotions based on the user's dining-out spending. If the spending in the dining-out category is $100, please provide the best promotional information for that condition."

[0514] The system based on this invention utilizes data analysis techniques and real-time communication technologies to provide advanced support for users' consumption activities and further offer added value in terms of education.

[0515] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0516] Step 1:

[0517] The server collects users' personal transaction data, including their purchase history and payment information. The server retrieves this data from financial institutions and online stores via the network and stores it in a database. The input is transaction history data, and the output is the transaction data stored in the database.

[0518] Step 2:

[0519] The server analyzes the accumulated transaction data. The information processing device uses algorithms to process the data and extract user purchasing patterns and consumption trends. The processing utilizes data mining techniques, classifying and organizing the data using statistical methods. The input is transaction data stored in the database, and the output is the analyzed purchasing patterns.

[0520] Step 3:

[0521] The server obtains the latest market information via external APIs. This includes promotional information and discount campaigns. Using communication equipment, it collects this information and selects the most suitable information for the user's purchasing patterns. The input is the analyzed purchasing patterns and the acquired market information, and the output is the optimal market information for the user.

[0522] Step 4:

[0523] The server notifies the user's terminal of the selected market information. Promotional information is sent to the user's terminal using a communication method. This information is displayed visually on the terminal, allowing the user to confirm the notification. The input is the selected market information, and the output is the notification information displayed on the terminal.

[0524] Step 5:

[0525] Users manage their spending based on information displayed on their devices. Through the device's interface, they review displayed promotional information and determine which transaction is most advantageous. Here, users make optimal purchasing decisions based on the displayed information. The input is the notification information displayed on the device, and the output is the user's purchasing behavior.

[0526] Step 6:

[0527] Users can view educational content provided on their devices. The devices display educational videos and articles sent from the server, helping users improve their financial knowledge. The input is the educational content from the server, and the output is the user's educational experience.

[0528] In this way, a system is formed in which servers, terminals, and users cooperate to optimize user consumption activities and provide educational value.

[0529] 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.

[0530] This invention relates to a system that recognizes emotions related to a user's consumption activities and provides customized information based on those emotions. The following describes specific embodiments of this invention.

[0531] Server Processing

[0532] The server first acquires user consumption activity data. This data includes the user's spending history and information about purchased items. In addition, the server is equipped with an emotion engine to analyze user emotions from user interaction and behavioral data. The emotion engine analyzes, for example, the language used in reviews and comments, changes in spending, and recent consumption behavior to evaluate the user's emotions.

[0533] Specific example

[0534] If a user makes a large purchase of a product and then posts a negative review, the server analyzes this using an emotion engine and determines that the user's satisfaction level is low.

[0535] Processing of communication devices

[0536] The communication device customizes individual promotional information based on the user's emotions analyzed by the server. By prioritizing and notifying users of campaign information related to categories in which they have shown positive emotions, it further stimulates their purchasing intent.

[0537] Specific example

[0538] If a user has previously expressed high satisfaction with outdoor equipment purchases, the communication device will prioritize notifying them of discount information on new outdoor equipment.

[0539] Terminal processing

[0540] The device has a function to display information that is relevant to the user's emotions in a timely manner. It automatically adjusts the displayed content and interface style according to changes in the user's emotional state. Furthermore, if the device determines that the user's reaction to consumer behavior is not positive, it provides content that offers encouragement or helpful money-saving tips.

[0541] Specific example

[0542] When a user opens an app, if the emotion engine determines that their recent spending habits are causing stress, the device will display content that helps reduce stress or budget management tools.

[0543] In this way, the present invention, which combines an emotion engine, enables the provision of more detailed services tailored to the individual needs of users, thereby improving the consumer experience.

[0544] The following describes the processing flow.

[0545] Step 1:

[0546] The server collects user consumption data and behavioral data such as feedback and reviews provided by users. This data includes the user's spending history, purchased items, and in-store behavior history.

[0547] Step 2:

[0548] The server's emotion engine analyzes collected data and uses natural language processing to assess the user's emotions. It detects the frequency of positive and negative words, as well as sudden changes in spending trends, to determine the user's current emotional state.

[0549] Step 3:

[0550] The communication device creates customized promotional information based on the user's emotional state obtained by the server. It is configured to provide special discount information for products in categories where the user has expressed joy, and relaxation-related product information in areas where the user is experiencing stress.

[0551] Step 4:

[0552] The device displays promotional information and customized content transmitted from the communication device to the user in real time. The displayed content may use different designs and messages than usual based on the determined emotional state.

[0553] Step 5:

[0554] Users can review information and suggestions provided through their devices, purchase products as needed, or create new payment plans. They can also record their feelings about their daily spending habits as feedback.

[0555] Step 6:

[0556] The server receives new feedback from users, analyzes it again using the sentiment engine, and uses it to improve future promotional information. The feedback is reflected in improving the accuracy of information provision and refining sentiment analysis.

[0557] (Example 2)

[0558] 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."

[0559] In today's consumer society, the sheer volume of information related to individual consumer activities makes it difficult to provide personalized and relevant information. Furthermore, promotional information and content that consider users' emotional states are often lacking, highlighting the need for efficient methods to enhance consumer satisfaction.

[0560] 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.

[0561] In this invention, the server includes means having a computing device that collects individual consumer activity data and performs sentiment analysis; means having a communication device that customizes and notifies relevant promotional information for each user based on the analyzed sentiment data; and means having a display device that adjusts the display content and interface according to the user's emotional state and displays the information. This makes it possible to provide individualized information based on the user's emotions and consumption patterns. It also makes it possible to provide services that improve the user's consumption experience.

[0562] "Personal consumption activity data" refers to information about an individual's consumption behavior, such as a user's spending history, purchased items, and transaction dates and times.

[0563] "Sentiment analysis" refers to the process of evaluating a user's emotional state using natural language processing and algorithms based on data such as user posts, reviews, and changes in spending.

[0564] A "processing unit" refers to a computer system or device used for collecting, processing, and analyzing data.

[0565] "Communication device" refers to a device or system that transmits and receives digital information and provides notifications to users.

[0566] A "display device" refers to a device that has a digital screen or interface for providing visual information to a user.

[0567] "Customization" refers to the process of adjusting and optimizing information and services based on the individual user's conditions and needs.

[0568] "Emotional state" refers to the state that represents the user's current psychological or emotional condition.

[0569] This invention relates to a system that provides customized information using a user's personal consumption activity data. The following details the implementation of this system.

[0570] The server collects user consumption activity data. This data is obtained through APIs and databases and includes the user's spending history, purchased items, and related metadata. The server uses a sentiment engine equipped with natural language processing (NLP) technology to perform sentiment analysis using the collected data. The sentiment engine analyzes the context of reviews and comments and evaluates user sentiment. This analysis process uses natural language processing libraries with programming languages ​​such as Python.

[0571] The communication device identifies and customizes promotional information tailored to the user's preferences based on sentiment data analyzed by the server. The selected information is immediately notified to the user. Specifically, the communication device considers the user's past behavior patterns and sends highly relevant campaign information via push notifications or email. Communication interfaces such as the Gmail API may be used in this process.

[0572] The device displays received information in a timely manner. It has the ability to dynamically adjust the UI design and displayed content according to the user's emotional state. Based on the analysis results of the emotion engine, the screen's color scheme and message tone are changed, providing a flexible response that matches the user's mood. For example, the user interface can be varied using frameworks such as React Native.

[0573] This system aims to enrich the user's consumption experience, improving consumer satisfaction through customized information delivery based on sentiment analysis. Furthermore, it uses prompt statements to instruct the generating AI model, enabling even more optimized information delivery. Specific examples of prompt statements used include:

[0574] "If a user has a purchase history of outdoor equipment and has left positive reviews, what kind of promotional information should be sent to them?"

[0575] In this way, the invention combines data analysis technology and communication technology to provide personalized information to individual users, thereby promoting consumer engagement.

[0576] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0577] Step 1:

[0578] The server collects individual consumer activity data. Specifically, it retrieves users' purchase and spending history through APIs and databases, and prepares it as input data for sentiment analysis. This step involves data preprocessing, such as formatting and normalization of the data.

[0579] Step 2:

[0580] The server feeds the collected consumer activity data into an emotion engine to analyze user emotions. This process involves using natural language processing techniques to analyze the context of reviews and comments. The analysis results in scores and metrics that represent the user's emotional state. This output data is used to customize subsequent promotional information.

[0581] Step 3:

[0582] The communication device selects and customizes promotional information suitable for the user based on the results of sentiment analysis. It uses the acquired sentiment data as input to extract relevant campaign and product discount information. This output information is then formatted as promotional content to be notified to the user.

[0583] Step 4:

[0584] The communication device notifies the user's device of customized promotional information. This process involves sending information instantly via push notifications or email. A specific example of this operation is sending notifications in email format using the Gmail API.

[0585] Step 5:

[0586] The device adjusts the content and style of the user interface based on the promotional information it receives, and displays the information accordingly. It receives a sentiment score and notified information as input, and adjusts the color settings of the display screen and the tone of the message before presenting it to the user. This output is visually appealing to the user and may include stress-reducing content or money-saving tips.

[0587] Step 6:

[0588] Users act based on the information displayed. In this step, actions such as clicks and purchases are taken to indicate their reaction to the provided promotions and content. This data is collected again within the system and used for future sentiment analysis and promotion customization.

[0589] (Application Example 2)

[0590] 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."

[0591] In individual consumer activities, users often fail to fully understand their own emotional state and purchasing patterns, leading to inappropriate spending. This can result in consumer activities becoming a source of anxiety and stress, making it difficult to enjoy a productive consumer experience. Furthermore, if personalized information tailored to the user's emotions is not provided, it may fail to adequately stimulate their purchasing intent, potentially leading to decreased customer satisfaction.

[0592] 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.

[0593] In this invention, the server includes means having a computing processing unit that collects individual consumption activity data and evaluates the emotional state using an emotion analysis engine; means having a communication device that collects promotional information related to electronic payment methods and provides personalized notifications based on the user's emotional state; and means having a display device that displays the collected data, promotional information, and savings guidelines, and adjusts the interface according to the emotional state, and performs consumption management in real time. This enables intelligent consumption management based on the user's emotional state, reduces stress caused by consumption activities, and improves customer satisfaction.

[0594] "Consumer activity data" refers to information about an individual's spending, including purchase history and product selection information.

[0595] An "emotion analysis engine" refers to software or algorithms that analyze a user's language expressions and consumer behavior to evaluate their emotional state.

[0596] "Personalized notifications" refer to sending individual information and messages tailored to a user's specific emotions or consumption patterns.

[0597] A "processing device" refers to an electronic device or system that performs data analysis and calculations, and includes computers.

[0598] "Communication equipment" refers to devices or systems used for sending and receiving data, and is used to provide information to users via a network.

[0599] A "display device" refers to a device equipped with a screen or display for showing visual information to a user.

[0600] "Real-time consumption management" refers to a process that instantly processes and displays information about a user's consumption activities, and continuously manages and optimizes them.

[0601] "Interface adjustment" refers to dynamically changing the appearance and usability of the user interface in response to the user's emotional state.

[0602] "Savings guidelines" refer to specific advice and tips for users to manage their funds efficiently and reduce unnecessary spending.

[0603] The system implementing this invention mainly consists of a server, a communication device, and a display device. The server collects user consumption activity data and uses an emotion analysis engine to evaluate the user's emotional state from that data. This process uses programming languages ​​such as Python and JavaScript, and artificial intelligence frameworks such as TensorFlow are utilized for emotion analysis.

[0604] The communication device provides personalized promotional information relevant to the user based on sentiment information obtained from the server. This is achieved by sending push notifications via Firebase Cloud Messaging (FCM). These notifications include information on campaigns and savings tips that are most relevant to the user's emotional state.

[0605] The display device is responsible for dynamically adjusting the interface according to the user's emotional state. Using Python or React Native, the interface style is adjusted to display emotionally relevant information in a timely manner. For example, if a user expresses high satisfaction after purchasing a travel-related product, travel-related promotional information will be prioritized.

[0606] In using the generative AI model, an example of a prompt might be, "Based on this user's recent purchase history and reviews, assess their emotional state and suggest some appropriate saving tips." In this way, the system facilitates the management of consumer activity and emotional state, improving the user's consumer experience.

[0607] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0608] Step 1:

[0609] The server collects user consumption activity data via the network. Inputs include user purchase history, spending amounts, and purchased items. Based on this data, the processing unit organizes the data and extracts consumption trends and patterns.

[0610] Step 2:

[0611] Based on the collected consumption activity data, the server uses an emotion analysis engine to evaluate the user's emotional state. The input is the consumption data organized in the previous step, and the emotion analysis engine uses natural language processing technology to analyze text data such as reviews and comments, and outputs the user's emotions as a numerical value.

[0612] Step 3:

[0613] Based on the user's emotional state analyzed by the server, the communication device customizes promotional information to suit the user's needs. It takes numerical data of the emotional state as input, prioritizes selecting the most relevant advertisements and promotions, and outputs that information.

[0614] Step 4:

[0615] The communication device sends customized promotional information to the user's smartphone via Firebase Cloud Messaging as push notifications. These notifications include money-saving tips and campaign information tailored to the user's current situation, aiming to increase the user's purchasing intent.

[0616] Step 5:

[0617] The device dynamically adjusts the interface style and displayed content to match the user's emotional state based on information obtained from push notifications. This process uses user emotional data and notification content as input, and adjusts the UI using React Native. The output is an interface that is most visually appealing and easy to operate for the user.

[0618] Step 6:

[0619] Ultimately, the device displays savings tips and promotional information on a customized interface for the user. Furthermore, the user experience is enhanced by passing a prompt message, such as "Based on this user's recent purchase history and reviews, assess their emotional state and suggest some appropriate savings tips," to the generating AI model.

[0620] 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.

[0621] 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.

[0622] 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.

[0623] [Fourth Embodiment]

[0624] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0625] 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.

[0626] 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).

[0627] 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.

[0628] 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.

[0629] 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).

[0630] 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.

[0631] 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.

[0632] 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.

[0633] 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.

[0634] 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.

[0635] 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.

[0636] 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".

[0637] This invention aims to effectively manage the consumption activities of individual users and propose the most suitable electronic payment method. It also aims to provide educational content to support the improvement of users' financial literacy. Specific embodiments for implementing this invention are described below.

[0638] Server Processing

[0639] The server is equipped with a computing device that continuously collects and analyzes user spending data. For example, the server classifies each spending item based on the user's spending history and generates spending patterns for each category. Based on these patterns, it provides the user with the most suitable electronic payment methods and the latest promotional information. Promotional information is obtained from external sources via APIs, and those that match the user's spending habits are prioritized.

[0640] Specific example

[0641] The server detects that the user has made significant spending on transportation and dining out in the past month. It then identifies e-money services offering discounts related to these spending and sends that information to the user.

[0642] Terminal processing

[0643] The terminal has a display device that receives information transmitted from the server and presents it visually to the user. The user can manage their spending based on this information. The display device updates spending information in real time, providing an interface that allows the user to easily understand their spending habits. Furthermore, educational content such as videos and articles are available to increase financial knowledge.

[0644] Specific example

[0645] When a user launches the application on their smartphone, their spending for the month is displayed on a dashboard. Furthermore, simulation results for using specific e-money services and videos offering money-saving tips are recommended.

[0646] User actions

[0647] Users manage their spending habits through their devices. Based on reward information provided by the server, they can select electronic payment methods and optimize their spending. They can also exchange information with other users using the forum function.

[0648] Specific example

[0649] The user decides to use electronic money for shopping at a specific supermarket, taking advantage of the reward information displayed on their device. Later, the user shares their experience on a forum and receives similar experiences and advice from other users.

[0650] In this way, the present invention intelligently supports users' consumption activities and promotes the use of electronic payment methods.

[0651] The following describes the processing flow.

[0652] Step 1:

[0653] The server collects daily transaction data from users' bank accounts and e-money accounts. This transaction data includes information such as the date and time of purchase, store name, amount, and category.

[0654] Step 2:

[0655] The server analyzes user spending patterns based on collected transaction data. Specifically, an AI model identifies spending trends and calculates spending percentages for each category. It also identifies user interests from past history and extracts categories that should be targeted for promotion.

[0656] Step 3:

[0657] The server accesses an external promotional database to retrieve the latest promotional information that matches the user's spending patterns. This information includes details about discounts and point-boosting campaigns at specific stores.

[0658] Step 4:

[0659] The terminal visually presents the analysis results and promotional information received from the server to the user in a dashboard format. The dashboard displays spending graphs and guidance on the optimal use of electronic money.

[0660] Step 5:

[0661] Users make decisions to manage their spending based on the information displayed. They aim to save money by checking promotional information and adjusting payment methods and purchase plans.

[0662] Step 6:

[0663] Users view educational content provided through their devices. The goal is to improve their financial literacy and acquire knowledge to enhance their consumer behavior.

[0664] Step 7:

[0665] Users can use the system's forums to share experiences and information with other users, thereby gaining further tips and advice on consumption management.

[0666] (Example 1)

[0667] 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".

[0668] In today's consumer environment, consumers often fail to fully utilize diverse payment methods and a wealth of promotional information. As a result, individual consumers may have difficulty managing their spending and may not be able to engage in effective consumption. Furthermore, there is a current situation where consumers' financial literacy is not sufficiently improved. This invention aims to solve these problems.

[0669] 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.

[0670] In this invention, the server includes means equipped with an information processing device that acquires and analyzes consumer spending activity data; means equipped with a communication device that collects reward information related to electronic payment methods and notifies consumers based on their individual spending trends; means equipped with a display device that displays the acquired data and reward information and performs immediate spending management; and means equipped with a function that optimizes the generated recommendation information using a generation AI model. This enables consumers to effectively utilize optimal payment methods and promotional information while managing their spending in real time. Furthermore, by supporting the improvement of consumers' financial literacy, it is possible to promote smarter spending activities.

[0671] "Consumer activity data" refers to information about consumers' purchasing behavior, including data that shows consumers' spending patterns and purchase history.

[0672] An "information processing device" is an electronic device used to collect, analyze, and store data, and includes computers and servers.

[0673] "Communication equipment" refers to devices that send and receive data and transmit information with consumers, enabling communication via the internet.

[0674] "Display devices" are devices used to output information visually, and include displays and screens.

[0675] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to analyze data and generate new information.

[0676] "Promotional information" refers to information about discounts and benefits that consumers can use when purchasing goods or services.

[0677] This invention is a system aimed at optimally managing consumer spending activities and effectively utilizing electronic payment methods. The system consists of an information processing device, a communication device, and a display device. Specific embodiments of this system are described below.

[0678] The server functions as an information processing device, responsible for collecting, storing, and analyzing consumer spending data. Specifically, the server retrieves bank transaction history, credit card statements, and electronic payment data using APIs and stores them in a database. Data analysis is supported by programming languages ​​such as Python and machine learning algorithms, which visualize consumption patterns and spending trends.

[0679] The terminal, acting as a communication device, receives promotional and spending information from the server. Users can check their spending management information in real time via the terminal's display. The terminal includes smartphones and tablets, and the information is presented graphically to allow users to understand it intuitively. It is also possible to provide educational content to support the improvement of users' financial literacy. The educational content is provided in the form of videos and interactive materials.

[0680] Users can optimize their spending based on the information displayed on their devices. They can use promotional information to, for example, select the appropriate e-money for shopping at a specific store, thereby saving money. They can also use the forum function to exchange opinions with other users and share advice and experiences related to spending.

[0681] The generative AI model dynamically generates optimal promotional information for consumers based on analyzed data. An example of a specific prompt is: "Based on the user's past spending data, please suggest the most suitable e-money promotional information. Please prioritize spending on transportation and dining out." Using this prompt, it becomes possible to provide information tailored to the individual needs of consumers.

[0682] In this way, this system supports consumer spending and promotes the use of more effective electronic payment methods.

[0683] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0684] Step 1:

[0685] The server collects consumer activity data. Inputs include bank transaction history, credit card statements, and electronic payment data. The server retrieves this data via an API and stores it in a database. The data is normalized and standardized for subsequent analysis.

[0686] Step 2:

[0687] The server analyzes the collected data. The input is consumer activity data stored in a database, and the output is spending patterns and trends for each consumer. The server uses machine learning algorithms to analyze the data and visualize spending trends for each category, such as transportation and dining out. The analysis results are visualized and used in subsequent steps.

[0688] Step 3:

[0689] The server generates promotional information using a generative AI model. The input is analyzed consumer spending patterns, and the output is optimal promotional information. The generative AI model dynamically selects the most effective promotions using prompts and lists them.

[0690] Step 4:

[0691] The server sends recommended promotional information to the device. The input is a list of promotions, and the output is a notification to the device. The server pushes the selected promotional information to the user's device in real time.

[0692] Step 5:

[0693] The terminal displays received promotional information to the user. Input is notifications from the server, and output is the visual presentation of information to the user. The terminal uses a graphical interface to display promotional information on a dashboard, making it easy for the user to understand.

[0694] Step 6:

[0695] Users optimize their spending based on the information they receive. Inputs include promotional information displayed on their device and their own spending history. Outputs include an optimized spending plan and selected electronic payment method. Users can leverage reward information to engage in efficient spending.

[0696] (Application Example 1)

[0697] 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".

[0698] In individual consumer activities, there is a need for efficient transaction management and the provision of optimal market information. However, current systems have challenges in adequately analyzing individual user purchasing patterns and insufficient sharing of appropriate educational content and information. Therefore, it is necessary to build a system that more effectively supports users' consumer activities.

[0699] 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.

[0700] In this invention, the server includes means having an information processing device for collecting and analyzing individual transaction data, means having a communication device for acquiring market information related to electronic payment methods and notifying the user of this information based on individual purchasing patterns, and means having a display means for displaying the acquired information and market information, and for performing consumption management immediately. As a result, users can receive optimal market information tailored to their consumption patterns, intelligently manage their own transactions, and share information with other users.

[0701] "Personal transaction data" refers to detailed information about purchases and payments made by a user, including data such as the date and time, amount, and the goods or services used.

[0702] An "information processing device" is a computer that has the function of analyzing collected data and finding specific patterns or trends based on that analysis.

[0703] "Electronic payment methods" refer to electromagnetic methods used to pay for goods and services without using cash or banknotes, and include credit cards, electronic money, and online payments.

[0704] "Market information" refers to various types of information related to current commercial activities, including promotional information, campaigns, discount information, and other content that stimulates consumer purchasing intent.

[0705] A "communication device" is a device used to send and receive data between a server and a user's terminal, and it utilizes wired or wireless network technology.

[0706] A "purchase pattern" is a set of characteristics that indicate a user's consumption tendencies and preferences, derived from their past transactions.

[0707] "Notifying" refers to the act of sending specific information to a user and informing them of that information visually or audibly.

[0708] "Display means" refers to technologies and devices for visually displaying information on screens such as those of computers and smartphones.

[0709] "Immediate consumption management" refers to users being able to grasp information about their own consumption activities in real time and manage it as needed.

[0710] To implement this invention, the server uses an information processing device that collects and analyzes individual transaction data. The information processing device analyzes the user's purchase history stored in the database and extracts specific patterns and purchasing trends. This data analysis reveals the user's individual purchasing patterns, and based on these, optimal market information is obtained.

[0711] Next, the server uses a communication device to notify the user's terminal of the acquired market information. This market information is obtained through an external API, and the server selects and notifies the user of the most relevant information. This information is prioritized based on the user's purchasing patterns and is constantly updated in real time.

[0712] The acquired information is displayed on the user's device. Examples of display methods include smartphones and tablet devices with high-definition displays, ensuring that the information is presented visually and clearly. Based on this information, users can select appropriate transactions and efficiently manage their spending. Furthermore, educational content to improve financial literacy is also displayed on the device, allowing users to deepen their knowledge by viewing videos and articles.

[0713] For example, if a user spends a high amount in a particular category, they can instantly receive discount information and promotions related to that category. This information includes campaign details, duration, and how to use them. Users can then use this information to make financially advantageous choices.

[0714] An example of a prompt using a generative AI model would be: "Suggest available discount promotions based on the user's dining-out spending. If the spending in the dining-out category is $100, please provide the best promotional information for that condition."

[0715] The system based on this invention utilizes data analysis techniques and real-time communication technologies to provide advanced support for users' consumption activities and further offer added value in terms of education.

[0716] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0717] Step 1:

[0718] The server collects users' personal transaction data, including their purchase history and payment information. The server retrieves this data from financial institutions and online stores via the network and stores it in a database. The input is transaction history data, and the output is the transaction data stored in the database.

[0719] Step 2:

[0720] The server analyzes the accumulated transaction data. The information processing device uses algorithms to process the data and extract user purchasing patterns and consumption trends. The processing utilizes data mining techniques, classifying and organizing the data using statistical methods. The input is transaction data stored in the database, and the output is the analyzed purchasing patterns.

[0721] Step 3:

[0722] The server obtains the latest market information via external APIs. This includes promotional information and discount campaigns. Using communication equipment, it collects this information and selects the most suitable information for the user's purchasing patterns. The input is the analyzed purchasing patterns and the acquired market information, and the output is the optimal market information for the user.

[0723] Step 4:

[0724] The server notifies the user's terminal of the selected market information. Promotional information is sent to the user's terminal using a communication method. This information is displayed visually on the terminal, allowing the user to confirm the notification. The input is the selected market information, and the output is the notification information displayed on the terminal.

[0725] Step 5:

[0726] Users manage their spending based on information displayed on their devices. Through the device's interface, they review displayed promotional information and determine which transaction is most advantageous. Here, users make optimal purchasing decisions based on the displayed information. The input is the notification information displayed on the device, and the output is the user's purchasing behavior.

[0727] Step 6:

[0728] Users can view educational content provided on their devices. The devices display educational videos and articles sent from the server, helping users improve their financial knowledge. The input is the educational content from the server, and the output is the user's educational experience.

[0729] In this way, a system is formed in which servers, terminals, and users cooperate to optimize user consumption activities and provide educational value.

[0730] 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.

[0731] This invention relates to a system that recognizes emotions related to a user's consumption activities and provides customized information based on those emotions. The following describes specific embodiments of this invention.

[0732] Server Processing

[0733] The server first acquires user consumption activity data. This data includes the user's spending history and information about purchased items. In addition, the server is equipped with an emotion engine to analyze user emotions from user interaction and behavioral data. The emotion engine analyzes, for example, the language used in reviews and comments, changes in spending, and recent consumption behavior to evaluate the user's emotions.

[0734] Specific example

[0735] If a user makes a large purchase of a product and then posts a negative review, the server analyzes this using an emotion engine and determines that the user's satisfaction level is low.

[0736] Processing of communication devices

[0737] The communication device customizes individual promotional information based on the user's emotions analyzed by the server. By prioritizing and notifying users of campaign information related to categories in which they have shown positive emotions, it further stimulates their purchasing intent.

[0738] Specific example

[0739] If a user has previously expressed high satisfaction with outdoor equipment purchases, the communication device will prioritize notifying them of discount information on new outdoor equipment.

[0740] Terminal processing

[0741] The device has a function to display information that is relevant to the user's emotions in a timely manner. It automatically adjusts the displayed content and interface style according to changes in the user's emotional state. Furthermore, if the device determines that the user's reaction to consumer behavior is not positive, it provides content that offers encouragement or helpful money-saving tips.

[0742] Specific example

[0743] When a user opens an app, if the emotion engine determines that their recent spending habits are causing stress, the device will display content that helps reduce stress or budget management tools.

[0744] In this way, the present invention, which combines an emotion engine, enables the provision of more detailed services tailored to the individual needs of users, thereby improving the consumer experience.

[0745] The following describes the processing flow.

[0746] Step 1:

[0747] The server collects user consumption data and behavioral data such as feedback and reviews provided by users. This data includes the user's spending history, purchased items, and in-store behavior history.

[0748] Step 2:

[0749] The server's emotion engine analyzes collected data and uses natural language processing to assess the user's emotions. It detects the frequency of positive and negative words, as well as sudden changes in spending trends, to determine the user's current emotional state.

[0750] Step 3:

[0751] The communication device creates customized promotional information based on the user's emotional state obtained by the server. It is configured to provide special discount information for products in categories where the user has expressed joy, and relaxation-related product information in areas where the user is experiencing stress.

[0752] Step 4:

[0753] The device displays promotional information and customized content transmitted from the communication device to the user in real time. The displayed content may use different designs and messages than usual based on the determined emotional state.

[0754] Step 5:

[0755] Users can review information and suggestions provided through their devices, purchase products as needed, or create new payment plans. They can also record their feelings about their daily spending habits as feedback.

[0756] Step 6:

[0757] The server receives new feedback from users, analyzes it again using the sentiment engine, and uses it to improve future promotional information. The feedback is reflected in improving the accuracy of information provision and refining sentiment analysis.

[0758] (Example 2)

[0759] 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".

[0760] In today's consumer society, the sheer volume of information related to individual consumer activities makes it difficult to provide personalized and relevant information. Furthermore, promotional information and content that consider users' emotional states are often lacking, highlighting the need for efficient methods to enhance consumer satisfaction.

[0761] 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.

[0762] In this invention, the server includes means having a computing device that collects individual consumer activity data and performs sentiment analysis; means having a communication device that customizes and notifies relevant promotional information for each user based on the analyzed sentiment data; and means having a display device that adjusts the display content and interface according to the user's emotional state and displays the information. This makes it possible to provide individualized information based on the user's emotions and consumption patterns. It also makes it possible to provide services that improve the user's consumption experience.

[0763] "Personal consumption activity data" refers to information about an individual's consumption behavior, such as a user's spending history, purchased items, and transaction dates and times.

[0764] "Sentiment analysis" refers to the process of evaluating a user's emotional state using natural language processing and algorithms based on data such as user posts, reviews, and changes in spending.

[0765] A "processing unit" refers to a computer system or device used for collecting, processing, and analyzing data.

[0766] "Communication device" refers to a device or system that transmits and receives digital information and provides notifications to users.

[0767] A "display device" refers to a device that has a digital screen or interface for providing visual information to a user.

[0768] "Customization" refers to the process of adjusting and optimizing information and services based on the individual user's conditions and needs.

[0769] "Emotional state" refers to the state that represents the user's current psychological or emotional condition.

[0770] This invention relates to a system that provides customized information using a user's personal consumption activity data. The following details the implementation of this system.

[0771] The server collects user consumption activity data. This data is obtained through APIs and databases and includes the user's spending history, purchased items, and related metadata. The server uses a sentiment engine equipped with natural language processing (NLP) technology to perform sentiment analysis using the collected data. The sentiment engine analyzes the context of reviews and comments and evaluates user sentiment. This analysis process uses natural language processing libraries with programming languages ​​such as Python.

[0772] The communication device identifies and customizes promotional information tailored to the user's preferences based on sentiment data analyzed by the server. The selected information is immediately notified to the user. Specifically, the communication device considers the user's past behavior patterns and sends highly relevant campaign information via push notifications or email. Communication interfaces such as the Gmail API may be used in this process.

[0773] The device displays received information in a timely manner. It has the ability to dynamically adjust the UI design and displayed content according to the user's emotional state. Based on the analysis results of the emotion engine, the screen's color scheme and message tone are changed, providing a flexible response that matches the user's mood. For example, the user interface can be varied using frameworks such as React Native.

[0774] This system aims to enrich the user's consumption experience, improving consumer satisfaction through customized information delivery based on sentiment analysis. Furthermore, it uses prompt statements to instruct the generating AI model, enabling even more optimized information delivery. Specific examples of prompt statements used include:

[0775] "If a user has a purchase history of outdoor equipment and has left positive reviews, what kind of promotional information should be sent to them?"

[0776] In this way, the invention combines data analysis technology and communication technology to provide personalized information to individual users, thereby promoting consumer engagement.

[0777] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0778] Step 1:

[0779] The server collects individual consumer activity data. Specifically, it retrieves users' purchase and spending history through APIs and databases, and prepares it as input data for sentiment analysis. This step involves data preprocessing, such as formatting and normalization of the data.

[0780] Step 2:

[0781] The server feeds the collected consumer activity data into an emotion engine to analyze user emotions. This process involves using natural language processing techniques to analyze the context of reviews and comments. The analysis results in scores and metrics that represent the user's emotional state. This output data is used to customize subsequent promotional information.

[0782] Step 3:

[0783] The communication device selects and customizes promotional information suitable for the user based on the results of sentiment analysis. It uses the acquired sentiment data as input to extract relevant campaign and product discount information. This output information is then formatted as promotional content to be notified to the user.

[0784] Step 4:

[0785] The communication device notifies the user's device of customized promotional information. This process involves sending information instantly via push notifications or email. A specific example of this operation is sending notifications in email format using the Gmail API.

[0786] Step 5:

[0787] The device adjusts the content and style of the user interface based on the promotional information it receives, and displays the information accordingly. It receives a sentiment score and notified information as input, and adjusts the color settings of the display screen and the tone of the message before presenting it to the user. This output is visually appealing to the user and may include stress-reducing content or money-saving tips.

[0788] Step 6:

[0789] Users act based on the information displayed. In this step, actions such as clicks and purchases are taken to indicate their reaction to the provided promotions and content. This data is collected again within the system and used for future sentiment analysis and promotion customization.

[0790] (Application Example 2)

[0791] 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".

[0792] In individual consumer activities, users often fail to fully understand their own emotional state and purchasing patterns, leading to inappropriate spending. This can result in consumer activities becoming a source of anxiety and stress, making it difficult to enjoy a productive consumer experience. Furthermore, if personalized information tailored to the user's emotions is not provided, it may fail to adequately stimulate their purchasing intent, potentially leading to decreased customer satisfaction.

[0793] 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.

[0794] In this invention, the server includes means having a computing processing unit that collects individual consumption activity data and evaluates the emotional state using an emotion analysis engine; means having a communication device that collects promotional information related to electronic payment methods and provides personalized notifications based on the user's emotional state; and means having a display device that displays the collected data, promotional information, and savings guidelines, and adjusts the interface according to the emotional state, and performs consumption management in real time. This enables intelligent consumption management based on the user's emotional state, reduces stress caused by consumption activities, and improves customer satisfaction.

[0795] "Consumer activity data" refers to information about an individual's spending, including purchase history and product selection information.

[0796] An "emotion analysis engine" refers to software or algorithms that analyze a user's language expressions and consumer behavior to evaluate their emotional state.

[0797] "Personalized notifications" refer to sending individual information and messages tailored to a user's specific emotions or consumption patterns.

[0798] A "processing device" refers to an electronic device or system that performs data analysis and calculations, and includes computers.

[0799] "Communication equipment" refers to devices or systems used for sending and receiving data, and is used to provide information to users via a network.

[0800] A "display device" refers to a device equipped with a screen or display for showing visual information to a user.

[0801] "Real-time consumption management" refers to a process that instantly processes and displays information about a user's consumption activities, and continuously manages and optimizes them.

[0802] "Interface adjustment" refers to dynamically changing the appearance and usability of the user interface in response to the user's emotional state.

[0803] "Savings guidelines" refer to specific advice and tips for users to manage their funds efficiently and reduce unnecessary spending.

[0804] The system implementing this invention mainly consists of a server, a communication device, and a display device. The server collects user consumption activity data and uses an emotion analysis engine to evaluate the user's emotional state from that data. This process uses programming languages ​​such as Python and JavaScript, and artificial intelligence frameworks such as TensorFlow are utilized for emotion analysis.

[0805] The communication device provides personalized promotional information relevant to the user based on sentiment information obtained from the server. This is achieved by sending push notifications via Firebase Cloud Messaging (FCM). These notifications include information on campaigns and savings tips that are most relevant to the user's emotional state.

[0806] The display device is responsible for dynamically adjusting the interface according to the user's emotional state. Using Python or React Native, the interface style is adjusted to display emotionally relevant information in a timely manner. For example, if a user expresses high satisfaction after purchasing a travel-related product, travel-related promotional information will be prioritized.

[0807] In using the generative AI model, an example of a prompt might be, "Based on this user's recent purchase history and reviews, assess their emotional state and suggest some appropriate saving tips." In this way, the system facilitates the management of consumer activity and emotional state, improving the user's consumer experience.

[0808] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0809] Step 1:

[0810] The server collects user consumption activity data via the network. Inputs include user purchase history, spending amounts, and purchased items. Based on this data, the processing unit organizes the data and extracts consumption trends and patterns.

[0811] Step 2:

[0812] Based on the collected consumption activity data, the server uses an emotion analysis engine to evaluate the user's emotional state. The input is the consumption data organized in the previous step, and the emotion analysis engine uses natural language processing technology to analyze text data such as reviews and comments, and outputs the user's emotions as a numerical value.

[0813] Step 3:

[0814] Based on the user's emotional state analyzed by the server, the communication device customizes promotional information to suit the user's needs. It takes numerical data of the emotional state as input, prioritizes selecting the most relevant advertisements and promotions, and outputs that information.

[0815] Step 4:

[0816] The communication device sends customized promotional information to the user's smartphone via Firebase Cloud Messaging as push notifications. These notifications include money-saving tips and campaign information tailored to the user's current situation, aiming to increase the user's purchasing intent.

[0817] Step 5:

[0818] The device dynamically adjusts the interface style and displayed content to match the user's emotional state based on information obtained from push notifications. This process uses user emotional data and notification content as input, and adjusts the UI using React Native. The output is an interface that is most visually appealing and easy to operate for the user.

[0819] Step 6:

[0820] Ultimately, the device displays savings tips and promotional information on a customized interface for the user. Furthermore, the user experience is enhanced by passing a prompt message, such as "Based on this user's recent purchase history and reviews, assess their emotional state and suggest some appropriate savings tips," to the generating AI model.

[0821] 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.

[0822] 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.

[0823] 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.

[0824] 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] 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."

[0830] 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.

[0831] 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.

[0832] 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.

[0833] 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.

[0834] 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.

[0835] 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.

[0836] 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.

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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.

[0842] The following is further disclosed regarding the embodiments described above.

[0843] (Claim 1)

[0844] A means having a computing device that collects and analyzes individual consumption activity data,

[0845] A means having a communication device that collects promotional information related to electronic payment methods and notifies the user of it based on individual consumption patterns,

[0846] It has a display device that shows collected data and promotional information, and means for real-time consumption management,

[0847] A system that includes this.

[0848] (Claim 2)

[0849] The system according to claim 1, wherein the above-mentioned processing unit further has a function of providing content for user education.

[0850] (Claim 3)

[0851] The system according to claim 1, wherein the display device further has a function of providing an interface for sharing information about electronic consumption activities with other users.

[0852] "Example 1"

[0853] (Claim 1)

[0854] A means equipped with an information processing device that acquires and analyzes consumer consumption activity data,

[0855] A means equipped with a communication device that collects information on benefits related to electronic payment methods and notifies consumers based on their individual spending habits,

[0856] A display device that shows acquired data and reward information, and a means for immediate consumption management,

[0857] A means equipped with a function to optimize the generated recommendation information using a generation AI model,

[0858] A system that includes this.

[0859] (Claim 2)

[0860] The system according to claim 1, wherein the above-mentioned information processing device further has a function of providing information for improving consumers' financial knowledge.

[0861] (Claim 3)

[0862] The system according to claim 1, wherein the display device further has a function to provide an interactive function for sharing information about electronic consumption activities with other consumers.

[0863] "Application Example 1"

[0864] (Claim 1)

[0865] A means having an information processing device that collects and analyzes individual transaction data,

[0866] A means having a communication device that acquires market information related to electronic payment methods and notifies users of it based on individual purchasing patterns,

[0867] It has a display means for displaying acquired information and market information, and means for immediately managing consumption,

[0868] A system that includes this.

[0869] (Claim 2)

[0870] The system according to claim 1, wherein the above-mentioned information processing device further has a function of providing educational materials for the education of users.

[0871] (Claim 3)

[0872] The system according to claim 1, wherein the above-mentioned display means further has a function of providing an operation screen for sharing information related to electronic purchasing activities with other users.

[0873] "Example 2 of combining an emotion engine"

[0874] (Claim 1)

[0875] A means having a computing device that collects individual consumption activity data and performs sentiment analysis,

[0876] A means having a communication device that customizes and notifies each user of relevant promotional information based on analyzed sentiment data,

[0877] A means having a display device that adjusts the displayed content and interface according to the user's emotional state and displays information,

[0878] A system that includes this.

[0879] (Claim 2)

[0880] The system according to claim 1, wherein the above-mentioned computing device further has a function to provide educational content based on user emotion analysis.

[0881] (Claim 3)

[0882] The system according to claim 1, wherein the display device further has a function of providing an interface for sharing information regarding emotional consumption activities with other users.

[0883] "Application example 2 when combining with an emotional engine"

[0884] (Claim 1)

[0885] A means having a computational processing unit that collects individual consumption activity data and evaluates emotional states using an emotion analysis engine,

[0886] A means having a communication device that collects promotional information related to electronic payment methods and provides personalized notifications based on the user's emotional state,

[0887] It has a display device that shows collected data, promotional information, and savings guidelines, and adjusts the interface according to emotional state, and has means for real-time consumption management.

[0888] A system that includes this.

[0889] (Claim 2)

[0890] The system according to claim 1, wherein the above-mentioned processing unit further has a function to provide content for individualized education based on the user's emotional state.

[0891] (Claim 3)

[0892] The system according to claim 1, wherein the display device further has a function of providing an interface for sharing information about emotion-based electronic consumption activities with other users. [Explanation of Symbols]

[0893] 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 means having a computing device that collects and analyzes individual consumption activity data, A means having a communication device that collects promotional information related to electronic payment methods and notifies the user of it based on individual consumption patterns, It has a display device that shows collected data and promotional information, and means for real-time consumption management, A system that includes this.

2. The system according to claim 1, wherein the above-mentioned processing unit further has a function of providing content for user education.

3. The system according to claim 1, wherein the display device further has a function of providing an interface for sharing information regarding electronic consumption activities with other users.

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