System

Abstract

To provide a system.SOLUTION: A system includes: means for managing transaction information with a business partner; means for receiving an inquiry from the business partner regarding a payment detail; means for automatically extracting relevant transaction information based on the inquiry, and generating a payment detail; means for notifying a source of the inquiry of the generated payment detail; means for displaying the transaction information via an application; and means for analyzing inquiry content using a generative AI model, and extracting the transaction information based on a prompt sentence.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Currently, inquiries about payment details from business partners and from both inside and outside the company must be handled manually one by one, which requires a significant amount of time and effort. [Means for solving the problem]

[0005] We provide a system that manages transaction information with business partners and accepts inquiries from business partners regarding payment details. This system automatically extracts relevant transaction information based on the inquiry and generates a payment detail. The system then notifies the inquirer of the generated payment detail. This automates the response to inquiries regarding payment details and reduces the amount of work required. [Brief explanation of the drawings]

[0006] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0008] First, the terms used in the following description will be explained.

[0009] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0011] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0012] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0017] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0018] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0019] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0024] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0025] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] The system of the present invention stores transaction information in a database and provides an interface for accepting inquiries from business partners. When an inquiry is received, the system automatically extracts the relevant transaction information from the database and generates a payment breakdown. The generated payment breakdown is automatically notified to the source of the inquiry. For example, when an inquiry is received from business partner A, the system extracts transaction information with business partner A from the database and generates a payment breakdown based on the transaction amount, transaction date and time, and transaction details. The generated payment breakdown is automatically notified to business partner A. This makes it possible to automate responses to inquiries regarding payment breakdowns and reduce labor costs.

[0029] "Example 2"

[0030] The system of the present invention stores transaction information in a database and provides an interface for accepting inquiries from business partners. When an inquiry is received, the system automatically extracts the relevant transaction information from the database and generates a payment breakdown. The generated payment breakdown is automatically notified to the source of the inquiry. For example, when an inquiry is received from business partner A, the system extracts transaction information with business partner A from the database and generates a payment breakdown based on the transaction amount, transaction date and time, and transaction details. The generated payment breakdown is automatically notified to business partner A. This makes it possible to automate responses to inquiries regarding payment breakdowns and reduce labor costs.

[0031] The processing flow of each embodiment will be described below.

[0032] "Example 1"

[0033] Step 1: A customer inquiry is entered into the system, for example via a web interface or email.

[0034] Step 2: When the system receives an inquiry, it automatically extracts the relevant transaction information from the database based on the customer information contained in the inquiry (e.g., customer name, ID, etc.).

[0035] Step 3: Generate a payment breakdown from the extracted transaction information. The payment breakdown includes information such as the transaction amount, transaction date and time, and transaction content.

[0036] Step 4: The generated payment details are sent to the inquirer, for example via email or a web interface.

[0037] "Example 2"

[0038] Step 1: A customer inquiry is entered into the system, for example via a web interface or email.

[0039] Step 2: When the system receives an inquiry, it automatically extracts the relevant transaction information from the database based on the customer information contained in the inquiry (e.g., customer name, ID, etc.).

[0040] Step 3: Generate a payment breakdown from the extracted transaction information. The payment breakdown includes information such as the transaction amount, transaction date and time, and transaction content.

[0041] Step 4: The generated payment details are sent to the inquirer, for example via email or a web interface.

[0042] Example 1

[0043] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0044] Conventional transaction information management systems require manual responses to inquiries about payment details from business partners, which requires a significant amount of time and effort. Manual responses also carry the risk of human error, resulting in inaccuracies. Furthermore, the complicated process of inputting and managing transaction information makes efficient operation difficult.

[0045] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0046] In this invention, the server includes means for managing transaction information with business partners, means for accepting inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiry and generating a payment detail, means for notifying the inquirer of the generated payment detail, means for providing an interface for inputting transaction information, means for storing the transaction information in a database, means for recording the inquiry content in a log file, and means for notifying the payment detail by email. This makes it possible to automate the management of transaction information and response to inquiries, thereby reducing labor hours and improving accuracy.

[0047] "Transaction information" refers to detailed data relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction content, and the like.

[0048] "Business partner" refers to a customer or client who receives goods or services.

[0049] "Payment details" is information provided to a trading partner that indicates details of a transaction, including the transaction amount, transaction date and time, transaction content, and the like.

[0050] "Inquiry" refers to a request from a business partner for information or confirmation.

[0051] A "server" refers to a computer system that processes and manages data on a network.

[0052] A "database" refers to a system for systematically storing and managing data such as transaction information.

[0053] An "interface" refers to the means or method by which a user interacts with a system.

[0054] A "log file" refers to a file that records system actions and events.

[0055] "Email" refers to a means of sending and receiving messages electronically.

[0056] MODE FOR CARRYING OUT THE INVENTION

[0057] The present invention relates to a system for managing transaction information and automatically responding to inquiries from business partners regarding payment details. A specific embodiment of this system will be described below.

[0058] System configuration

[0059] This system consists of three main components: a server, a terminal, and a user. The server plays a central role in managing transaction information, accepting inquiries, and generating and notifying payment details. The terminal provides an interface for users to input transaction information and make inquiries. The user is the entity that inputs transaction information and makes inquiries.

[0060] Hardware and software used

[0061] The server uses a general web server (for example, Apache (registered trademark) or Nginx (registered trademark)), and the database uses a relational database such as MySQL (registered trademark) or PostgreSQL. Programming languages ​​such as Python or Java (registered trademark) are used to implement the program. The terminal uses a web browser for user access.

[0062] Data processing and calculation

[0063] The server receives the transaction information entered by the user and stores it in a database. When an inquiry is received from a business partner, the server extracts the relevant transaction information from the database and generates a payment breakdown. The generated payment breakdown is then sent to the business partner by email.

[0064] Specific examples

[0065] For example, if a business partner A inquires, "Please tell me the details of transactions for September 2023," the server will process the inquiry using the following procedure.

[0066] 1. The server accepts an inquiry from business partner A.

[0067] 2. The server extracts trading information for trading partner A for September 2023 from the database.

[0068] 3. Based on the extracted transaction information, the server generates a payment breakdown including the transaction amount, transaction date and time, and transaction details.

[0069] 4. The server sends the generated payment details to Customer A via email.

[0070] Prompt Sentence Examples

[0071] "In response to an inquiry from Business Partner A asking for a transaction breakdown for September 2023, please create a program that will extract the relevant transaction information from the database, generate a payment breakdown, and notify the customer by email."

[0072] In this way, this system automates the management of transaction information and response to inquiries, thereby improving the efficiency and accuracy of operations.

[0073] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0074] Step 1:

[0075] The user enters the transaction information.

[0076] The user accesses a web form for entering transaction information and enters information such as the client name, transaction amount, transaction date and time, and transaction details. Specifically, the user enters "Client name: Client A, transaction amount: 100,000 yen, transaction date and time: 2023-09-15, transaction details: product purchase" and clicks the "Submit" button. The entered data is sent to the server.

[0077] Step 2:

[0078] The server stores the transaction information in a database.

[0079] The server receives the transaction information sent by the user and stores it in the database. Specifically, the server executes the SQL query "INSERT INTO transactions (client_name, amount, date, description) VALUES ('Customer A', 100000, '2023-09-15', 'Product Purchase');". The input is the transaction information sent by the user, and the output is the transaction information stored in the database.

[0080] Step 3:

[0081] A business partner makes an inquiry.

[0082] The business partner accesses the interface for making an inquiry and enters the details of the inquiry. Specifically, business partner A enters "Please tell me the transaction details for September 2023" and clicks the "Send" button. The entered inquiry details are sent to the server.

[0083] Step 4:

[0084] The server accepts the query.

[0085] The server accepts inquiries from business partners and records the inquiry details in a log file. Specifically, the server records a log stating, "An inquiry from business partner A has been accepted." The input is the inquiry details sent by the business partner, and the output is the inquiry details recorded in the log file.

[0086] Step 5:

[0087] The server retrieves the relevant transaction information from the database.

[0088] The server extracts the relevant transaction information from the database based on the query. Specifically, the server executes the SQL query "SELECT FROM transactions WHERE client_name = 'Customer A' AND date LIKE '2023-09%';". The input is the query, and the output is the extracted transaction information.

[0089] Step 6:

[0090] The server generates the payment details.

[0091] The server generates a payment breakdown based on the extracted transaction information. Specifically, the server generates the following breakdown: "Transaction breakdown for customer A in September 2023: 1. Transaction amount: 100,000 yen, Transaction date and time: 2023-09-15, Transaction content: Product purchase." The input is the extracted transaction information, and the output is the generated payment breakdown.

[0092] Step 7:

[0093] The server notifies the customer of the payment details generated.

[0094] The server notifies the client of the generated payment details by email. Specifically, the server records a log stating "Payment details have been sent to client A by email" and sends the email via the SMTP server. The input is the generated payment details, and the output is the email sent to the client.

[0095] (Application example 1)

[0096] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0097] With conventional transaction information management systems, it was difficult to respond quickly and accurately to inquiries about payment details from business partners. Furthermore, there was a problem in that analyzing the content of inquiries and extracting the appropriate transaction information required a great deal of time and effort. Furthermore, there was a lack of a way for users to easily check transaction information via smartphone.

[0098] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0099] In this invention, the server includes means for managing transaction information with business partners, means for accepting inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiry and generating a payment detail, means for notifying the originator of the inquiry of the generated payment detail, means for displaying the transaction information via an application installed on the smartphone, and means for analyzing the inquiry using a generative AI model and extracting transaction information based on a prompt sentence. This allows for quick and accurate responses to inquiries from business partners and enables users to easily check transaction information via their smartphones.

[0100] "Transaction information" refers to information relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction details, etc.

[0101] "Payment details" is detailed payment information generated based on the transaction amount, transaction date and time, and transaction content for each business partner.

[0102] "Inquiry" refers to a question or request for confirmation from a business partner regarding payment details.

[0103] A "smartphone" is a multi-functional mobile device that can connect to the Internet and run applications in addition to the functions of a mobile phone.

[0104] An "application" is a software program that is installed on a smartphone and provides specific functions or services.

[0105] A "generative AI model" is a model that uses artificial intelligence technology to analyze data and automatically perform specific tasks.

[0106] A "prompt" is an instruction entered into a generative AI model, which serves as a trigger for extracting specific information.

[0107] The following system configuration will be described as an embodiment of the present invention.

[0108] System Configuration

[0109] The system includes a server, a smartphone, and a generative AI model. The server manages transaction information and generates payment details based on inquiries. The smartphone provides an interface for users to check the transaction information. The generative AI model analyzes the inquiry and extracts transaction information based on prompts.

[0110] Program processing explanation

[0111] Hardware:

[0112] Server: Database management system (e.g. SQLite)

[0113] Smartphone: Multi-function mobile device

[0114] software:

[0115] SQLite: Database Management System

[0116] Python: a programming language

[0117] Generative AI model: A data analysis model using artificial intelligence technology

[0118] Data processing and calculation:

[0119] 1. Connect to the database and create tables:

[0120] The server uses SQLite to create a database and tables to store the transaction information.

[0121] 2. Insert transaction information:

[0122] The server inserts the new transaction information into the database.

[0123] 3. Enquiry Processing:

[0124] The server retrieves transaction information for the specified merchant from the database.

[0125] 4. Generate payment details:

[0126] The server generates a payment breakdown based on the extracted transaction information.

[0127] 5. User Notice:

[0128] The generated payment details are displayed to the user via their smartphone.

[0129] 6. Use of generative AI models:

[0130] The generative AI model analyzes the query and extracts transaction information based on the prompt.

[0131] Specific examples

[0132] For example, if a user uses a smartphone to inquire about transaction information regarding "Customer A," they might enter a prompt like the following:

[0133] Example prompt sentence:

[0134] "Please tell me the transaction information regarding business partner A."

[0135] Once the prompt is entered, the generative AI model analyzes the query, and the server extracts the relevant transaction information from the database, after which a payment breakdown is generated and notified to the user via their smartphone.

[0136] In this way, the present invention allows for quick and accurate responses to inquiries from business partners and allows users to easily check transaction information via their smartphones.

[0137] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0138] Step 1:

[0139] The server connects to the SQLite database and creates a table to store the transaction information.

[0140] Input: Database connection information

[0141] Output: A table to store transaction information

[0142] What happens: The server connects to the SQLite database and creates a table named "transactions" with columns for transaction ID, customer, transaction amount, transaction date and time, and transaction details.

[0143] Step 2:

[0144] The server inserts the new transaction information into the database.

[0145] Input: Customer, transaction amount, transaction details

[0146] Output: New transaction information is added to the database

[0147] Specific operation: The server receives the client, transaction amount, and transaction details, obtains the current date and time, and inserts this information into the "transactions" table.

[0148] Step 3:

[0149] A user uses a smartphone to make an inquiry about a business partner.

[0150] Input: Prompt statement (e.g., "Please tell me the transaction information about Customer A.")

[0151] Output: The query is sent to the server

[0152] Specific operation: The user opens the application on their smartphone and enters a query about a client. The entered prompt is sent to the server.

[0153] Step 4:

[0154] The server uses a generative AI model to analyze the query and extract transaction information based on the prompt text.

[0155] Input: prompt statement

[0156] Output: Extracted transaction information

[0157] Specific operation: The server inputs a prompt sentence into the generative AI model, which then analyzes the query. Based on the analysis results, the server extracts the transaction information of the relevant trading partner from the database.

[0158] Step 5:

[0159] The server generates a payment breakdown based on the extracted transaction information.

[0160] Input: Extracted transaction information

[0161] Output: Payment details

[0162] Specific operation: Based on the extracted transaction information, the server generates a payment breakdown including the transaction ID, transaction amount, transaction date and time, and transaction details.

[0163] Step 6:

[0164] The server notifies the smartphone of the generated payment details.

[0165] Input: Payment details

[0166] Output: Payment details displayed on smartphone

[0167] Specific operation: The server sends the generated payment details to the smartphone, where the user can check them through the application.

[0168] Step 7:

[0169] Users can check their payment details via their smartphone.

[0170] Input: Payment details displayed on smartphone

[0171] Output: Payment details confirmed by the user

[0172] Specific operation: The user opens the application on their smartphone and checks the displayed payment details.

[0173] Example 2

[0174] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0175] With conventional transaction information management systems, inquiries about payment details from business partners had to be handled manually, which was a time-consuming process. Furthermore, manual responses carried the risk of human error, making it difficult to respond to business partners promptly. This could result in reduced operational efficiency and a loss of trust from business partners.

[0176] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0177] In this invention, the server includes means for managing transaction information with business partners, means for receiving inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiry and generating a payment detail, means for notifying the inquirer of the generated payment detail, means for a user to input transaction information, means for the server to store the transaction information in a database, means for the server to extract relevant transaction information from the database, means for the server to generate a payment detail, and means for notifying the inquirer of the generated payment detail. This makes it possible to automate responses to inquiries regarding payment details and reduce man-hours.

[0178] "Transaction information" refers to information relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction details, etc.

[0179] "Business Partner" means a party with whom a transaction is conducted using the system.

[0180] "Payment details" is information showing details of the amount to be paid to the business partner, including the transaction amount, transaction date and time, transaction content, etc.

[0181] An "inquiry" is an action in which a business partner requests information regarding payment details through the system.

[0182] A "database" is a system for storing and managing transaction information.

[0183] A "server" is a computer system that manages the entire system and executes various processes.

[0184] "User" means a person who utilizes the system to enter transaction information.

[0185] "Automatically extracting" means that the system retrieves the necessary information from the database without human intervention.

[0186] "Generating" means that the system creates a payment breakdown based on the transaction information.

[0187] "Notifying" means transmitting the payment details generated by the system to the trading partner.

[0188] The present invention is a system for managing transaction information and automatically responding to inquiries from business partners regarding payment details. A specific embodiment of this system will be described below.

[0189] System configuration

[0190] Hardware

[0191] 1. Server

[0192] Database server (e.g., MySQL (registered trademark), PostgreSQL)

[0193] Web server (e.g., Apache (registered trademark), Nginx (registered trademark))

[0194] Mail server (e.g. SendGrid, Amazon SES)

[0195] 2. Terminal

[0196] PCs and smartphones used by users and business partners

[0197] software

[0198] 1. Database Management System (DBMS)

[0199] MySQL (registered trademark), PostgreSQL, etc.

[0200] 2. Web Application Frameworks

[0201] Django, Ruby on Rails, etc.

[0202] 3. Data processing script

[0203] Python, JavaScript (registered trademark), etc.

[0204] 4. Email Sending Library

[0205] SMTP, SendMail, etc.

[0206] System Operation

[0207] 1. The user enters transaction information

[0208] The user uses a terminal to access the web interface and inputs transaction information such as the transaction amount, transaction date and time, and transaction details.

[0209] Specific behavior: The user enters transaction information into the form and clicks the "Submit" button.

[0210] 2. The server stores the transaction information in a database

[0211] The server receives the transaction information sent by the user and stores it in a database.

[0212] Specific operation: The server executes an SQL query to insert the transaction information into the database.

[0213] 3. A business partner makes an inquiry

[0214] The customer uses a terminal to access a web interface and make inquiries about payment details.

[0215] Specific operation: The client enters the required information into the inquiry form and clicks the "Submit" button.

[0216] 4. The server accepts the query

[0217] The server receives an inquiry from a business partner and analyzes the inquiry content.

[0218] Specific operation: The server analyzes the inquiry content and identifies the corresponding customer ID.

[0219] 5. The server extracts the relevant transaction information from the database.

[0220] The server extracts transaction information from a database based on the identified merchant ID.

[0221] Specific operation: The server executes an SQL query to select the relevant transaction information.

[0222] 6. The server generates the payment details

[0223] The server generates a payment breakdown based on the extracted transaction information.

[0224] What happens: The server runs a data processing script to calculate and format the payment details.

[0225] 7. The server notifies the inquirer of the payment details generated by the server.

[0226] The server notifies the inquirer of the generated payment details by email.

[0227] Specific behavior: The server uses the email sending library to send an email containing the payment details.

[0228] Specific examples

[0229] Inquiry from Business Partner A

[0230] 1. Supplier A inquires about payment details through the web interface.

[0231] 2. The server extracts the transaction information of trading partner A (transaction amount, transaction date and time, transaction details) from the database.

[0232] 3. The server generates a payment breakdown based on the extracted information.

[0233] 4. The server sends the generated payment details to Customer A via email.

[0234] Example prompts to input to the generative AI model

[0235] "We have received an inquiry about payment details from Supplier A. Please extract Supplier A's transaction information from the database, generate a payment detail, and notify us by email."

[0236] This system automates responses to inquiries regarding payment details, reducing man-hours.

[0237] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0238] Step 1:

[0239] The user enters the transaction information.

[0240] Input: The user uses a terminal to access the web interface and inputs transaction information such as the transaction amount, transaction date and time, and transaction details.

[0241] Data processing: The transaction information entered by the user is sent to the server as form data.

[0242] Output: The transaction information sent to the server.

[0243] Specific behavior: The user enters transaction information into the form and clicks the "Submit" button.

[0244] Step 2:

[0245] The server stores the transaction information in a database.

[0246] Input: Transaction information submitted by the user.

[0247] Data processing: The server inserts the received transaction information into the database using an SQL query.

[0248] Output: Transaction information stored in a database.

[0249] Specific operation: The server executes an SQL query to insert the transaction information into the database.

[0250] Step 3:

[0251] A business partner makes an inquiry.

[0252] Input: The customer uses a terminal to access the web interface and make an inquiry about the payment details.

[0253] Data processing: The inquiry details entered by the business partner are sent to the server as form data.

[0254] Output: The query sent to the server.

[0255] Specific operation: The client enters the required information into the inquiry form and clicks the "Submit" button.

[0256] Step 4:

[0257] The server accepts the query.

[0258] Input: Inquiry sent by business partner.

[0259] Data processing: The server analyzes the inquiry content and identifies the corresponding customer ID.

[0260] Output: The identified account ID.

[0261] Specific operation: The server analyzes the inquiry content and identifies the corresponding customer ID.

[0262] Step 5:

[0263] The server retrieves the relevant transaction information from the database.

[0264] Input: A specific account ID.

[0265] Data processing: The server executes an SQL query to select the relevant transaction information from the database.

[0266] Output: Extracted transaction information.

[0267] Specific operation: The server executes an SQL query to select the relevant transaction information.

[0268] Step 6:

[0269] The server generates the payment details.

[0270] Input: Extracted transaction information.

[0271] Data Processing: The server runs data processing scripts to calculate and format payment details.

[0272] Output: The generated payment breakdown.

[0273] What happens: The server runs a data processing script to calculate and format the payment details.

[0274] Step 7:

[0275] The server notifies the inquirer of the generated payment details.

[0276] Input: Generated payment breakdown.

[0277] Data processing: The server uses an email sending library to send an email containing the payment details.

[0278] Output: Payment breakdown email sent to the inquirer.

[0279] Specific behavior: The server uses the email sending library to send an email containing the payment details.

[0280] (Application example 2)

[0281] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0282] With conventional transaction information management systems, it was difficult to respond quickly and accurately to inquiries from business partners regarding payment details, and manual responses were required, resulting in increased workload. Furthermore, there was a lack of efficient methods for managing transaction information and responding to inquiries using smart devices. This resulted in issues such as poor communication with business partners and reduced operational efficiency.

[0283] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0284] In this invention, the server includes means for managing transaction information with business partners, means for accepting inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiries and generating payment details, means for notifying the originator of the inquiries of the generated payment details, and means for managing transaction information, accepting inquiries, and generating and notifying payment details via an application installed on the smart device. This enables quick and accurate responses to inquiries from business partners, significantly improving business efficiency.

[0285] "Transaction information" refers to detailed data relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction content, and the like.

[0286] "Payment details" is detailed information about payments for each supplier that is generated based on transaction information, and includes the transaction amount, transaction date and time, transaction content, and the like.

[0287] "Inquiry" refers to a question or request for confirmation from a business partner regarding payment details.

[0288] "Smart devices" refers to electronic devices with internet connectivity, such as smartphones, tablets, smart glasses, and head-mounted displays.

[0289] An "application" is a software program installed on a smart device that provides specific functions or services.

[0290] A "server" refers to a computer system that stores, processes, and manages data over a network.

[0291] "Automatic extraction" refers to the process in which the system selects the necessary information from the database without human intervention.

[0292] "Notification" refers to the act of informing the trading partner of the generated payment details.

[0293] A system for implementing the present invention includes a server, a smart device, and an application installed thereon. Specific embodiments are described below.

[0294] System Configuration

[0295] The server has a database for managing transaction information and provides an interface for accepting inquiries from business partners. An application for managing transaction information, accepting inquiries, and generating and notifying payment details is installed on the smart device.

[0296] Hardware and software used

[0297] Hardware: Servers, smart devices such as smartphones, tablets, smart glasses, and head-mounted displays.

[0298] Software: Python, Flask (web framework), SQLite (database).

[0299] Data processing and calculation

[0300] 1. Database initialization: The server initializes the SQLite database and creates a table to store transaction information.

[0301] 2. Inquiry reception: The application on the smart device receives inquiries from business partners in JSON format.

[0302] 3. Transaction information extraction: The server automatically extracts the transaction information of the relevant trading partner from the SQLite database.

[0303] 4. Generate payment details: Generate payment details based on the extracted transaction information.

[0304] 5. Automatic notification: The generated payment details are sent to the inquirer in JSON format.

[0305] Specific examples

[0306] When business partner A uses a smartphone to inquire about his / her transaction information, the following steps are taken.

[0307] 1. Client A launches the application on their smartphone and inquires about transaction information.

[0308] 2. The application sends a JSON request to the server containing the name of Customer A.

[0309] 3. The server extracts the transaction information for Customer A from the SQLite database and generates a payment breakdown.

[0310] 4. The generated payment details are sent to Customer A in JSON format.

[0311] Prompt Sentence Examples

[0312] "Please generate a request to inquire about trading information for trading partner A."

[0313] In this way, a specific embodiment for carrying out the invention has been shown. This system makes it possible to respond to inquiries from business partners quickly and accurately, thereby significantly improving business efficiency.

[0314] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0315] Step 1:

[0316] The server initializes an SQLite database and creates a table to store transaction information. Specifically, the server establishes a database connection and executes SQL commands to create a table to store transaction information. The input is a request to initialize the database, and the output is the initialized database.

[0317] Step 2:

[0318] A user launches an application on a smart device and makes an inquiry about transaction information. Specifically, the user enters the name of a trading partner into the application's inquiry form and presses the submit button. The input is the trading partner's name, and the output is an inquiry request.

[0319] Step 3:

[0320] The terminal sends a JSON request including the name of the customer to the server. Specifically, the application converts the customer name entered by the user into JSON format and sends it as an HTTP request to the server. The input is the customer name, and the output is a JSON request to the server.

[0321] Step 4:

[0322] The server extracts the transaction information of the corresponding trading partner from the SQLite database. Specifically, the server parses the received JSON request and generates an SQL query based on the trading partner name to search the database. The input is the JSON request, and the output is the corresponding transaction information.

[0323] Step 5:

[0324] The server generates a payment breakdown based on the extracted transaction information. Specifically, the server analyzes the extracted transaction information and generates a payment breakdown including the transaction amount, transaction date and time, and transaction details. The input is the transaction information, and the output is the payment breakdown.

[0325] Step 6:

[0326] The server notifies the inquirer of the generated payment details in JSON format. Specifically, the server converts the generated payment details into JSON format and sends it to the terminal as an HTTP response. The input is the payment details, and the output is a JSON response.

[0327] Step 7:

[0328] The terminal displays the received payment details to the user. Specifically, the application parses the received JSON response and displays the payment details in a user-friendly format. The input is the JSON response and the output is the payment details displayed to the user.

[0329] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0330] "Example 1"

[0331] In one embodiment of the present invention, an emotion engine is incorporated. This emotion engine recognizes a user's emotions from the user's tone of voice, facial expression, and choice of words. For example, if a user's tone of voice or facial expression indicates anger or frustration when making an inquiry, the emotion engine captures this information. Based on this information, the emotion engine then adjusts the notification method for the payment details. Specifically, if the emotion engine recognizes that the user is frustrated, it instructs the system to provide a detailed explanation of the payment details. Similarly, if the emotion engine recognizes that the user is happy or satisfied, it feeds this information back to the system and instructs the system to take the same steps next time a similar transaction occurs. This allows the system to respond optimally based on the user's emotions.

[0332] "Example 2"

[0333] In one embodiment of the present invention, an emotion engine is incorporated. This emotion engine recognizes a user's emotions from the user's tone of voice, facial expression, and choice of words. For example, if a user's tone of voice or facial expression indicates anger or frustration when making an inquiry, the emotion engine captures this information. Based on this information, the emotion engine then adjusts the notification method for the payment details. Specifically, if the emotion engine recognizes that the user is frustrated, it instructs the system to provide a detailed explanation of the payment details. Similarly, if the emotion engine recognizes that the user is happy or satisfied, it feeds this information back to the system and instructs the system to take the same steps next time a similar transaction occurs. This allows the system to respond optimally based on the user's emotions.

[0334] The processing flow of each embodiment will be described below.

[0335] "Example 1"

[0336] Step 1: The user queries the system, and the emotion engine captures the user's tone of voice, facial expression, and choice of words.

[0337] Step 2: The emotion engine recognizes the user's emotions from the captured information. For example, if the user senses anger or frustration from the tone of voice or facial expression, the emotion engine will capture that information.

[0338] Step 3: The emotion engine adjusts the notification of the payment details based on the recognized emotion. Specifically, if the emotion engine recognizes that the user is dissatisfied, it instructs the system to provide a detailed explanation of the payment details.

[0339] Step 4: If the emotion engine detects that the user is feeling happy or satisfied, it feeds that information back into the system, instructing it to follow the same steps when a similar transaction occurs.

[0340] Step 5: The system notifies the user of the payment details based on the instructions from the emotion engine, allowing the system to take the most appropriate action based on the user's emotions.

[0341] "Example 2"

[0342] Step 1: The user queries the system, and the emotion engine captures the user's tone of voice, facial expression, and choice of words.

[0343] Step 2: The emotion engine recognizes the user's emotions from the captured information. For example, if the user senses anger or frustration from the tone of voice or facial expression, the emotion engine will capture that information.

[0344] Step 3: The emotion engine adjusts the notification of the payment details based on the recognized emotion. Specifically, if the emotion engine recognizes that the user is dissatisfied, it instructs the system to provide a detailed explanation of the payment details.

[0345] Step 4: If the emotion engine detects that the user is feeling happy or satisfied, it feeds that information back into the system, instructing it to follow the same steps when a similar transaction occurs.

[0346] Step 5: The system notifies the user of the payment details based on the instructions from the emotion engine, allowing the system to take the most appropriate action based on the user's emotions.

[0347] Example 1

[0348] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0349] Conventional transaction information management systems have difficulty responding quickly and accurately to inquiries from business partners regarding payment details. Furthermore, they are unable to respond in a way that takes into account the user's feelings, making it difficult to improve user satisfaction. In particular, when a user is dissatisfied, they require a detailed explanation, but conventional systems do not automate such responses.

[0350] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0351] In this invention, the server includes means for managing transaction information with business partners, means for receiving inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiry and generating a payment detail, means for notifying the inquirer of the generated payment detail, means for recognizing the user's emotion, and means for adjusting the method of notifying the payment detail based on the recognized emotion. This not only automates the management of transaction information and the generation and notification of payment details, but also enables optimal responses according to the user's emotion.

[0352] "Transaction information" refers to information relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction details, etc.

[0353] "Business Partner" means a party with whom a transaction is conducted using the system.

[0354] "Payment details" refers to detailed payment details generated based on transaction information, and includes the transaction amount, transaction date and time, transaction details, and the like.

[0355] An "inquiry" is a request made by a business partner to the system for information or confirmation.

[0356] A "database" is an information system for storing and managing transaction information.

[0357] An "emotion engine" is software or hardware that recognizes a user's emotions from their tone of voice, facial expressions, choice of words, etc.

[0358] "Notification" refers to the act of transmitting the generated payment details to the trading partner, and is done via email or a notification function within the web application.

[0359] "User" means any person or entity that uses the System to manage or inquire about transaction information.

[0360] "Server" refers to the computer system that processes the entire system, managing transaction information, accepting inquiries, and generating and notifying payment details.

[0361] This invention is a system that manages transaction information, automatically generates and notifies payment details in response to inquiries from business partners, and can also recognize the user's emotions and respond accordingly.

[0362] System configuration

[0363] Management of transaction information

[0364] The server stores transaction information in a database. Specifically, information such as the customer ID, transaction date and time, transaction amount, and transaction details is saved in a MySQL (registered trademark) database. For example, when a new transaction occurs, the server receives that information and inserts it into the database using SQL statements.

[0365] Receiving inquiries

[0366] Users use the web application interface to make inquiries about transaction information. The terminal (user's PC or smartphone) accesses this interface through a browser. Inquiries are made by filling out a form or by voice input.

[0367] Processing inquiries

[0368] The server receives the user's inquiry and extracts the relevant transaction information from the database. Specifically, it executes an SQL query to retrieve the data based on the customer ID and transaction date and time entered by the user in the form.

[0369] Generate payment details

[0370] The server generates a payment breakdown based on the extracted transaction information. A Python script is used to calculate the transaction amount, transaction date and time, and transaction details to create a detailed payment breakdown. For example, if transaction information for Customer A is extracted, the Python script processes the information and generates a payment breakdown.

[0371] Payment details notification

[0372] The server notifies the inquiring business partner of the generated payment details. Notification can be via email or a notification function within a web application. For example, the generated payment details can be sent to business partner A by email.

[0373] Recognizing user emotions with an emotion engine

[0374] When a user makes a query, the emotion engine recognizes the user's emotion from the user's tone of voice, facial expression, choice of words, etc. The emotion engine is implemented using a general emotion recognition API. For example, when a user makes a voice input, the emotion engine analyzes the voice data and recognizes the emotion.

[0375] Adjusting responses according to emotions

[0376] The server adjusts how it notifies users of payment details based on information from the emotion engine. Specifically, if it recognizes that the user is dissatisfied, it instructs the system to provide a detailed payment detail. If it recognizes that the user is happy or satisfied, it feeds that information back into the system and instructs it to take the same steps next time a similar transaction occurs.

[0377] Specific examples

[0378] For example, if a business partner A inquires, "Please tell me the payment details of recent transactions," the server will process the inquiry using the following procedure.

[0379] 1. The server extracts trading information for Trading Partner A from the MySQL® database.

[0380] 2. The server uses a Python script to generate a payment breakdown based on the transaction amount, transaction date and time, and transaction details.

[0381] 3. The server notifies Customer A of the generated payment details via email.

[0382] 4. When a user makes an inquiry, the emotion engine analyzes the user's tone of voice and facial expressions and recognizes that they are feeling angry or frustrated.

[0383] 5. The server provides a payment breakdown with detailed explanations based on the information from the emotion engine.

[0384] Prompt Sentence Examples

[0385] "If a customer A asks for a payment breakdown of their recent transaction, please explain how the system will handle this."

[0386] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0387] Step 1:

[0388] The server stores the transaction information in a database. As input, it receives transaction information such as the customer ID, transaction date and time, transaction amount, and transaction details. Specifically, it inserts this information into a MySQL® database using SQL statements. As output, it saves the new transaction information in the database.

[0389] Step 2:

[0390] A user uses a web application interface to make an inquiry about transaction information. As input, the user enters the inquiry details, such as the trading partner ID and transaction date and time, into a form. Specifically, the terminal (the user's PC or smartphone) accesses this interface through a browser and sends the inquiry details. As output, the inquiry details are sent to the server.

[0391] Step 3:

[0392] The server receives the user's inquiry and extracts the relevant transaction information from the database. As input, it receives the customer ID and transaction date and time entered by the user in the form. Specifically, it executes an SQL query to retrieve the relevant transaction information from the database. As output, the relevant transaction information is extracted.

[0393] Step 4:

[0394] The server generates a payment breakdown based on the extracted transaction information. It receives the extracted transaction information as input. Specifically, it uses a Python script to calculate the transaction amount, transaction date and time, and transaction details to create a detailed payment breakdown. The payment breakdown is generated as output.

[0395] Step 5:

[0396] The server notifies the inquiring business partner of the generated payment details. It receives the generated payment details as input. Specific operations include sending the payment details via email or using a notification function within the web application. The output is a notification of the payment details to the business partner.

[0397] Step 6:

[0398] When a user makes a query, the emotion engine recognizes the user's emotions from the user's tone of voice, facial expressions, choice of words, etc. As input, it receives the user's voice data and facial expression data. Specifically, it uses an emotion recognition API to analyze this data and recognize the user's emotions. As output, it generates the user's emotional information.

[0399] Step 7:

[0400] The server adjusts the notification method for payment details based on information from the emotion engine. As input, it receives the user's emotional information. Specifically, if it recognizes that the user is dissatisfied, it instructs the system to provide a payment detail with a detailed explanation. If it recognizes that the user is happy or satisfied, it feeds that information back to the system and instructs it to take the same steps when a similar transaction occurs. As output, it responds optimally according to the emotion.

[0401] (Application example 1)

[0402] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0403] Conventional transaction information management systems had the problem of being unable to respond quickly and appropriately to inquiries from business partners regarding payment details. Furthermore, because they responded uniformly without considering the user's feelings, there was a risk of user satisfaction declining. This posed a risk of damaging trusting relationships with business partners.

[0404] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0405] In this invention, the server includes means for managing transaction information with business partners, means for accepting inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiries and generating payment details, means for notifying the inquirer of the generated payment details, means including an emotion engine for recognizing the user's emotions, and means for adjusting the notification method according to the user's emotions. This makes it possible to respond quickly and appropriately to inquiries from business partners and to provide an optimal response according to the user's emotions.

[0406] "Transaction information" refers to detailed data relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction content, and the like.

[0407] "Payment details" is a list of detailed payment details generated based on transaction information, and includes the transaction amount, transaction date and time, transaction details, etc.

[0408] "Inquiry" refers to a question or request for confirmation from a business partner regarding payment details.

[0409] An "emotion engine" is a technology that recognizes a user's emotions from their tone of voice, facial expressions, choice of words, etc.

[0410] "Notification method" refers to the means or method for transmitting the generated payment details to the trading partner.

[0411] "Business partner" refers to the company or individual that is the subject of business information.

[0412] "User" refers to the entity that manages transaction information and makes inquiries.

[0413] "Server" refers to a computer system that manages transaction information and responds to inquiries.

[0414] A system for implementing this invention manages transaction information and responds to inquiries from business partners regarding payment details. The system includes a server for managing transaction information, a terminal for accepting inquiries, and an emotion engine for recognizing user emotions.

[0415] The server manages transaction information using a MySQL (registered trademark) database. Transaction information includes the transaction amount, transaction date and time, and transaction details for each customer. When a user makes an inquiry through their terminal, the server automatically extracts the relevant transaction information and generates a payment breakdown.

[0416] The generated payment details are sent to the inquirer via the terminal. The notification method is adjusted according to the user's emotions by the emotion engine. The emotion engine uses Microsoft® Azure® Cognitive Services to analyze the user's tone of voice and facial expressions to recognize emotions.

[0417] As a concrete example, consider the case where a user makes an inquiry about a transaction using a smartphone application. When the user inputs an inquiry such as "Please tell me the payment details for Supplier A," the server extracts the transaction information for Supplier A from the MySQL® database and generates a payment detail.

[0418] The emotion engine then analyzes the user's tone of voice and facial expressions, adjusting the notification method to provide a detailed explanation if it detects that the user is dissatisfied, or a simple notification if it detects that the user is satisfied.

[0419] An example of a prompt for the generative AI model is as follows:

[0420] "The user has made an inquiry regarding a transaction. Please generate a payment breakdown based on the following information and notify the user.

[0421] Account: Account A

[0422] Transaction amount: 100,000 yen

[0423] Transaction Date: October 1, 2023

[0424] Transaction details: Product purchase

[0425] Also, recognize the user's emotions from their tone of voice and facial expressions and respond appropriately."

[0426] In this way, the system can respond quickly and appropriately to inquiries from business partners and provide optimal responses according to the user's feelings.

[0427] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0428] Step 1:

[0429] The user uses a terminal to input an inquiry about a transaction. The input inquiry is sent to the server. The input data includes the name of the customer, the transaction amount, the transaction date and time, and the transaction details.

[0430] Step 2:

[0431] The server analyzes the received inquiry and extracts the relevant transaction information from the MySQL® database. Based on the input data, the database is searched using criteria such as the client name and transaction date and time, and the relevant transaction information is obtained.

[0432] Step 3:

[0433] The server generates a payment breakdown based on the extracted transaction information, processing data such as the transaction amount, transaction date and time, and transaction details, and compiling it into a payment breakdown.

[0434] Step 4:

[0435] The server temporarily stores the generated payment details and then invokes the emotion engine, which uses Microsoft Azure Cognitive Services to analyze the user's tone of voice and facial expressions. The input data is the user's voice and image data, and the output data is the user's emotional information.

[0436] Step 5:

[0437] The emotion engine recognizes the user's emotions and returns the results to the server. For example, if the user is dissatisfied, it outputs "angry," and if they are satisfied, it outputs "happy."

[0438] Step 6:

[0439] The server receives emotion information from the emotion engine and adjusts the notification method. If the user is dissatisfied, it adds a detailed explanation of the payment details, and if the user is satisfied, it sends a brief notification. The input data is emotion information, and the output data is the adjusted notification content.

[0440] Step 7:

[0441] The server sends the adjusted notification content to the terminal, which then displays the received notification content to the user. The user can check the payment details based on the transaction information and an appropriate explanation according to their emotions.

[0442] In this way, the system can respond quickly and appropriately to inquiries from business partners and provide optimal responses according to the user's feelings.

[0443] Example 2

[0444] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0445] Conventional transaction information management systems have difficulty responding quickly and accurately to inquiries from business partners regarding payment details. Furthermore, they are unable to respond in response to the user's emotions, making it difficult to improve user satisfaction. In particular, when a user is dissatisfied, they require a detailed explanation, but conventional systems do not automate this process.

[0446] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0447] In this invention, the server includes means for managing transaction information with business partners, means for accepting inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiries and generating payment details, means for notifying the source of the inquiries of the generated payment details, means including an emotion engine for recognizing the user's emotions, and means for adjusting the method of notifying the payment details based on feedback from the emotion engine. This enables quick and accurate responses to inquiries from business partners and optimal responses according to the user's emotions.

[0448] "Transaction information" refers to information relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction details, etc.

[0449] "Inquiry" means a question or request from a business partner regarding payment details.

[0450] "Payment details" refers to detailed payment details generated based on transaction information, and includes the transaction amount, transaction date and time, transaction details, etc.

[0451] An "emotion engine" refers to software or hardware that recognizes a user's emotions from their tone of voice, facial expressions, choice of words, etc.

[0452] "Feedback" refers to information provided to the system based on the user's emotions as recognized by the emotion engine.

[0453] The "notification method" refers to the means by which the generated payment details are communicated to the inquirer, and includes email, push notification, etc.

[0454] "Server" refers to a computer system that manages transaction information, accepts inquiries, generates and notifies payment details, and operates the emotion engine.

[0455] "Database" refers to a data management system for storing transaction information and retrieving the information as needed.

[0456] "User" refers to a business partner or an individual or corporation that uses the system.

[0457] This invention is a system that manages transaction information and responds quickly and accurately to inquiries from business partners regarding payment details. It also recognizes the user's emotions and responds optimally accordingly.

[0458] System configuration

[0459] Management of transaction information

[0460] The server stores transaction information in a database. Transaction information includes the transaction amount, transaction date and time, transaction details, etc. For example, when a new transaction occurs, the server adds that information to the database. Database management systems such as MySQL (registered trademark) and PostgreSQL are used.

[0461] Receiving inquiries

[0462] A user makes a query using a device. The device sends the query to the server through a web browser or mobile application. For example, a representative at Client A might type, "Please tell me the payment details for last month's transactions." The query is sent to the server as an HTTP request.

[0463] Extracting information from a database

[0464] When the server receives a query from a user, it extracts the relevant transaction information from the database. Specifically, it uses an SQL query to search for transaction information for trading partner A. For example, it executes the query "SELECT FROM transactions WHERE client_id = 'A' AND date >= '2023-09-01' AND date <= '2023-09-30'".

[0465] Generate payment details

[0466] The server generates a payment statement based on the extracted transaction information. The payment statement details the transaction amount, date, and time, and transaction details. For example, a Python script can be used to format the extracted data and convert it into the payment statement format.

[0467] Payment details notification

[0468] The server automatically notifies the inquirer of the generated payment details. Notification methods include email and push notification. For example, the server sends the payment details to business partner A via email using the SMTP protocol.

[0469] Emotion Engine Operation

[0470] When a user makes a query, the device sends the user's tone of voice, facial expressions, and word choice to the emotion engine, which then uses voice recognition software (e.g., Google® Cloud Speech-to-Text) and facial expression recognition software (e.g., Microsoft Azure Face API) to recognize the user's emotions.

[0471] Responding according to emotions

[0472] The server receives feedback from the emotion engine and adjusts how it communicates the transaction details. For example, if it detects that the user is dissatisfied, it will prompt the server to provide a transaction detail with a detailed explanation. Conversely, if it detects that the user is satisfied, it will feed that information back and prompt the server to repeat the process for similar transactions.

[0473] Specific examples

[0474] When Customer A inquires, "Please tell me the payment details for last month's transactions," the server extracts last month's transaction information from the database and generates a payment detail. The generated payment detail is then sent to Customer A via email. If the emotion engine recognizes that Customer A's representative is dissatisfied at the time of the inquiry, the server will provide a payment detail with a detailed explanation.

[0475] Prompt Sentence Examples

[0476] "In response to an inquiry from Supplier A, please generate a payment breakdown based on last month's transaction information and send an email with a detailed explanation."

[0477] This system automates responses to inquiries from business partners, reducing man-hours. In addition, by using an emotion engine, it is possible to provide optimal responses based on the user's emotions.

[0478] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0479] Step 1:

[0480] The server stores transaction information in a database. As input, new transaction information (transaction amount, transaction date and time, transaction details) is provided. The server takes this information and inserts it into the database using an SQL query. As output, the new transaction information is added to the database. Specifically, the server executes the following SQL query:

[0481] sql

[0482] INSERT INTO transactions (client_id, amount, date, description) VALUES ('A', 1000, '2023-09-15', 'Product Purchase')

[0483] Step 2:

[0484] A user makes a query using a terminal. As input, the user enters the query content (e.g., "Please tell me the payment details for last month's transactions") into the terminal. The terminal sends this information as an HTTP request to the server. As output, the query content is sent to the server. Specifically, the terminal sends the following HTTP request to the server:

[0485] http

[0486] POST / api / inquiry

[0487] Content-Type: application / json

[0488] {

[0489] "client_id": "A",

[0490] "query": "What is the payment breakdown for last month's transactions?"

[0491] }

[0492] Step 3:

[0493] When the server receives a query from a user, it extracts the relevant transaction information from the database. The query content and customer ID are provided as input. The server uses an SQL query to search for the transaction information from the database. The relevant transaction information is extracted as output. Specifically, the server executes the following SQL query:

[0494] sql

[0495] SELECT FROM transactions WHERE client_id = 'A' AND date >= '2023-09-01' AND date <= '2023-09-30'

[0496] Step 4:

[0497] The server generates a payment breakdown based on the extracted transaction information. The extracted transaction information is provided as input. The server uses a Python script to format the transaction information and convert it into a payment breakdown format. The payment breakdown is generated as output. Specifically, the server performs the following processes:

[0498] python

[0499] def generate_payment_details(transactions):

[0500] details = "Account: A\n"

[0501] for transactions in transactions:

[0502] details += f"Transaction amount: {transaction['amount']} yen\n"

[0503] details += f"Transaction date and time: {transaction['date']}\n"

[0504] details += f"Transaction details: {transaction['description']}\n"

[0505] return details

[0506] Step 5:

[0507] The server automatically notifies the inquirer of the generated payment details. As input, the generated payment details and the inquirer's contact information are provided. The server sends the payment details by email using the SMTP protocol. As output, the inquirer is notified of the payment details. Specifically, the server sends an email like the one below.

[0508] email

[0509] To: clientA@example.com

[0510] Subject: Payment details

[0511] Customer: A

[0512] Transaction amount: 1000 yen

[0513] Transaction Date: 2023-09-15

[0514] Transaction details: Product purchase

[0515] Step 6:

[0516] When a user makes a query, the device sends the user's tone of voice, facial expression, choice of words, etc. to the emotion engine. The user's audio and video data are provided as input. The device sends this data to the emotion engine. As output, the emotion engine recognizes the user's emotion. Specifically, the device sends the following API request to the emotion engine:

[0517] http

[0518] POST / api / emotion

[0519] Content-Type: application / json

[0520] {

[0521] "audio": "base64_encoded_audio_data",

[0522] "video": "base64_encoded_video_data"

[0523] }

[0524] Step 7:

[0525] The server receives feedback from the emotion engine and adjusts the notification method for the payment details. Feedback information from the emotion engine is provided as input. The server uses this information to decide whether to generate a payment details with detailed explanations or a regular payment details. As output, the optimal payment details are generated and notified. Specifically, the server performs the following processes:

[0526] python

[0527] def adjust_notification_based_on_emotion(emotion_feedback, payment_details):

[0528] if emotion_feedback == "unhappy":

[0529] payment_details += "\nDetailed Description:\nThis transaction is for a purchase made on September 15, 2023. The transaction amount was 1000 yen, and the item was delivered the next day."

[0530] return payment_details

[0531] (Application example 2)

[0532] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0533] Conventional transaction information management systems have difficulty responding quickly and accurately to inquiries from business partners regarding payment details. Furthermore, they respond uniformly without considering the user's feelings, which can lead to a decline in user satisfaction. While appropriate responses are required when users feel dissatisfied or angry, conventional systems are unable to recognize such emotions and adjust their responses accordingly. This reduces the efficiency of inquiries and makes it difficult to improve user satisfaction.

[0534] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0535] In this invention, the server includes means for managing transaction information with business partners, means for accepting inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiry and generating a payment detail, means for notifying the inquirer of the generated payment detail, means for recognizing the user's emotion, and means for adjusting the notification method based on the recognized emotion. This makes it possible to respond quickly and accurately to inquiries from business partners, and further improve user satisfaction by providing an optimal response according to the user's emotion.

[0536] "Means for managing transaction information" refers to a system that stores information about transactions with business partners in a database and has the functions to update, search, and display that information as needed.

[0537] The "means for accepting inquiries regarding payment details" is a system that provides an interface for receiving questions or requests regarding payment details from business partners and initiating processing accordingly.

[0538] "Means for automatically extracting transaction information and generating payment details" refers to a system that has the function of automatically searching for relevant transaction information from a database based on received inquiries and creating payment details based on that information.

[0539] The "means for notifying the inquirer of the generated payment details" is a system having a function for automatically sending and notifying the supplier of the generated payment details.

[0540] The "means for recognizing user emotions" is a system that has the function of analyzing and recognizing emotions from the user's tone of voice, facial expressions, choice of words, etc.

[0541] The "means for adjusting the notification method based on the recognized emotion" is a system that has the function of optimizing the content and method of notification according to the user's emotion and taking appropriate action.

[0542] As an embodiment of the present invention, a system for managing transaction information and responding to inquiries from business partners is constructed. A specific embodiment of this system is shown below.

[0543] System configuration

[0544] The system consists of the following main components:

[0545] 1. Database Server: Manages the database for storing transaction information. SQLite can be used.

[0546] 2. Emotion Recognition Engine: An engine that analyzes the user's tone of voice and facial expressions to recognize emotions. EmotionEngine is used.

[0547] 3. Notification Service: A service for notifying the trading partner of the generated payment details. NotificationService is used.

[0548] 4. User interface: An interface for receiving inquiries from business partners. Implemented as a smartphone application.

[0549] Program processing

[0550] The server performs the process in the following procedure.

[0551] 1. Database connection: Connect to the database that stores transaction information using SQLite.

[0552] 2. Initialize the emotion engine: Recognize the user's emotions using the EmotionEngine.

[0553] 3. Initialize the notification service: Send notifications using NotificationService.

[0554] 4. Inquiry processing: Receives the client ID and inquiry details and extracts the relevant transaction information from the database.

[0555] 5. Generate payment details: Generate payment details based on the extracted transaction information.

[0556] 6. Emotion Recognition: Recognize user emotions using EmotionEngine.

[0557] 7. Adjust notification method: Adjust notification method according to user's emotions.

[0558] Specific examples

[0559] For example, if user A asks, "Tell me about your recent transactions," the system operates as follows:

[0560] 1. Extract user A's transaction information from the database.

[0561] 2. Generate payment details based on the extracted transaction information.

[0562] 3. Recognize User A's emotions from his / her tone of voice.

[0563] 4. If User A is dissatisfied, provide a detailed breakdown of the payment.

[0564] Prompt Sentence Examples

[0565] User A: Tell me about your recent transactions.

[0566] System: Extracting transaction information. Please wait a moment.

[0567] System: Transaction date and time: 2023-10-01, Amount: 10,000 yen, Content: Purchase of product A

[0568] System: Transaction date and time: 2023-10-05, Amount: 5,000 yen, Content: Purchase of product B

[0569] System: Detailed payment details have been provided.

[0570] In this way, the system can respond quickly and accurately to inquiries from business partners, and can also provide optimal responses based on the user's emotions, thereby improving user satisfaction.

[0571] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0572] Step 1:

[0573] The server connects to the database that stores transaction information using SQLite. The input is database connection information, and the output is the establishment of a database connection. In this step, a database connection object is created, allowing subsequent data manipulation.

[0574] Step 2:

[0575] The server initializes the EmotionEngine and prepares to recognize the user's emotions. The input required is the EmotionEngine's configuration information, and the output is a message indicating that the emotion recognition engine has been initialized. In this step, the emotion recognition engine is started and ready to analyze the user's emotions.

[0576] Step 3:

[0577] The server initializes the NotificationService and prepares to send notifications. The input requires configuration information for the NotificationService, and the output is the completion of initialization of the NotificationService. In this step, the NotificationService is started and is ready to notify the customer of the generated payment details.

[0578] Step 4:

[0579] The terminal accepts inquiries from business partners. The input requires the content of the inquiry from the business partner, and the output is the receipt of the content of the inquiry. In this step, the user makes an inquiry, and the content is input into the system.

[0580] Step 5:

[0581] The server extracts the relevant transaction information from the database based on the received query. The query content and the customer ID are required as input, and the relevant transaction information is obtained as output. In this step, the database query is executed and the transaction information is extracted.

[0582] Step 6:

[0583] The server generates a payment breakdown based on the extracted transaction information. The extracted transaction information is required as input, and the generated payment breakdown is obtained as output. In this step, the transaction information is analyzed and a payment breakdown is created.

[0584] Step 7:

[0585] The server uses the EmotionEngine to recognize the user's emotions. The inputs are the user's tone of voice and facial expressions, and the output is the recognized emotions. In this step, the user's emotions are analyzed and emotion data is generated.

[0586] Step 8:

[0587] The server adjusts the notification method based on the recognized emotion. The inputs are the recognized emotion and the generated payment details, and the output is the adjusted notification method. In this step, the content and method of the notification are optimized according to the user's emotion.

[0588] Step 9:

[0589] The server notifies the customer of the generated payment details using the NotificationService. The inputs are the adjusted notification method and the payment details, and the output is the notification completion. In this step, the payment details are sent to the customer and the notification is completed.

[0590] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0591] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0592] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are listed.

[0593] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0594] [Second embodiment]

[0595] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0596] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0597] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0598] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0599] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0600] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0601] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0602] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0603] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0604] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0605] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0606] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0607] "Example 1"

[0608] The system of the present invention stores transaction information in a database and provides an interface for accepting inquiries from business partners. When an inquiry is received, the system automatically extracts the relevant transaction information from the database and generates a payment breakdown. The generated payment breakdown is automatically notified to the source of the inquiry. For example, when an inquiry is received from business partner A, the system extracts transaction information with business partner A from the database and generates a payment breakdown based on the transaction amount, transaction date and time, and transaction details. The generated payment breakdown is automatically notified to business partner A. This makes it possible to automate responses to inquiries regarding payment breakdowns and reduce labor costs.

[0609] "Example 2"

[0610] The system of the present invention stores transaction information in a database and provides an interface for accepting inquiries from business partners. When an inquiry is received, the system automatically extracts the relevant transaction information from the database and generates a payment breakdown. The generated payment breakdown is automatically notified to the source of the inquiry. For example, when an inquiry is received from business partner A, the system extracts transaction information with business partner A from the database and generates a payment breakdown based on the transaction amount, transaction date and time, and transaction details. The generated payment breakdown is automatically notified to business partner A. This makes it possible to automate responses to inquiries regarding payment breakdowns and reduce labor costs.

[0611] The processing flow of each embodiment will be described below.

[0612] "Example 1"

[0613] Step 1: A customer inquiry is entered into the system, for example via a web interface or email.

[0614] Step 2: When the system receives an inquiry, it automatically extracts the relevant transaction information from the database based on the customer information contained in the inquiry (e.g., customer name, ID, etc.).

[0615] Step 3: Generate a payment breakdown from the extracted transaction information. The payment breakdown includes information such as the transaction amount, transaction date and time, and transaction content.

[0616] Step 4: The generated payment details are sent to the inquirer, for example via email or a web interface.

[0617] "Example 2"

[0618] Step 1: A customer inquiry is entered into the system, for example via a web interface or email.

[0619] Step 2: When the system receives an inquiry, it automatically extracts the relevant transaction information from the database based on the customer information contained in the inquiry (e.g., customer name, ID, etc.).

[0620] Step 3: Generate a payment breakdown from the extracted transaction information. The payment breakdown includes information such as the transaction amount, transaction date and time, and transaction content.

[0621] Step 4: The generated payment details are sent to the inquirer, for example via email or a web interface.

[0622] Example 1

[0623] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0624] Conventional transaction information management systems require manual responses to inquiries about payment details from business partners, which requires a significant amount of time and effort. Manual responses also carry the risk of human error, resulting in inaccuracies. Furthermore, the complicated process of inputting and managing transaction information makes efficient operation difficult.

[0625] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0626] In this invention, the server includes means for managing transaction information with business partners, means for accepting inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiry and generating a payment detail, means for notifying the inquirer of the generated payment detail, means for providing an interface for inputting transaction information, means for storing the transaction information in a database, means for recording the inquiry content in a log file, and means for notifying the payment detail by email. This makes it possible to automate the management of transaction information and response to inquiries, thereby reducing labor hours and improving accuracy.

[0627] "Transaction information" refers to detailed data relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction content, and the like.

[0628] "Business partner" refers to a customer or client who receives goods or services.

[0629] "Payment details" is information provided to a trading partner that indicates details of a transaction, including the transaction amount, transaction date and time, transaction content, and the like.

[0630] "Inquiry" refers to a request from a business partner for information or confirmation.

[0631] A "server" refers to a computer system that processes and manages data on a network.

[0632] A "database" refers to a system for systematically storing and managing data such as transaction information.

[0633] An "interface" refers to the means or method by which a user interacts with a system.

[0634] A "log file" refers to a file that records system actions and events.

[0635] "Email" refers to a means of sending and receiving messages electronically.

[0636] MODE FOR CARRYING OUT THE INVENTION

[0637] The present invention relates to a system for managing transaction information and automatically responding to inquiries from business partners regarding payment details. A specific embodiment of this system will be described below.

[0638] System configuration

[0639] This system consists of three main components: a server, a terminal, and a user. The server plays a central role in managing transaction information, accepting inquiries, and generating and notifying payment details. The terminal provides an interface for users to input transaction information and make inquiries. The user is the entity that inputs transaction information and makes inquiries.

[0640] Hardware and software used

[0641] The server uses a general web server (for example, Apache (registered trademark) or Nginx (registered trademark)), and the database uses a relational database such as MySQL (registered trademark) or PostgreSQL. Programming languages ​​such as Python and Java are used to implement the program. The terminal uses a web browser for user access.

[0642] Data processing and calculation

[0643] The server receives the transaction information entered by the user and stores it in a database. When an inquiry is received from a business partner, the server extracts the relevant transaction information from the database and generates a payment breakdown. The generated payment breakdown is then sent to the business partner by email.

[0644] Specific examples

[0645] For example, if a business partner A inquires, "Please tell me the details of transactions for September 2023," the server will process the inquiry using the following procedure.

[0646] 1. The server accepts an inquiry from business partner A.

[0647] 2. The server extracts trading information for trading partner A for September 2023 from the database.

[0648] 3. Based on the extracted transaction information, the server generates a payment breakdown including the transaction amount, transaction date and time, and transaction details.

[0649] 4. The server sends the generated payment details to Customer A via email.

[0650] Prompt Sentence Examples

[0651] "In response to an inquiry from Business Partner A asking for a transaction breakdown for September 2023, please create a program that will extract the relevant transaction information from the database, generate a payment breakdown, and notify the customer by email."

[0652] In this way, this system automates the management of transaction information and response to inquiries, thereby improving the efficiency and accuracy of operations.

[0653] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0654] Step 1:

[0655] The user enters the transaction information.

[0656] The user accesses a web form for entering transaction information and enters information such as the client name, transaction amount, transaction date and time, and transaction details. Specifically, the user enters "Client name: Client A, transaction amount: 100,000 yen, transaction date and time: 2023-09-15, transaction details: product purchase" and clicks the "Submit" button. The entered data is sent to the server.

[0657] Step 2:

[0658] The server stores the transaction information in a database.

[0659] The server receives the transaction information sent by the user and stores it in the database. Specifically, the server executes the SQL query "INSERT INTO transactions (client_name, amount, date, description) VALUES ('Customer A', 100000, '2023-09-15', 'Product Purchase');". The input is the transaction information sent by the user, and the output is the transaction information stored in the database.

[0660] Step 3:

[0661] A business partner makes an inquiry.

[0662] The business partner accesses the interface for making an inquiry and enters the details of the inquiry. Specifically, business partner A enters "Please tell me the transaction details for September 2023" and clicks the "Send" button. The entered inquiry details are sent to the server.

[0663] Step 4:

[0664] The server accepts the query.

[0665] The server accepts inquiries from business partners and records the inquiry details in a log file. Specifically, the server records a log stating, "An inquiry from business partner A has been accepted." The input is the inquiry details sent by the business partner, and the output is the inquiry details recorded in the log file.

[0666] Step 5:

[0667] The server retrieves the relevant transaction information from the database.

[0668] The server extracts the relevant transaction information from the database based on the query. Specifically, the server executes the SQL query "SELECT FROM transactions WHERE client_name = 'Customer A' AND date LIKE '2023-09%';". The input is the query, and the output is the extracted transaction information.

[0669] Step 6:

[0670] The server generates the payment details.

[0671] The server generates a payment breakdown based on the extracted transaction information. Specifically, the server generates the following breakdown: "Transaction breakdown for customer A in September 2023: 1. Transaction amount: 100,000 yen, Transaction date and time: 2023-09-15, Transaction content: Product purchase." The input is the extracted transaction information, and the output is the generated payment breakdown.

[0672] Step 7:

[0673] The server notifies the customer of the payment details generated.

[0674] The server notifies the client of the generated payment details by email. Specifically, the server records a log stating "Payment details have been sent to client A by email" and sends the email via the SMTP server. The input is the generated payment details, and the output is the email sent to the client.

[0675] (Application example 1)

[0676] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0677] With conventional transaction information management systems, it was difficult to respond quickly and accurately to inquiries about payment details from business partners. Furthermore, there was a problem in that analyzing the content of inquiries and extracting the appropriate transaction information required a great deal of time and effort. Furthermore, there was a lack of a way for users to easily check transaction information via smartphone.

[0678] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0679] In this invention, the server includes means for managing transaction information with business partners, means for accepting inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiry and generating a payment detail, means for notifying the originator of the inquiry of the generated payment detail, means for displaying the transaction information via an application installed on the smartphone, and means for analyzing the inquiry using a generative AI model and extracting transaction information based on a prompt sentence. This allows for quick and accurate responses to inquiries from business partners and enables users to easily check transaction information via their smartphones.

[0680] "Transaction information" refers to information relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction details, etc.

[0681] "Payment details" is detailed payment information generated based on the transaction amount, transaction date and time, and transaction content for each business partner.

[0682] "Inquiry" refers to a question or request for confirmation from a business partner regarding payment details.

[0683] A "smartphone" is a multi-functional mobile device that can connect to the Internet and run applications in addition to the functions of a mobile phone.

[0684] An "application" is a software program that is installed on a smartphone and provides specific functions or services.

[0685] A "generative AI model" is a model that uses artificial intelligence technology to analyze data and automatically perform specific tasks.

[0686] A "prompt" is an instruction entered into a generative AI model, which serves as a trigger for extracting specific information.

[0687] The following system configuration will be described as an embodiment of the present invention.

[0688] System Configuration

[0689] The system includes a server, a smartphone, and a generative AI model. The server manages transaction information and generates payment details based on inquiries. The smartphone provides an interface for users to check the transaction information. The generative AI model analyzes the inquiry and extracts transaction information based on prompts.

[0690] Program processing explanation

[0691] Hardware:

[0692] Server: Database management system (e.g. SQLite)

[0693] Smartphone: Multi-function mobile device

[0694] software:

[0695] SQLite: Database Management System

[0696] Python: a programming language

[0697] Generative AI model: A data analysis model using artificial intelligence technology

[0698] Data processing and calculation:

[0699] 1. Connect to the database and create tables:

[0700] The server uses SQLite to create a database and tables to store the transaction information.

[0701] 2. Insert transaction information:

[0702] The server inserts the new transaction information into the database.

[0703] 3. Enquiry Processing:

[0704] The server retrieves transaction information for the specified merchant from the database.

[0705] 4. Generate payment details:

[0706] The server generates a payment breakdown based on the extracted transaction information.

[0707] 5. User Notice:

[0708] The generated payment details are displayed to the user via their smartphone.

[0709] 6. Use of generative AI models:

[0710] The generative AI model analyzes the query and extracts transaction information based on the prompt.

[0711] Specific examples

[0712] For example, if a user uses a smartphone to inquire about transaction information regarding "Customer A," they might enter a prompt like the following:

[0713] Example prompt sentence:

[0714] "Please tell me the transaction information regarding business partner A."

[0715] Once the prompt is entered, the generative AI model analyzes the query, and the server extracts the relevant transaction information from the database, after which a payment breakdown is generated and notified to the user via their smartphone.

[0716] In this way, the present invention allows for quick and accurate responses to inquiries from business partners and allows users to easily check transaction information via their smartphones.

[0717] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0718] Step 1:

[0719] The server connects to the SQLite database and creates a table to store the transaction information.

[0720] Input: Database connection information

[0721] Output: A table to store transaction information

[0722] What happens: The server connects to the SQLite database and creates a table named "transactions" with columns for transaction ID, customer, transaction amount, transaction date and time, and transaction details.

[0723] Step 2:

[0724] The server inserts the new transaction information into the database.

[0725] Input: Customer, transaction amount, transaction details

[0726] Output: New transaction information is added to the database

[0727] Specific operation: The server receives the client, transaction amount, and transaction details, obtains the current date and time, and inserts this information into the "transactions" table.

[0728] Step 3:

[0729] A user uses a smartphone to make an inquiry about a business partner.

[0730] Input: Prompt statement (e.g., "Please tell me the transaction information about Customer A.")

[0731] Output: The query is sent to the server

[0732] Specific operation: The user opens the application on their smartphone and enters a query about a client. The entered prompt is sent to the server.

[0733] Step 4:

[0734] The server uses a generative AI model to analyze the query and extract transaction information based on the prompt text.

[0735] Input: prompt statement

[0736] Output: Extracted transaction information

[0737] Specific operation: The server inputs a prompt sentence into the generative AI model, which then analyzes the query. Based on the analysis results, the server extracts the transaction information of the relevant trading partner from the database.

[0738] Step 5:

[0739] The server generates a payment breakdown based on the extracted transaction information.

[0740] Input: Extracted transaction information

[0741] Output: Payment details

[0742] Specific operation: Based on the extracted transaction information, the server generates a payment breakdown including the transaction ID, transaction amount, transaction date and time, and transaction details.

[0743] Step 6:

[0744] The server notifies the smartphone of the generated payment details.

[0745] Input: Payment details

[0746] Output: Payment details displayed on smartphone

[0747] Specific operation: The server sends the generated payment details to the smartphone, where the user can check them through the application.

[0748] Step 7:

[0749] Users can check their payment details via their smartphone.

[0750] Input: Payment details displayed on smartphone

[0751] Output: Payment details confirmed by the user

[0752] Specific operation: The user opens the application on their smartphone and checks the displayed payment details.

[0753] Example 2

[0754] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0755] With conventional transaction information management systems, inquiries about payment details from business partners had to be handled manually, which was a time-consuming process. Furthermore, manual responses carried the risk of human error, making it difficult to respond to business partners promptly. This could result in reduced operational efficiency and a loss of trust from business partners.

[0756] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0757] In this invention, the server includes means for managing transaction information with business partners, means for receiving inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiry and generating a payment detail, means for notifying the inquirer of the generated payment detail, means for a user to input transaction information, means for the server to store the transaction information in a database, means for the server to extract relevant transaction information from the database, means for the server to generate a payment detail, and means for notifying the inquirer of the generated payment detail. This makes it possible to automate responses to inquiries regarding payment details and reduce man-hours.

[0758] "Transaction information" refers to information relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction details, etc.

[0759] "Business Partner" means a party with whom a transaction is conducted using the system.

[0760] "Payment details" is information showing details of the amount to be paid to the business partner, including the transaction amount, transaction date and time, transaction content, etc.

[0761] An "inquiry" is an action in which a business partner requests information regarding payment details through the system.

[0762] A "database" is a system for storing and managing transaction information.

[0763] A "server" is a computer system that manages the entire system and executes various processes.

[0764] "User" means a person who utilizes the system to enter transaction information.

[0765] "Automatically extracting" means that the system retrieves the necessary information from the database without human intervention.

[0766] "Generating" means that the system creates a payment breakdown based on the transaction information.

[0767] "Notifying" means transmitting the payment details generated by the system to the trading partner.

[0768] The present invention is a system for managing transaction information and automatically responding to inquiries from business partners regarding payment details. A specific embodiment of this system will be described below.

[0769] System configuration

[0770] Hardware

[0771] 1. Server

[0772] Database server (e.g., MySQL (registered trademark), PostgreSQL)

[0773] Web server (e.g., Apache (registered trademark), Nginx (registered trademark))

[0774] Mail server (e.g. SendGrid, Amazon SES)

[0775] 2. Terminal

[0776] PCs and smartphones used by users and business partners

[0777] software

[0778] 1. Database Management System (DBMS)

[0779] MySQL (registered trademark), PostgreSQL, etc.

[0780] 2. Web Application Frameworks

[0781] Django, Ruby on Rails, etc.

[0782] 3. Data processing script

[0783] Python, JavaScript, etc.

[0784] 4. Email Sending Library

[0785] SMTP, SendMail, etc.

[0786] System Operation

[0787] 1. The user enters transaction information

[0788] The user uses a terminal to access the web interface and inputs transaction information such as the transaction amount, transaction date and time, and transaction details.

[0789] Specific behavior: The user enters transaction information into the form and clicks the "Submit" button.

[0790] 2. The server stores the transaction information in a database

[0791] The server receives the transaction information sent by the user and stores it in a database.

[0792] Specific operation: The server executes an SQL query to insert the transaction information into the database.

[0793] 3. A business partner makes an inquiry

[0794] The customer uses a terminal to access a web interface and make inquiries about payment details.

[0795] Specific operation: The client enters the required information into the inquiry form and clicks the "Submit" button.

[0796] 4. The server accepts the query

[0797] The server receives an inquiry from a business partner and analyzes the inquiry content.

[0798] Specific operation: The server analyzes the inquiry content and identifies the corresponding customer ID.

[0799] 5. The server extracts the relevant transaction information from the database.

[0800] The server extracts transaction information from a database based on the identified merchant ID.

[0801] Specific operation: The server executes an SQL query to select the relevant transaction information.

[0802] 6. The server generates the payment details

[0803] The server generates a payment breakdown based on the extracted transaction information.

[0804] What happens: The server runs a data processing script to calculate and format the payment details.

[0805] 7. The server notifies the inquirer of the payment details generated by the server.

[0806] The server notifies the inquirer of the generated payment details by email.

[0807] Specific behavior: The server uses the email sending library to send an email containing the payment details.

[0808] Specific examples

[0809] Inquiry from Business Partner A

[0810] 1. Supplier A inquires about payment details through the web interface.

[0811] 2. The server extracts the transaction information of trading partner A (transaction amount, transaction date and time, transaction details) from the database.

[0812] 3. The server generates a payment breakdown based on the extracted information.

[0813] 4. The server sends the generated payment details to Customer A via email.

[0814] Example prompts to input to the generative AI model

[0815] "We have received an inquiry about payment details from Supplier A. Please extract Supplier A's transaction information from the database, generate a payment detail, and notify us by email."

[0816] This system automates responses to inquiries regarding payment details, reducing man-hours.

[0817] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0818] Step 1:

[0819] The user enters the transaction information.

[0820] Input: The user uses a terminal to access the web interface and inputs transaction information such as the transaction amount, transaction date and time, and transaction details.

[0821] Data processing: The transaction information entered by the user is sent to the server as form data.

[0822] Output: The transaction information sent to the server.

[0823] Specific behavior: The user enters transaction information into the form and clicks the "Submit" button.

[0824] Step 2:

[0825] The server stores the transaction information in a database.

[0826] Input: Transaction information submitted by the user.

[0827] Data processing: The server inserts the received transaction information into the database using an SQL query.

[0828] Output: Transaction information stored in a database.

[0829] Specific operation: The server executes an SQL query to insert the transaction information into the database.

[0830] Step 3:

[0831] A business partner makes an inquiry.

[0832] Input: The customer uses a terminal to access the web interface and make an inquiry about the payment details.

[0833] Data processing: The inquiry details entered by the business partner are sent to the server as form data.

[0834] Output: The query sent to the server.

[0835] Specific operation: The client enters the required information into the inquiry form and clicks the "Submit" button.

[0836] Step 4:

[0837] The server accepts the query.

[0838] Input: Inquiry sent by business partner.

[0839] Data processing: The server analyzes the inquiry content and identifies the corresponding customer ID.

[0840] Output: The identified account ID.

[0841] Specific operation: The server analyzes the inquiry content and identifies the corresponding customer ID.

[0842] Step 5:

[0843] The server retrieves the relevant transaction information from the database.

[0844] Input: A specific account ID.

[0845] Data processing: The server executes an SQL query to select the relevant transaction information from the database.

[0846] Output: Extracted transaction information.

[0847] Specific operation: The server executes an SQL query to select the relevant transaction information.

[0848] Step 6:

[0849] The server generates the payment details.

[0850] Input: Extracted transaction information.

[0851] Data Processing: The server runs data processing scripts to calculate and format payment details.

[0852] Output: The generated payment breakdown.

[0853] What happens: The server runs a data processing script to calculate and format the payment details.

[0854] Step 7:

[0855] The server notifies the inquirer of the generated payment details.

[0856] Input: Generated payment breakdown.

[0857] Data processing: The server uses an email sending library to send an email containing the payment details.

[0858] Output: Payment breakdown email sent to the inquirer.

[0859] Specific behavior: The server uses the email sending library to send an email containing the payment details.

[0860] (Application example 2)

[0861] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0862] With conventional transaction information management systems, it was difficult to respond quickly and accurately to inquiries from business partners regarding payment details, and manual responses were required, resulting in increased workload. Furthermore, there was a lack of efficient methods for managing transaction information and responding to inquiries using smart devices. This resulted in issues such as poor communication with business partners and reduced operational efficiency.

[0863] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0864] In this invention, the server includes means for managing transaction information with business partners, means for accepting inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiries and generating payment details, means for notifying the originator of the inquiries of the generated payment details, and means for managing transaction information, accepting inquiries, and generating and notifying payment details via an application installed on the smart device. This enables quick and accurate responses to inquiries from business partners, significantly improving business efficiency.

[0865] "Transaction information" refers to detailed data relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction content, and the like.

[0866] "Payment details" is detailed information about payments for each supplier that is generated based on transaction information, and includes the transaction amount, transaction date and time, transaction content, and the like.

[0867] "Inquiry" refers to a question or request for confirmation from a business partner regarding payment details.

[0868] "Smart devices" refers to electronic devices with internet connectivity, such as smartphones, tablets, smart glasses, and head-mounted displays.

[0869] An "application" is a software program installed on a smart device that provides specific functions or services.

[0870] A "server" refers to a computer system that stores, processes, and manages data over a network.

[0871] "Automatic extraction" refers to the process in which the system selects the necessary information from the database without human intervention.

[0872] "Notification" refers to the act of informing the trading partner of the generated payment details.

[0873] A system for implementing the present invention includes a server, a smart device, and an application installed thereon. Specific embodiments are described below.

[0874] System Configuration

[0875] The server has a database for managing transaction information and provides an interface for accepting inquiries from business partners. An application for managing transaction information, accepting inquiries, and generating and notifying payment details is installed on the smart device.

[0876] Hardware and software used

[0877] Hardware: Servers, smart devices such as smartphones, tablets, smart glasses, and head-mounted displays.

[0878] Software: Python, Flask (web framework), SQLite (database).

[0879] Data processing and calculation

[0880] 1. Database initialization: The server initializes the SQLite database and creates a table to store transaction information.

[0881] 2. Inquiry reception: The application on the smart device receives inquiries from business partners in JSON format.

[0882] 3. Transaction information extraction: The server automatically extracts the transaction information of the relevant trading partner from the SQLite database.

[0883] 4. Generate payment details: Generate payment details based on the extracted transaction information.

[0884] 5. Automatic notification: The generated payment details are sent to the inquirer in JSON format.

[0885] Specific examples

[0886] When business partner A uses a smartphone to inquire about his / her transaction information, the following steps are taken.

[0887] 1. Client A launches the application on their smartphone and inquires about transaction information.

[0888] 2. The application sends a JSON request to the server containing the name of Customer A.

[0889] 3. The server extracts the transaction information for Customer A from the SQLite database and generates a payment breakdown.

[0890] 4. The generated payment details are sent to Customer A in JSON format.

[0891] Prompt Sentence Examples

[0892] "Please generate a request to inquire about trading information for trading partner A."

[0893] In this way, a specific embodiment for carrying out the invention has been shown. This system makes it possible to respond to inquiries from business partners quickly and accurately, thereby significantly improving business efficiency.

[0894] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0895] Step 1:

[0896] The server initializes an SQLite database and creates a table to store transaction information. Specifically, the server establishes a database connection and executes SQL commands to create a table to store transaction information. The input is a request to initialize the database, and the output is the initialized database.

[0897] Step 2:

[0898] A user launches an application on a smart device and makes an inquiry about transaction information. Specifically, the user enters the name of a trading partner into the application's inquiry form and presses the submit button. The input is the trading partner's name, and the output is an inquiry request.

[0899] Step 3:

[0900] The terminal sends a JSON request including the name of the customer to the server. Specifically, the application converts the customer name entered by the user into JSON format and sends it as an HTTP request to the server. The input is the customer name, and the output is a JSON request to the server.

[0901] Step 4:

[0902] The server extracts the transaction information of the corresponding trading partner from the SQLite database. Specifically, the server parses the received JSON request and generates an SQL query based on the trading partner name to search the database. The input is the JSON request, and the output is the corresponding transaction information.

[0903] Step 5:

[0904] The server generates a payment breakdown based on the extracted transaction information. Specifically, the server analyzes the extracted transaction information and generates a payment breakdown including the transaction amount, transaction date and time, and transaction details. The input is the transaction information, and the output is the payment breakdown.

[0905] Step 6:

[0906] The server notifies the inquirer of the generated payment details in JSON format. Specifically, the server converts the generated payment details into JSON format and sends it to the terminal as an HTTP response. The input is the payment details, and the output is a JSON response.

[0907] Step 7:

[0908] The terminal displays the received payment details to the user. Specifically, the application parses the received JSON response and displays the payment details in a user-friendly format. The input is the JSON response and the output is the payment details displayed to the user.

[0909] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0910] "Example 1"

[0911] In one embodiment of the present invention, an emotion engine is incorporated. This emotion engine recognizes a user's emotions from the user's tone of voice, facial expression, and choice of words. For example, if a user's tone of voice or facial expression indicates anger or frustration when making an inquiry, the emotion engine captures this information. Based on this information, the emotion engine then adjusts the notification method for the payment details. Specifically, if the emotion engine recognizes that the user is frustrated, it instructs the system to provide a detailed explanation of the payment details. Similarly, if the emotion engine recognizes that the user is happy or satisfied, it feeds this information back to the system and instructs the system to take the same steps next time a similar transaction occurs. This allows the system to respond optimally based on the user's emotions.

[0912] "Example 2"

[0913] In one embodiment of the present invention, an emotion engine is incorporated. This emotion engine recognizes a user's emotions from the user's tone of voice, facial expression, and choice of words. For example, if a user's tone of voice or facial expression indicates anger or frustration when making an inquiry, the emotion engine captures this information. Based on this information, the emotion engine then adjusts the notification method for the payment details. Specifically, if the emotion engine recognizes that the user is frustrated, it instructs the system to provide a detailed explanation of the payment details. Similarly, if the emotion engine recognizes that the user is happy or satisfied, it feeds this information back to the system and instructs the system to take the same steps next time a similar transaction occurs. This allows the system to respond optimally based on the user's emotions.

[0914] The processing flow of each embodiment will be described below.

[0915] "Example 1"

[0916] Step 1: The user queries the system, and the emotion engine captures the user's tone of voice, facial expression, and choice of words.

[0917] Step 2: The emotion engine recognizes the user's emotions from the captured information. For example, if the user senses anger or frustration from the tone of voice or facial expression, the emotion engine will capture that information.

[0918] Step 3: The emotion engine adjusts the notification of the payment details based on the recognized emotion. Specifically, if the emotion engine recognizes that the user is dissatisfied, it instructs the system to provide a detailed explanation of the payment details.

[0919] Step 4: If the emotion engine detects that the user is feeling happy or satisfied, it feeds that information back into the system, instructing it to follow the same steps when a similar transaction occurs.

[0920] Step 5: The system notifies the user of the payment details based on the instructions from the emotion engine, allowing the system to take the most appropriate action based on the user's emotions.

[0921] "Example 2"

[0922] Step 1: The user queries the system, and the emotion engine captures the user's tone of voice, facial expression, and choice of words.

[0923] Step 2: The emotion engine recognizes the user's emotions from the captured information. For example, if the user senses anger or frustration from the tone of voice or facial expression, the emotion engine will capture that information.

[0924] Step 3: The emotion engine adjusts the notification of the payment details based on the recognized emotion. Specifically, if the emotion engine recognizes that the user is dissatisfied, it instructs the system to provide a detailed explanation of the payment details.

[0925] Step 4: If the emotion engine detects that the user is feeling happy or satisfied, it feeds that information back into the system, instructing it to follow the same steps when a similar transaction occurs.

[0926] Step 5: The system notifies the user of the payment details based on the instructions from the emotion engine, allowing the system to take the most appropriate action based on the user's emotions.

[0927] Example 1

[0928] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0929] Conventional transaction information management systems have difficulty responding quickly and accurately to inquiries from business partners regarding payment details. Furthermore, they are unable to respond in a way that takes into account the user's feelings, making it difficult to improve user satisfaction. In particular, when a user is dissatisfied, they require a detailed explanation, but conventional systems do not automate such responses.

[0930] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0931] In this invention, the server includes means for managing transaction information with business partners, means for receiving inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiry and generating a payment detail, means for notifying the inquirer of the generated payment detail, means for recognizing the user's emotion, and means for adjusting the method of notifying the payment detail based on the recognized emotion. This not only automates the management of transaction information and the generation and notification of payment details, but also enables optimal responses according to the user's emotion.

[0932] "Transaction information" refers to information relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction details, etc.

[0933] "Business Partner" means a party with whom a transaction is conducted using the system.

[0934] "Payment details" refers to detailed payment details generated based on transaction information, and includes the transaction amount, transaction date and time, transaction details, and the like.

[0935] An "inquiry" is a request made by a business partner to the system for information or confirmation.

[0936] A "database" is an information system for storing and managing transaction information.

[0937] An "emotion engine" is software or hardware that recognizes a user's emotions from their tone of voice, facial expressions, choice of words, etc.

[0938] "Notification" refers to the act of transmitting the generated payment details to the trading partner, and is done via email or a notification function within the web application.

[0939] "User" means any person or entity that uses the System to manage or inquire about transaction information.

[0940] "Server" refers to the computer system that processes the entire system, managing transaction information, accepting inquiries, and generating and notifying payment details.

[0941] This invention is a system that manages transaction information, automatically generates and notifies payment details in response to inquiries from business partners, and can also recognize the user's emotions and respond accordingly.

[0942] System configuration

[0943] Management of transaction information

[0944] The server stores transaction information in a database. Specifically, information such as the customer ID, transaction date and time, transaction amount, and transaction details is saved in a MySQL (registered trademark) database. For example, when a new transaction occurs, the server receives that information and inserts it into the database using SQL statements.

[0945] Receiving inquiries

[0946] Users use the web application interface to make inquiries about transaction information. The terminal (user's PC or smartphone) accesses this interface through a browser. Inquiries are made by filling out a form or by voice input.

[0947] Processing inquiries

[0948] The server receives the user's inquiry and extracts the relevant transaction information from the database. Specifically, it executes an SQL query to retrieve the data based on the customer ID and transaction date and time entered by the user in the form.

[0949] Generate payment details

[0950] The server generates a payment breakdown based on the extracted transaction information. A Python script is used to calculate the transaction amount, transaction date and time, and transaction details to create a detailed payment breakdown. For example, if transaction information for Customer A is extracted, the Python script processes the information and generates a payment breakdown.

[0951] Payment details notification

[0952] The server notifies the inquiring business partner of the generated payment details. Notification can be via email or a notification function within a web application. For example, the generated payment details can be sent to business partner A by email.

[0953] Recognizing user emotions with an emotion engine

[0954] When a user makes a query, the emotion engine recognizes the user's emotion from the user's tone of voice, facial expression, choice of words, etc. The emotion engine is implemented using a general emotion recognition API. For example, when a user makes a voice input, the emotion engine analyzes the voice data and recognizes the emotion.

[0955] Adjusting responses according to emotions

[0956] The server adjusts how it notifies users of payment details based on information from the emotion engine. Specifically, if it recognizes that the user is dissatisfied, it instructs the system to provide a detailed payment detail. If it recognizes that the user is happy or satisfied, it feeds that information back into the system and instructs it to take the same steps next time a similar transaction occurs.

[0957] Specific examples

[0958] For example, if a business partner A inquires, "Please tell me the payment details of recent transactions," the server will process the inquiry using the following procedure.

[0959] 1. The server extracts trading information for Trading Partner A from the MySQL® database.

[0960] 2. The server uses a Python script to generate a payment breakdown based on the transaction amount, transaction date and time, and transaction details.

[0961] 3. The server notifies Customer A of the generated payment details via email.

[0962] 4. When a user makes an inquiry, the emotion engine analyzes the user's tone of voice and facial expressions and recognizes that they are feeling angry or frustrated.

[0963] 5. The server provides a payment breakdown with detailed explanations based on the information from the emotion engine.

[0964] Prompt Sentence Examples

[0965] "If a customer A asks for a payment breakdown of their recent transaction, please explain how the system will handle this."

[0966] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0967] Step 1:

[0968] The server stores the transaction information in a database. As input, it receives transaction information such as the customer ID, transaction date and time, transaction amount, and transaction details. Specifically, it inserts this information into a MySQL® database using SQL statements. As output, it saves the new transaction information in the database.

[0969] Step 2:

[0970] A user uses a web application interface to make an inquiry about transaction information. As input, the user enters the inquiry details, such as the trading partner ID and transaction date and time, into a form. Specifically, the terminal (the user's PC or smartphone) accesses this interface through a browser and sends the inquiry details. As output, the inquiry details are sent to the server.

[0971] Step 3:

[0972] The server receives the user's inquiry and extracts the relevant transaction information from the database. As input, it receives the customer ID and transaction date and time entered by the user in the form. Specifically, it executes an SQL query to retrieve the relevant transaction information from the database. As output, the relevant transaction information is extracted.

[0973] Step 4:

[0974] The server generates a payment breakdown based on the extracted transaction information. It receives the extracted transaction information as input. Specifically, it uses a Python script to calculate the transaction amount, transaction date and time, and transaction details to create a detailed payment breakdown. The payment breakdown is generated as output.

[0975] Step 5:

[0976] The server notifies the inquiring business partner of the generated payment details. It receives the generated payment details as input. Specific operations include sending the payment details via email or using a notification function within the web application. The output is a notification of the payment details to the business partner.

[0977] Step 6:

[0978] When a user makes a query, the emotion engine recognizes the user's emotions from the user's tone of voice, facial expressions, choice of words, etc. As input, it receives the user's voice data and facial expression data. Specifically, it uses an emotion recognition API to analyze this data and recognize the user's emotions. As output, it generates the user's emotional information.

[0979] Step 7:

[0980] The server adjusts the notification method for payment details based on information from the emotion engine. As input, it receives the user's emotional information. Specifically, if it recognizes that the user is dissatisfied, it instructs the system to provide a payment detail with a detailed explanation. If it recognizes that the user is happy or satisfied, it feeds that information back to the system and instructs it to take the same steps when a similar transaction occurs. As output, it responds optimally according to the emotion.

[0981] (Application example 1)

[0982] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0983] Conventional transaction information management systems had the problem of being unable to respond quickly and appropriately to inquiries from business partners regarding payment details. Furthermore, because they responded uniformly without considering the user's feelings, there was a risk of user satisfaction declining. This posed a risk of damaging trusting relationships with business partners.

[0984] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0985] In this invention, the server includes means for managing transaction information with business partners, means for accepting inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiries and generating payment details, means for notifying the inquirer of the generated payment details, means including an emotion engine for recognizing the user's emotions, and means for adjusting the notification method according to the user's emotions. This makes it possible to respond quickly and appropriately to inquiries from business partners and to provide an optimal response according to the user's emotions.

[0986] "Transaction information" refers to detailed data relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction content, and the like.

[0987] "Payment details" is a list of detailed payment details generated based on transaction information, and includes the transaction amount, transaction date and time, transaction details, etc.

[0988] "Inquiry" refers to a question or request for confirmation from a business partner regarding payment details.

[0989] An "emotion engine" is a technology that recognizes a user's emotions from their tone of voice, facial expressions, choice of words, etc.

[0990] "Notification method" refers to the means or method for transmitting the generated payment details to the trading partner.

[0991] "Business partner" refers to the company or individual that is the subject of business information.

[0992] "User" refers to the entity that manages transaction information and makes inquiries.

[0993] "Server" refers to a computer system that manages transaction information and responds to inquiries.

[0994] A system for implementing this invention manages transaction information and responds to inquiries from business partners regarding payment details. The system includes a server for managing transaction information, a terminal for accepting inquiries, and an emotion engine for recognizing user emotions.

[0995] The server manages transaction information using a MySQL (registered trademark) database. Transaction information includes the transaction amount, transaction date and time, and transaction details for each customer. When a user makes an inquiry through their terminal, the server automatically extracts the relevant transaction information and generates a payment breakdown.

[0996] The generated payment details are sent to the inquirer via the terminal. The notification method is adjusted according to the user's emotions by an emotion engine. The emotion engine uses Microsoft Azure Cognitive Services to analyze the user's tone of voice and facial expressions to recognize emotions.

[0997] As a concrete example, consider the case where a user makes an inquiry about a transaction using a smartphone application. When the user inputs an inquiry such as "Please tell me the payment details for Supplier A," the server extracts the transaction information for Supplier A from the MySQL® database and generates a payment detail.

[0998] The emotion engine then analyzes the user's tone of voice and facial expressions, adjusting the notification method to provide a detailed explanation if it detects that the user is dissatisfied, or a simple notification if it detects that the user is satisfied.

[0999] An example of a prompt for the generative AI model is as follows:

[1000] "The user has made an inquiry regarding a transaction. Please generate a payment breakdown based on the following information and notify the user.

[1001] Account: Account A

[1002] Transaction amount: 100,000 yen

[1003] Transaction Date: October 1, 2023

[1004] Transaction details: Product purchase

[1005] Also, recognize the user's emotions from their tone of voice and facial expressions and respond appropriately."

[1006] In this way, the system can respond quickly and appropriately to inquiries from business partners and provide optimal responses according to the user's feelings.

[1007] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1008] Step 1:

[1009] The user uses a terminal to input an inquiry about a transaction. The input inquiry is sent to the server. The input data includes the name of the customer, the transaction amount, the transaction date and time, and the transaction details.

[1010] Step 2:

[1011] The server analyzes the received inquiry and extracts the relevant transaction information from the MySQL® database. Based on the input data, the database is searched using criteria such as the client name and transaction date and time, and the relevant transaction information is obtained.

[1012] Step 3:

[1013] The server generates a payment breakdown based on the extracted transaction information, processing data such as the transaction amount, transaction date and time, and transaction details, and compiling it into a payment breakdown.

[1014] Step 4:

[1015] The server temporarily stores the generated payment details and then invokes the emotion engine, which uses Microsoft Azure Cognitive Services to analyze the user's tone of voice and facial expressions. The input data is the user's voice and image data, and the output data is the user's emotional information.

[1016] Step 5:

[1017] The emotion engine recognizes the user's emotions and returns the results to the server. For example, if the user is dissatisfied, it outputs "angry," and if they are satisfied, it outputs "happy."

[1018] Step 6:

[1019] The server receives emotion information from the emotion engine and adjusts the notification method. If the user is dissatisfied, it adds a detailed explanation of the payment details, and if the user is satisfied, it sends a brief notification. The input data is emotion information, and the output data is the adjusted notification content.

[1020] Step 7:

[1021] The server sends the adjusted notification content to the terminal, which then displays the received notification content to the user. The user can check the payment details based on the transaction information and an appropriate explanation according to their emotions.

[1022] In this way, the system can respond quickly and appropriately to inquiries from business partners and provide optimal responses according to the user's feelings.

[1023] Example 2

[1024] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1025] Conventional transaction information management systems have difficulty responding quickly and accurately to inquiries from business partners regarding payment details. Furthermore, they are unable to respond in response to the user's emotions, making it difficult to improve user satisfaction. In particular, when a user is dissatisfied, they require a detailed explanation, but conventional systems do not automate this process.

[1026] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1027] In this invention, the server includes means for managing transaction information with business partners, means for accepting inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiries and generating payment details, means for notifying the source of the inquiries of the generated payment details, means including an emotion engine for recognizing the user's emotions, and means for adjusting the method of notifying the payment details based on feedback from the emotion engine. This enables quick and accurate responses to inquiries from business partners and optimal responses according to the user's emotions.

[1028] "Transaction information" refers to information relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction details, etc.

[1029] "Inquiry" means a question or request from a business partner regarding payment details.

[1030] "Payment details" refers to detailed payment details generated based on transaction information, and includes the transaction amount, transaction date and time, transaction details, etc.

[1031] An "emotion engine" refers to software or hardware that recognizes a user's emotions from their tone of voice, facial expressions, choice of words, etc.

[1032] "Feedback" refers to information provided to the system based on the user's emotions as recognized by the emotion engine.

[1033] The "notification method" refers to the means by which the generated payment details are communicated to the inquirer, and includes email, push notification, etc.

[1034] "Server" refers to a computer system that manages transaction information, accepts inquiries, generates and notifies payment details, and operates the emotion engine.

[1035] "Database" refers to a data management system for storing transaction information and retrieving the information as needed.

[1036] "User" refers to a business partner or an individual or corporation that uses the system.

[1037] This invention is a system that manages transaction information and responds quickly and accurately to inquiries from business partners regarding payment details. It also recognizes the user's emotions and responds optimally accordingly.

[1038] System configuration

[1039] Management of transaction information

[1040] The server stores transaction information in a database. Transaction information includes the transaction amount, transaction date and time, transaction details, etc. For example, when a new transaction occurs, the server adds that information to the database. Database management systems such as MySQL (registered trademark) and PostgreSQL are used.

[1041] Receiving inquiries

[1042] A user makes a query using a device. The device sends the query to the server through a web browser or mobile application. For example, a representative at Client A might type, "Please tell me the payment details for last month's transactions." The query is sent to the server as an HTTP request.

[1043] Extracting information from a database

[1044] When the server receives a query from a user, it extracts the relevant transaction information from the database. Specifically, it uses an SQL query to search for transaction information for trading partner A. For example, it executes the query "SELECT FROM transactions WHERE client_id = 'A' AND date >= '2023-09-01' AND date <= '2023-09-30'".

[1045] Generate payment details

[1046] The server generates a payment statement based on the extracted transaction information. The payment statement details the transaction amount, date, and time, and transaction details. For example, a Python script can be used to format the extracted data and convert it into the payment statement format.

[1047] Payment details notification

[1048] The server automatically notifies the inquirer of the generated payment details. Notification methods include email and push notification. For example, the server sends the payment details to business partner A via email using the SMTP protocol.

[1049] Emotion Engine Operation

[1050] When a user makes a query, the device sends the user's tone of voice, facial expressions, and word choice to the emotion engine, which then uses voice recognition software (e.g., Google Cloud Speech-to-Text) and facial expression recognition software (e.g., Microsoft Azure Face API) to recognize the user's emotions.

[1051] Responding according to emotions

[1052] The server receives feedback from the emotion engine and adjusts how it communicates the transaction details. For example, if it detects that the user is dissatisfied, it will prompt the server to provide a transaction detail with a detailed explanation. Conversely, if it detects that the user is satisfied, it will feed that information back and prompt the server to repeat the process for similar transactions.

[1053] Specific examples

[1054] When Customer A inquires, "Please tell me the payment details for last month's transactions," the server extracts last month's transaction information from the database and generates a payment detail. The generated payment detail is then sent to Customer A via email. If the emotion engine recognizes that Customer A's representative is dissatisfied at the time of the inquiry, the server will provide a payment detail with a detailed explanation.

[1055] Prompt Sentence Examples

[1056] "In response to an inquiry from Supplier A, please generate a payment breakdown based on last month's transaction information and send an email with a detailed explanation."

[1057] This system automates responses to inquiries from business partners, reducing man-hours. In addition, by using an emotion engine, it is possible to provide optimal responses based on the user's emotions.

[1058] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1059] Step 1:

[1060] The server stores transaction information in a database. As input, new transaction information (transaction amount, transaction date and time, transaction details) is provided. The server takes this information and inserts it into the database using an SQL query. As output, the new transaction information is added to the database. Specifically, the server executes the following SQL query:

[1061] sql

[1062] INSERT INTO transactions (client_id, amount, date, description) VALUES ('A', 1000, '2023-09-15', 'Product Purchase')

[1063] Step 2:

[1064] A user makes a query using a terminal. As input, the user enters the query content (e.g., "Please tell me the payment details for last month's transactions") into the terminal. The terminal sends this information as an HTTP request to the server. As output, the query content is sent to the server. Specifically, the terminal sends the following HTTP request to the server:

[1065] http

[1066] POST / api / inquiry

[1067] Content-Type: application / json

[1068] {

[1069] "client_id": "A",

[1070] "query": "What is the payment breakdown for last month's transactions?"

[1071] }

[1072] Step 3:

[1073] When the server receives a query from a user, it extracts the relevant transaction information from the database. The query content and customer ID are provided as input. The server uses an SQL query to search for the transaction information from the database. The relevant transaction information is extracted as output. Specifically, the server executes the following SQL query:

[1074] sql

[1075] SELECT FROM transactions WHERE client_id = 'A' AND date >= '2023-09-01' AND date <= '2023-09-30'

[1076] Step 4:

[1077] The server generates a payment breakdown based on the extracted transaction information. The extracted transaction information is provided as input. The server uses a Python script to format the transaction information and convert it into a payment breakdown format. The payment breakdown is generated as output. Specifically, the server performs the following processes:

[1078] python

[1079] def generate_payment_details(transactions):

[1080] details = "Account: A\n"

[1081] for transactions in transactions:

[1082] details += f"Transaction amount: {transaction['amount']} yen\n"

[1083] details += f"Transaction date and time: {transaction['date']}\n"

[1084] details += f"Transaction details: {transaction['description']}\n"

[1085] return details

[1086] Step 5:

[1087] The server automatically notifies the inquirer of the generated payment details. As input, the generated payment details and the inquirer's contact information are provided. The server sends the payment details by email using the SMTP protocol. As output, the inquirer is notified of the payment details. Specifically, the server sends an email like the one below.

[1088] email

[1089] To: clientA@example.com

[1090] Subject: Payment details

[1091] Customer: A

[1092] Transaction amount: 1000 yen

[1093] Transaction Date: 2023-09-15

[1094] Transaction details: Product purchase

[1095] Step 6:

[1096] When a user makes a query, the device sends the user's tone of voice, facial expression, choice of words, etc. to the emotion engine. The user's audio and video data are provided as input. The device sends this data to the emotion engine. As output, the emotion engine recognizes the user's emotion. Specifically, the device sends the following API request to the emotion engine:

[1097] http

[1098] POST / api / emotion

[1099] Content-Type: application / json

[1100] {

[1101] "audio": "base64_encoded_audio_data",

[1102] "video": "base64_encoded_video_data"

[1103] }

[1104] Step 7:

[1105] The server receives feedback from the emotion engine and adjusts the notification method for the payment details. Feedback information from the emotion engine is provided as input. The server uses this information to decide whether to generate a payment details with detailed explanations or a regular payment details. As output, the optimal payment details are generated and notified. Specifically, the server performs the following processes:

[1106] python

[1107] def adjust_notification_based_on_emotion(emotion_feedback, payment_details):

[1108] if emotion_feedback == "unhappy":

[1109] payment_details += "\nDetailed Description:\nThis transaction is for a purchase made on September 15, 2023. The transaction amount was 1000 yen, and the item was delivered the next day."

[1110] return payment_details

[1111] (Application example 2)

[1112] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1113] Conventional transaction information management systems have difficulty responding quickly and accurately to inquiries from business partners regarding payment details. Furthermore, they respond uniformly without considering the user's feelings, which can lead to a decline in user satisfaction. While appropriate responses are required when users feel dissatisfied or angry, conventional systems are unable to recognize such emotions and adjust their responses accordingly. This reduces the efficiency of inquiries and makes it difficult to improve user satisfaction.

[1114] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1115] In this invention, the server includes means for managing transaction information with business partners, means for accepting inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiry and generating a payment detail, means for notifying the inquirer of the generated payment detail, means for recognizing the user's emotion, and means for adjusting the notification method based on the recognized emotion. This makes it possible to respond quickly and accurately to inquiries from business partners, and further improve user satisfaction by providing an optimal response according to the user's emotion.

[1116] "Means for managing transaction information" refers to a system that stores information about transactions with business partners in a database and has the functions to update, search, and display that information as needed.

[1117] The "means for accepting inquiries regarding payment details" is a system that provides an interface for receiving questions or requests regarding payment details from business partners and initiating processing accordingly.

[1118] "Means for automatically extracting transaction information and generating payment details" refers to a system that has the function of automatically searching for relevant transaction information from a database based on received inquiries and creating payment details based on that information.

[1119] The "means for notifying the inquirer of the generated payment details" is a system having a function for automatically sending and notifying the supplier of the generated payment details.

[1120] The "means for recognizing user emotions" is a system that has the function of analyzing and recognizing emotions from the user's tone of voice, facial expressions, choice of words, etc.

[1121] The "means for adjusting the notification method based on the recognized emotion" is a system that has the function of optimizing the content and method of notification according to the user's emotion and taking appropriate action.

[1122] As an embodiment of the present invention, a system for managing transaction information and responding to inquiries from business partners is constructed. A specific embodiment of this system is shown below.

[1123] System configuration

[1124] The system consists of the following main components:

[1125] 1. Database Server: Manages the database for storing transaction information. SQLite can be used.

[1126] 2. Emotion Recognition Engine: An engine that analyzes the user's tone of voice and facial expressions to recognize emotions. EmotionEngine is used.

[1127] 3. Notification Service: A service for notifying the trading partner of the generated payment details. NotificationService is used.

[1128] 4. User interface: An interface for receiving inquiries from business partners. Implemented as a smartphone application.

[1129] Program processing

[1130] The server performs the process in the following procedure.

[1131] 1. Database connection: Connect to the database that stores transaction information using SQLite.

[1132] 2. Initialize the emotion engine: Recognize the user's emotions using the EmotionEngine.

[1133] 3. Initialize the notification service: Send notifications using NotificationService.

[1134] 4. Inquiry processing: Receives the client ID and inquiry details and extracts the relevant transaction information from the database.

[1135] 5. Generate payment details: Generate payment details based on the extracted transaction information.

[1136] 6. Emotion Recognition: Recognize user emotions using EmotionEngine.

[1137] 7. Adjust notification method: Adjust notification method according to user's emotions.

[1138] Specific examples

[1139] For example, if user A asks, "Tell me about your recent transactions," the system operates as follows:

[1140] 1. Extract user A's transaction information from the database.

[1141] 2. Generate payment details based on the extracted transaction information.

[1142] 3. Recognize User A's emotions from his / her tone of voice.

[1143] 4. If User A is dissatisfied, provide a detailed breakdown of the payment.

[1144] Prompt Sentence Examples

[1145] User A: Tell me about your recent transactions.

[1146] System: Extracting transaction information. Please wait a moment.

[1147] System: Transaction date and time: 2023-10-01, Amount: 10,000 yen, Content: Purchase of product A

[1148] System: Transaction date and time: 2023-10-05, Amount: 5,000 yen, Content: Purchase of product B

[1149] System: Detailed payment details have been provided.

[1150] In this way, the system can respond quickly and accurately to inquiries from business partners, and can also provide optimal responses based on the user's emotions, thereby improving user satisfaction.

[1151] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1152] Step 1:

[1153] The server connects to the database that stores transaction information using SQLite. The input is database connection information, and the output is the establishment of a database connection. In this step, a database connection object is created, allowing subsequent data manipulation.

[1154] Step 2:

[1155] The server initializes the EmotionEngine and prepares to recognize the user's emotions. The input required is the EmotionEngine's configuration information, and the output is a message indicating that the emotion recognition engine has been initialized. In this step, the emotion recognition engine is started and ready to analyze the user's emotions.

[1156] Step 3:

[1157] The server initializes the NotificationService and prepares to send notifications. The input requires configuration information for the NotificationService, and the output is the completion of initialization of the NotificationService. In this step, the NotificationService is started and is ready to notify the customer of the generated payment details.

[1158] Step 4:

[1159] The terminal accepts inquiries from business partners. The input requires the content of the inquiry from the business partner, and the output is the receipt of the content of the inquiry. In this step, the user makes an inquiry, and the content is input into the system.

[1160] Step 5:

[1161] The server extracts the relevant transaction information from the database based on the received query. The query content and the customer ID are required as input, and the relevant transaction information is obtained as output. In this step, the database query is executed and the transaction information is extracted.

[1162] Step 6:

[1163] The server generates a payment breakdown based on the extracted transaction information. The extracted transaction information is required as input, and the generated payment breakdown is obtained as output. In this step, the transaction information is analyzed and a payment breakdown is created.

[1164] Step 7:

[1165] The server uses the EmotionEngine to recognize the user's emotions. The inputs are the user's tone of voice and facial expressions, and the output is the recognized emotions. In this step, the user's emotions are analyzed and emotion data is generated.

[1166] Step 8:

[1167] The server adjusts the notification method based on the recognized emotion. The inputs are the recognized emotion and the generated payment details, and the output is the adjusted notification method. In this step, the content and method of the notification are optimized according to the user's emotion.

[1168] Step 9:

[1169] The server notifies the customer of the generated payment details using the NotificationService. The inputs are the adjusted notification method and the payment details, and the output is the notification completion. In this step, the payment details are sent to the customer and the notification is completed.

[1170] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1171] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1172] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are listed.

[1173] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1174] [Third embodiment]

[1175] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1176] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1177] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1178] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1179] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1180] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1181] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1182] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1183] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1184] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1185] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1186] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1187] "Example 1"

[1188] The system of the present invention stores transaction information in a database and provides an interface for accepting inquiries from business partners. When an inquiry is received, the system automatically extracts the relevant transaction information from the database and generates a payment breakdown. The generated payment breakdown is automatically notified to the source of the inquiry. For example, when an inquiry is received from business partner A, the system extracts transaction information with business partner A from the database and generates a payment breakdown based on the transaction amount, transaction date and time, and transaction details. The generated payment breakdown is automatically notified to business partner A. This makes it possible to automate responses to inquiries regarding payment breakdowns and reduce labor costs.

[1189] "Example 2"

[1190] The system of the present invention stores transaction information in a database and provides an interface for accepting inquiries from business partners. When an inquiry is received, the system automatically extracts the relevant transaction information from the database and generates a payment breakdown. The generated payment breakdown is automatically notified to the source of the inquiry. For example, when an inquiry is received from business partner A, the system extracts transaction information with business partner A from the database and generates a payment breakdown based on the transaction amount, transaction date and time, and transaction details. The generated payment breakdown is automatically notified to business partner A. This makes it possible to automate responses to inquiries regarding payment breakdowns and reduce labor costs.

[1191] The processing flow of each embodiment will be described below.

[1192] "Example 1"

[1193] Step 1: A customer inquiry is entered into the system, for example via a web interface or email.

[1194] Step 2: When the system receives an inquiry, it automatically extracts the relevant transaction information from the database based on the customer information contained in the inquiry (e.g., customer name, ID, etc.).

[1195] Step 3: Generate a payment breakdown from the extracted transaction information. The payment breakdown includes information such as the transaction amount, transaction date and time, and transaction content.

[1196] Step 4: The generated payment details are sent to the inquirer, for example via email or a web interface.

[1197] "Example 2"

[1198] Step 1: A customer inquiry is entered into the system, for example via a web interface or email.

[1199] Step 2: When the system receives an inquiry, it automatically extracts the relevant transaction information from the database based on the customer information contained in the inquiry (e.g., customer name, ID, etc.).

[1200] Step 3: Generate a payment breakdown from the extracted transaction information. The payment breakdown includes information such as the transaction amount, transaction date and time, and transaction content.

[1201] Step 4: The generated payment details are sent to the inquirer, for example via email or a web interface.

[1202] Example 1

[1203] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1204] Conventional transaction information management systems require manual responses to inquiries from business partners regarding payment details, which requires a significant amount of time and effort. Manual responses also carry the risk of human error, resulting in inaccuracies. Furthermore, the complicated process of inputting and managing transaction information makes efficient operation difficult.

[1205] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1206] In this invention, the server includes means for managing transaction information with business partners, means for accepting inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiry and generating a payment detail, means for notifying the inquirer of the generated payment detail, means for providing an interface for inputting transaction information, means for storing the transaction information in a database, means for recording the inquiry content in a log file, and means for notifying the payment detail by email. This makes it possible to automate the management of transaction information and response to inquiries, thereby reducing labor hours and improving accuracy.

[1207] "Transaction information" refers to detailed data relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction content, and the like.

[1208] "Business partner" refers to a customer or client who receives goods or services.

[1209] "Payment details" is information provided to a trading partner that indicates details of a transaction, including the transaction amount, transaction date and time, transaction content, and the like.

[1210] "Inquiry" refers to a request from a business partner for information or confirmation.

[1211] A "server" refers to a computer system that processes and manages data on a network.

[1212] A "database" refers to a system for systematically storing and managing data such as transaction information.

[1213] An "interface" refers to the means or method by which a user interacts with a system.

[1214] A "log file" refers to a file that records system actions and events.

[1215] "Email" refers to a means of sending and receiving messages electronically.

[1216] MODE FOR CARRYING OUT THE INVENTION

[1217] The present invention relates to a system for managing transaction information and automatically responding to inquiries from business partners regarding payment details. A specific embodiment of this system will be described below.

[1218] System configuration

[1219] This system consists of three main components: a server, a terminal, and a user. The server plays a central role in managing transaction information, accepting inquiries, and generating and notifying payment details. The terminal provides an interface for users to input transaction information and make inquiries. The user is the entity that inputs transaction information and makes inquiries.

[1220] Hardware and software used

[1221] The server uses a general web server (for example, Apache (registered trademark) or Nginx (registered trademark)), and the database uses a relational database such as MySQL (registered trademark) or PostgreSQL. Programming languages ​​such as Python and Java are used to implement the program. The terminal uses a web browser for user access.

[1222] Data processing and calculation

[1223] The server receives the transaction information entered by the user and stores it in a database. When an inquiry is received from a business partner, the server extracts the relevant transaction information from the database and generates a payment breakdown. The generated payment breakdown is then sent to the business partner by email.

[1224] Specific examples

[1225] For example, if a business partner A inquires, "Please tell me the details of transactions for September 2023," the server will process the inquiry using the following procedure.

[1226] 1. The server accepts an inquiry from business partner A.

[1227] 2. The server extracts trading information for trading partner A for September 2023 from the database.

[1228] 3. Based on the extracted transaction information, the server generates a payment breakdown including the transaction amount, transaction date and time, and transaction details.

[1229] 4. The server sends the generated payment details to Customer A via email.

[1230] Prompt Sentence Examples

[1231] "In response to an inquiry from Business Partner A asking for a transaction breakdown for September 2023, please create a program that will extract the relevant transaction information from the database, generate a payment breakdown, and notify the customer by email."

[1232] In this way, this system automates the management of transaction information and response to inquiries, thereby improving the efficiency and accuracy of operations.

[1233] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1234] Step 1:

[1235] The user enters the transaction information.

[1236] The user accesses a web form for entering transaction information and enters information such as the client name, transaction amount, transaction date and time, and transaction details. Specifically, the user enters "Client name: Client A, transaction amount: 100,000 yen, transaction date and time: 2023-09-15, transaction details: product purchase" and clicks the "Submit" button. The entered data is sent to the server.

[1237] Step 2:

[1238] The server stores the transaction information in a database.

[1239] The server receives the transaction information sent by the user and stores it in the database. Specifically, the server executes the SQL query "INSERT INTO transactions (client_name, amount, date, description) VALUES ('Customer A', 100000, '2023-09-15', 'Product Purchase');". The input is the transaction information sent by the user, and the output is the transaction information stored in the database.

[1240] Step 3:

[1241] A business partner makes an inquiry.

[1242] The business partner accesses the interface for making an inquiry and enters the details of the inquiry. Specifically, business partner A enters "Please tell me the transaction details for September 2023" and clicks the "Send" button. The entered inquiry details are sent to the server.

[1243] Step 4:

[1244] The server accepts the query.

[1245] The server accepts inquiries from business partners and records the inquiry details in a log file. Specifically, the server records a log stating, "An inquiry from business partner A has been accepted." The input is the inquiry details sent by the business partner, and the output is the inquiry details recorded in the log file.

[1246] Step 5:

[1247] The server retrieves the relevant transaction information from the database.

[1248] The server extracts the relevant transaction information from the database based on the query. Specifically, the server executes the SQL query "SELECT FROM transactions WHERE client_name = 'Customer A' AND date LIKE '2023-09%';". The input is the query, and the output is the extracted transaction information.

[1249] Step 6:

[1250] The server generates the payment details.

[1251] The server generates a payment breakdown based on the extracted transaction information. Specifically, the server generates the following breakdown: "Transaction breakdown for customer A in September 2023: 1. Transaction amount: 100,000 yen, Transaction date and time: 2023-09-15, Transaction content: Product purchase." The input is the extracted transaction information, and the output is the generated payment breakdown.

[1252] Step 7:

[1253] The server notifies the customer of the payment details generated.

[1254] The server notifies the client of the generated payment details by email. Specifically, the server records a log stating "Payment details have been sent to client A by email" and sends the email via the SMTP server. The input is the generated payment details, and the output is the email sent to the client.

[1255] (Application example 1)

[1256] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1257] With conventional transaction information management systems, it was difficult to respond quickly and accurately to inquiries about payment details from business partners. Furthermore, there was a problem in that analyzing the content of inquiries and extracting the appropriate transaction information required a great deal of time and effort. Furthermore, there was a lack of a way for users to easily check transaction information via smartphone.

[1258] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1259] In this invention, the server includes means for managing transaction information with business partners, means for accepting inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiry and generating a payment detail, means for notifying the originator of the inquiry of the generated payment detail, means for displaying the transaction information via an application installed on the smartphone, and means for analyzing the inquiry using a generative AI model and extracting transaction information based on a prompt sentence. This allows for quick and accurate responses to inquiries from business partners and enables users to easily check transaction information via their smartphones.

[1260] "Transaction information" refers to information relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction details, etc.

[1261] "Payment details" is detailed payment information generated based on the transaction amount, transaction date and time, and transaction content for each business partner.

[1262] "Inquiry" refers to a question or request for confirmation from a business partner regarding payment details.

[1263] A "smartphone" is a multi-functional mobile device that can connect to the Internet and run applications in addition to the functions of a mobile phone.

[1264] An "application" is a software program that is installed on a smartphone and provides specific functions or services.

[1265] A "generative AI model" is a model that uses artificial intelligence technology to analyze data and automatically perform specific tasks.

[1266] A "prompt" is an instruction entered into a generative AI model, which serves as a trigger for extracting specific information.

[1267] The following system configuration will be described as an embodiment of the present invention.

[1268] System Configuration

[1269] The system includes a server, a smartphone, and a generative AI model. The server manages transaction information and generates payment details based on inquiries. The smartphone provides an interface for users to check the transaction information. The generative AI model analyzes the inquiry and extracts transaction information based on prompts.

[1270] Program processing explanation

[1271] Hardware:

[1272] Server: Database management system (e.g. SQLite)

[1273] Smartphone: Multi-function mobile device

[1274] software:

[1275] SQLite: Database Management System

[1276] Python: a programming language

[1277] Generative AI model: A data analysis model using artificial intelligence technology

[1278] Data processing and calculation:

[1279] 1. Connect to the database and create tables:

[1280] The server uses SQLite to create a database and tables to store the transaction information.

[1281] 2. Insert transaction information:

[1282] The server inserts the new transaction information into the database.

[1283] 3. Enquiry Processing:

[1284] The server retrieves transaction information for the specified merchant from the database.

[1285] 4. Generate payment details:

[1286] The server generates a payment breakdown based on the extracted transaction information.

[1287] 5. User Notice:

[1288] The generated payment details are displayed to the user via their smartphone.

[1289] 6. Use of generative AI models:

[1290] The generative AI model analyzes the query and extracts transaction information based on the prompt.

[1291] Specific examples

[1292] For example, if a user uses a smartphone to inquire about transaction information regarding "Customer A," they might enter a prompt like the following:

[1293] Example prompt sentence:

[1294] "Please tell me the transaction information regarding business partner A."

[1295] Once the prompt is entered, the generative AI model analyzes the query, and the server extracts the relevant transaction information from the database, after which a payment breakdown is generated and notified to the user via their smartphone.

[1296] In this way, the present invention allows for quick and accurate responses to inquiries from business partners and allows users to easily check transaction information via their smartphones.

[1297] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1298] Step 1:

[1299] The server connects to the SQLite database and creates a table to store the transaction information.

[1300] Input: Database connection information

[1301] Output: A table to store transaction information

[1302] What happens: The server connects to the SQLite database and creates a table named "transactions" with columns for transaction ID, customer, transaction amount, transaction date and time, and transaction details.

[1303] Step 2:

[1304] The server inserts the new transaction information into the database.

[1305] Input: Customer, transaction amount, transaction details

[1306] Output: New transaction information is added to the database

[1307] Specific operation: The server receives the client, transaction amount, and transaction details, obtains the current date and time, and inserts this information into the "transactions" table.

[1308] Step 3:

[1309] A user uses a smartphone to make an inquiry about a business partner.

[1310] Input: Prompt statement (e.g., "Please tell me the transaction information about Customer A.")

[1311] Output: The query is sent to the server

[1312] Specific operation: The user opens the application on their smartphone and enters a query about a client. The entered prompt is sent to the server.

[1313] Step 4:

[1314] The server uses a generative AI model to analyze the query and extract transaction information based on the prompt text.

[1315] Input: prompt statement

[1316] Output: Extracted transaction information

[1317] Specific operation: The server inputs a prompt sentence into the generative AI model, which then analyzes the query. Based on the analysis results, the server extracts the transaction information of the relevant trading partner from the database.

[1318] Step 5:

[1319] The server generates a payment breakdown based on the extracted transaction information.

[1320] Input: Extracted transaction information

[1321] Output: Payment details

[1322] Specific operation: Based on the extracted transaction information, the server generates a payment breakdown including the transaction ID, transaction amount, transaction date and time, and transaction details.

[1323] Step 6:

[1324] The server notifies the smartphone of the generated payment details.

[1325] Input: Payment details

[1326] Output: Payment details displayed on smartphone

[1327] Specific operation: The server sends the generated payment details to the smartphone, where the user can check them through the application.

[1328] Step 7:

[1329] Users can check their payment details via their smartphone.

[1330] Input: Payment details displayed on smartphone

[1331] Output: Payment details confirmed by the user

[1332] Specific operation: The user opens the application on their smartphone and checks the displayed payment details.

[1333] Example 2

[1334] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1335] With conventional transaction information management systems, inquiries about payment details from business partners had to be handled manually, which was a time-consuming process. Furthermore, manual responses carried the risk of human error, making it difficult to respond to business partners promptly. This could result in reduced operational efficiency and a loss of trust from business partners.

[1336] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1337] In this invention, the server includes means for managing transaction information with business partners, means for receiving inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiry and generating a payment detail, means for notifying the inquirer of the generated payment detail, means for a user to input transaction information, means for the server to store the transaction information in a database, means for the server to extract relevant transaction information from the database, means for the server to generate a payment detail, and means for notifying the inquirer of the generated payment detail. This makes it possible to automate responses to inquiries regarding payment details and reduce man-hours.

[1338] "Transaction information" refers to information relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction details, etc.

[1339] "Business Partner" means a party with whom a transaction is conducted using the system.

[1340] "Payment details" is information showing details of the amount to be paid to the business partner, including the transaction amount, transaction date and time, transaction content, etc.

[1341] An "inquiry" is an action in which a business partner requests information regarding payment details through the system.

[1342] A "database" is a system for storing and managing transaction information.

[1343] A "server" is a computer system that manages the entire system and executes various processes.

[1344] "User" means a person who utilizes the system to enter transaction information.

[1345] "Automatically extracting" means that the system retrieves the necessary information from the database without human intervention.

[1346] "Generating" means that the system creates a payment breakdown based on the transaction information.

[1347] "Notifying" means transmitting the payment details generated by the system to the trading partner.

[1348] The present invention is a system for managing transaction information and automatically responding to inquiries from business partners regarding payment details. A specific embodiment of this system will be described below.

[1349] System configuration

[1350] Hardware

[1351] 1. Server

[1352] Database server (e.g., MySQL (registered trademark), PostgreSQL)

[1353] Web server (e.g., Apache (registered trademark), Nginx (registered trademark))

[1354] Mail server (e.g. SendGrid, Amazon SES)

[1355] 2. Terminal

[1356] PCs and smartphones used by users and business partners

[1357] software

[1358] 1. Database Management System (DBMS)

[1359] MySQL (registered trademark), PostgreSQL, etc.

[1360] 2. Web Application Frameworks

[1361] Django, Ruby on Rails, etc.

[1362] 3. Data processing script

[1363] Python, JavaScript, etc.

[1364] 4. Email Sending Library

[1365] SMTP, SendMail, etc.

[1366] System Operation

[1367] 1. The user enters transaction information

[1368] The user uses a terminal to access the web interface and inputs transaction information such as the transaction amount, transaction date and time, and transaction details.

[1369] Specific behavior: The user enters transaction information into the form and clicks the "Submit" button.

[1370] 2. The server stores the transaction information in a database

[1371] The server receives the transaction information sent by the user and stores it in a database.

[1372] Specific operation: The server executes an SQL query to insert the transaction information into the database.

[1373] 3. A business partner makes an inquiry

[1374] The customer uses a terminal to access a web interface and make inquiries about payment details.

[1375] Specific operation: The client enters the required information into the inquiry form and clicks the "Submit" button.

[1376] 4. The server accepts the query

[1377] The server receives an inquiry from a business partner and analyzes the inquiry content.

[1378] Specific operation: The server analyzes the inquiry content and identifies the corresponding customer ID.

[1379] 5. The server extracts the relevant transaction information from the database.

[1380] The server extracts transaction information from a database based on the identified merchant ID.

[1381] Specific operation: The server executes an SQL query to select the relevant transaction information.

[1382] 6. The server generates the payment details

[1383] The server generates a payment breakdown based on the extracted transaction information.

[1384] What happens: The server runs a data processing script to calculate and format the payment details.

[1385] 7. The server notifies the inquirer of the payment details generated by the server.

[1386] The server notifies the inquirer of the generated payment details by email.

[1387] Specific behavior: The server uses the email sending library to send an email containing the payment details.

[1388] Specific examples

[1389] Inquiry from Business Partner A

[1390] 1. Supplier A inquires about payment details through the web interface.

[1391] 2. The server extracts the transaction information of trading partner A (transaction amount, transaction date and time, transaction details) from the database.

[1392] 3. The server generates a payment breakdown based on the extracted information.

[1393] 4. The server sends the generated payment details to Customer A via email.

[1394] Example prompts to input to the generative AI model

[1395] "We have received an inquiry about payment details from Supplier A. Please extract Supplier A's transaction information from the database, generate a payment detail, and notify us by email."

[1396] This system automates responses to inquiries regarding payment details, reducing man-hours.

[1397] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1398] Step 1:

[1399] The user enters the transaction information.

[1400] Input: The user uses a terminal to access the web interface and inputs transaction information such as the transaction amount, transaction date and time, and transaction details.

[1401] Data processing: The transaction information entered by the user is sent to the server as form data.

[1402] Output: The transaction information sent to the server.

[1403] Specific behavior: The user enters transaction information into the form and clicks the "Submit" button.

[1404] Step 2:

[1405] The server stores the transaction information in a database.

[1406] Input: Transaction information submitted by the user.

[1407] Data processing: The server inserts the received transaction information into the database using an SQL query.

[1408] Output: Transaction information stored in a database.

[1409] Specific operation: The server executes an SQL query to insert the transaction information into the database.

[1410] Step 3:

[1411] A business partner makes an inquiry.

[1412] Input: The customer uses a terminal to access the web interface and make an inquiry about the payment details.

[1413] Data processing: The inquiry details entered by the business partner are sent to the server as form data.

[1414] Output: The query sent to the server.

[1415] Specific operation: The client enters the required information into the inquiry form and clicks the "Submit" button.

[1416] Step 4:

[1417] The server accepts the query.

[1418] Input: Inquiry sent by business partner.

[1419] Data processing: The server analyzes the inquiry content and identifies the corresponding customer ID.

[1420] Output: The identified account ID.

[1421] Specific operation: The server analyzes the inquiry content and identifies the corresponding customer ID.

[1422] Step 5:

[1423] The server retrieves the relevant transaction information from the database.

[1424] Input: A specific account ID.

[1425] Data processing: The server executes an SQL query to select the relevant transaction information from the database.

[1426] Output: Extracted transaction information.

[1427] Specific operation: The server executes an SQL query to select the relevant transaction information.

[1428] Step 6:

[1429] The server generates the payment details.

[1430] Input: Extracted transaction information.

[1431] Data Processing: The server runs data processing scripts to calculate and format payment details.

[1432] Output: The generated payment breakdown.

[1433] What happens: The server runs a data processing script to calculate and format the payment details.

[1434] Step 7:

[1435] The server notifies the inquirer of the generated payment details.

[1436] Input: Generated payment breakdown.

[1437] Data processing: The server uses an email sending library to send an email containing the payment details.

[1438] Output: Payment breakdown email sent to the inquirer.

[1439] Specific behavior: The server uses the email sending library to send an email containing the payment details.

[1440] (Application example 2)

[1441] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1442] With conventional transaction information management systems, it was difficult to respond quickly and accurately to inquiries from business partners regarding payment details, and manual responses were required, resulting in increased workload. Furthermore, there was a lack of efficient methods for managing transaction information and responding to inquiries using smart devices. This resulted in issues such as poor communication with business partners and reduced operational efficiency.

[1443] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1444] In this invention, the server includes means for managing transaction information with business partners, means for accepting inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiries and generating payment details, means for notifying the originator of the inquiries of the generated payment details, and means for managing transaction information, accepting inquiries, and generating and notifying payment details via an application installed on the smart device. This enables quick and accurate responses to inquiries from business partners, significantly improving business efficiency.

[1445] "Transaction information" refers to detailed data relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction content, and the like.

[1446] "Payment details" is detailed information about payments for each supplier that is generated based on transaction information, and includes the transaction amount, transaction date and time, transaction content, and the like.

[1447] "Inquiry" refers to a question or request for confirmation from a business partner regarding payment details.

[1448] "Smart devices" refers to electronic devices with internet connectivity, such as smartphones, tablets, smart glasses, and head-mounted displays.

[1449] An "application" is a software program installed on a smart device that provides specific functions or services.

[1450] A "server" refers to a computer system that stores, processes, and manages data over a network.

[1451] "Automatic extraction" refers to the process in which the system selects the necessary information from the database without human intervention.

[1452] "Notification" refers to the act of informing the trading partner of the generated payment details.

[1453] A system for implementing the present invention includes a server, a smart device, and an application installed thereon. Specific embodiments are described below.

[1454] System Configuration

[1455] The server has a database for managing transaction information and provides an interface for accepting inquiries from business partners. An application for managing transaction information, accepting inquiries, and generating and notifying payment details is installed on the smart device.

[1456] Hardware and software used

[1457] Hardware: Servers, smart devices such as smartphones, tablets, smart glasses, and head-mounted displays.

[1458] Software: Python, Flask (web framework), SQLite (database).

[1459] Data processing and calculation

[1460] 1. Database initialization: The server initializes the SQLite database and creates a table to store transaction information.

[1461] 2. Inquiry reception: The application on the smart device receives inquiries from business partners in JSON format.

[1462] 3. Transaction information extraction: The server automatically extracts the transaction information of the relevant trading partner from the SQLite database.

[1463] 4. Generate payment details: Generate payment details based on the extracted transaction information.

[1464] 5. Automatic notification: The generated payment details are sent to the inquirer in JSON format.

[1465] Specific examples

[1466] When business partner A uses a smartphone to inquire about his / her transaction information, the following steps are taken.

[1467] 1. Client A launches the application on their smartphone and inquires about transaction information.

[1468] 2. The application sends a JSON request to the server containing the name of Customer A.

[1469] 3. The server extracts the transaction information for Customer A from the SQLite database and generates a payment breakdown.

[1470] 4. The generated payment details are sent to Customer A in JSON format.

[1471] Prompt Sentence Examples

[1472] "Please generate a request to inquire about trading information for trading partner A."

[1473] In this way, a specific embodiment for carrying out the invention has been shown. This system makes it possible to respond to inquiries from business partners quickly and accurately, thereby significantly improving business efficiency.

[1474] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1475] Step 1:

[1476] The server initializes an SQLite database and creates a table to store transaction information. Specifically, the server establishes a database connection and executes SQL commands to create a table to store transaction information. The input is a request to initialize the database, and the output is the initialized database.

[1477] Step 2:

[1478] A user launches an application on a smart device and makes an inquiry about transaction information. Specifically, the user enters the name of a trading partner into the application's inquiry form and presses the submit button. The input is the trading partner's name, and the output is an inquiry request.

[1479] Step 3:

[1480] The terminal sends a JSON request including the name of the customer to the server. Specifically, the application converts the customer name entered by the user into JSON format and sends it as an HTTP request to the server. The input is the customer name, and the output is a JSON request to the server.

[1481] Step 4:

[1482] The server extracts the transaction information of the corresponding trading partner from the SQLite database. Specifically, the server parses the received JSON request and generates an SQL query based on the trading partner name to search the database. The input is the JSON request, and the output is the corresponding transaction information.

[1483] Step 5:

[1484] The server generates a payment breakdown based on the extracted transaction information. Specifically, the server analyzes the extracted transaction information and generates a payment breakdown including the transaction amount, transaction date and time, and transaction details. The input is the transaction information, and the output is the payment breakdown.

[1485] Step 6:

[1486] The server notifies the inquirer of the generated payment details in JSON format. Specifically, the server converts the generated payment details into JSON format and sends it to the terminal as an HTTP response. The input is the payment details, and the output is a JSON response.

[1487] Step 7:

[1488] The terminal displays the received payment details to the user. Specifically, the application parses the received JSON response and displays the payment details in a user-friendly format. The input is the JSON response and the output is the payment details displayed to the user.

[1489] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1490] "Example 1"

[1491] In one embodiment of the present invention, an emotion engine is incorporated. This emotion engine recognizes a user's emotions from the user's tone of voice, facial expression, and choice of words. For example, if a user's tone of voice or facial expression indicates anger or frustration when making an inquiry, the emotion engine captures this information. Based on this information, the emotion engine then adjusts the notification method for the payment details. Specifically, if the emotion engine recognizes that the user is frustrated, it instructs the system to provide a detailed explanation of the payment details. Similarly, if the emotion engine recognizes that the user is happy or satisfied, it feeds this information back to the system and instructs the system to take the same steps next time a similar transaction occurs. This allows the system to respond optimally based on the user's emotions.

[1492] "Example 2"

[1493] In one embodiment of the present invention, an emotion engine is incorporated. This emotion engine recognizes a user's emotions from the user's tone of voice, facial expression, and choice of words. For example, if a user's tone of voice or facial expression indicates anger or frustration when making an inquiry, the emotion engine captures this information. Based on this information, the emotion engine then adjusts the notification method for the payment details. Specifically, if the emotion engine recognizes that the user is frustrated, it instructs the system to provide a detailed explanation of the payment details. Similarly, if the emotion engine recognizes that the user is happy or satisfied, it feeds this information back to the system and instructs the system to take the same steps next time a similar transaction occurs. This allows the system to respond optimally based on the user's emotions.

[1494] The processing flow of each embodiment will be described below.

[1495] "Example 1"

[1496] Step 1: The user queries the system, and the emotion engine captures the user's tone of voice, facial expression, and choice of words.

[1497] Step 2: The emotion engine recognizes the user's emotions from the captured information. For example, if the user senses anger or frustration from the tone of voice or facial expression, the emotion engine will capture that information.

[1498] Step 3: The emotion engine adjusts the notification of the payment details based on the recognized emotion. Specifically, if the emotion engine recognizes that the user is dissatisfied, it instructs the system to provide a detailed explanation of the payment details.

[1499] Step 4: If the emotion engine detects that the user is feeling happy or satisfied, it feeds that information back into the system, instructing it to follow the same steps when a similar transaction occurs.

[1500] Step 5: The system notifies the user of the payment details based on the instructions from the emotion engine, allowing the system to take the most appropriate action based on the user's emotions.

[1501] "Example 2"

[1502] Step 1: The user queries the system, and the emotion engine captures the user's tone of voice, facial expression, and choice of words.

[1503] Step 2: The emotion engine recognizes the user's emotions from the captured information. For example, if the user senses anger or frustration from the tone of voice or facial expression, the emotion engine will capture that information.

[1504] Step 3: The emotion engine adjusts the notification of the payment details based on the recognized emotion. Specifically, if the emotion engine recognizes that the user is dissatisfied, it instructs the system to provide a detailed explanation of the payment details.

[1505] Step 4: If the emotion engine detects that the user is feeling happy or satisfied, it feeds that information back into the system, instructing it to follow the same steps when a similar transaction occurs.

[1506] Step 5: The system notifies the user of the payment details based on the instructions from the emotion engine, allowing the system to take the most appropriate action based on the user's emotions.

[1507] Example 1

[1508] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1509] Conventional transaction information management systems have difficulty responding quickly and accurately to inquiries from business partners regarding payment details. Furthermore, they are unable to respond in a way that takes into account the user's feelings, making it difficult to improve user satisfaction. In particular, when a user is dissatisfied, they require a detailed explanation, but conventional systems do not automate such responses.

[1510] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1511] In this invention, the server includes means for managing transaction information with business partners, means for receiving inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiry and generating a payment detail, means for notifying the inquirer of the generated payment detail, means for recognizing the user's emotion, and means for adjusting the method of notifying the payment detail based on the recognized emotion. This not only automates the management of transaction information and the generation and notification of payment details, but also enables optimal responses according to the user's emotion.

[1512] "Transaction information" refers to information relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction details, etc.

[1513] "Business Partner" means a party with whom a transaction is conducted using the system.

[1514] "Payment details" refers to detailed payment details generated based on transaction information, and includes the transaction amount, transaction date and time, transaction details, and the like.

[1515] An "inquiry" is a request made by a business partner to the system for information or confirmation.

[1516] A "database" is an information system for storing and managing transaction information.

[1517] An "emotion engine" is software or hardware that recognizes a user's emotions from their tone of voice, facial expressions, choice of words, etc.

[1518] "Notification" refers to the act of transmitting the generated payment details to the trading partner, and is done via email or a notification function within the web application.

[1519] "User" means any person or entity that uses the System to manage or inquire about transaction information.

[1520] "Server" refers to the computer system that processes the entire system, managing transaction information, accepting inquiries, and generating and notifying payment details.

[1521] This invention is a system that manages transaction information, automatically generates and notifies payment details in response to inquiries from business partners, and can also recognize the user's emotions and respond accordingly.

[1522] System configuration

[1523] Management of transaction information

[1524] The server stores transaction information in a database. Specifically, information such as the customer ID, transaction date and time, transaction amount, and transaction details is saved in a MySQL (registered trademark) database. For example, when a new transaction occurs, the server receives that information and inserts it into the database using SQL statements.

[1525] Receiving inquiries

[1526] Users use the web application interface to make inquiries about transaction information. The terminal (user's PC or smartphone) accesses this interface through a browser. Inquiries are made by filling out a form or by voice input.

[1527] Processing inquiries

[1528] The server receives the user's inquiry and extracts the relevant transaction information from the database. Specifically, it executes an SQL query to retrieve the data based on the customer ID and transaction date and time entered by the user in the form.

[1529] Generate payment details

[1530] The server generates a payment breakdown based on the extracted transaction information. A Python script is used to calculate the transaction amount, transaction date and time, and transaction details to create a detailed payment breakdown. For example, if transaction information for Customer A is extracted, the Python script processes the information and generates a payment breakdown.

[1531] Payment details notification

[1532] The server notifies the inquiring business partner of the generated payment details. Notification can be via email or a notification function within a web application. For example, the generated payment details can be sent to business partner A by email.

[1533] Recognizing user emotions with an emotion engine

[1534] When a user makes a query, the emotion engine recognizes the user's emotion from the user's tone of voice, facial expression, choice of words, etc. The emotion engine is implemented using a general emotion recognition API. For example, when a user makes a voice input, the emotion engine analyzes the voice data and recognizes the emotion.

[1535] Adjusting responses according to emotions

[1536] The server adjusts how it notifies users of payment details based on information from the emotion engine. Specifically, if it recognizes that the user is dissatisfied, it instructs the system to provide a detailed payment detail. If it recognizes that the user is happy or satisfied, it feeds that information back into the system and instructs it to take the same steps next time a similar transaction occurs.

[1537] Specific examples

[1538] For example, if a business partner A inquires, "Please tell me the payment details of recent transactions," the server will process the inquiry using the following procedure.

[1539] 1. The server extracts trading information for Trading Partner A from the MySQL® database.

[1540] 2. The server uses a Python script to generate a payment breakdown based on the transaction amount, transaction date and time, and transaction details.

[1541] 3. The server notifies Customer A of the generated payment details via email.

[1542] 4. When a user makes an inquiry, the emotion engine analyzes the user's tone of voice and facial expressions and recognizes that they are feeling angry or frustrated.

[1543] 5. The server provides a payment breakdown with detailed explanations based on the information from the emotion engine.

[1544] Prompt Sentence Examples

[1545] "If a customer A asks for a payment breakdown of their recent transaction, please explain how the system will handle this."

[1546] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1547] Step 1:

[1548] The server stores the transaction information in a database. As input, it receives transaction information such as the customer ID, transaction date and time, transaction amount, and transaction details. Specifically, it inserts this information into a MySQL® database using SQL statements. As output, it saves the new transaction information in the database.

[1549] Step 2:

[1550] A user uses a web application interface to make an inquiry about transaction information. As input, the user enters the inquiry details, such as the trading partner ID and transaction date and time, into a form. Specifically, the terminal (the user's PC or smartphone) accesses this interface through a browser and sends the inquiry details. As output, the inquiry details are sent to the server.

[1551] Step 3:

[1552] The server receives the user's inquiry and extracts the relevant transaction information from the database. As input, it receives the customer ID and transaction date and time entered by the user in the form. Specifically, it executes an SQL query to retrieve the relevant transaction information from the database. As output, the relevant transaction information is extracted.

[1553] Step 4:

[1554] The server generates a payment breakdown based on the extracted transaction information. It receives the extracted transaction information as input. Specifically, it uses a Python script to calculate the transaction amount, transaction date and time, and transaction details to create a detailed payment breakdown. The payment breakdown is generated as output.

[1555] Step 5:

[1556] The server notifies the inquiring business partner of the generated payment details. It receives the generated payment details as input. Specific operations include sending the payment details via email or using a notification function within the web application. The output is a notification of the payment details to the business partner.

[1557] Step 6:

[1558] When a user makes a query, the emotion engine recognizes the user's emotions from the user's tone of voice, facial expressions, choice of words, etc. As input, it receives the user's voice data and facial expression data. Specifically, it uses an emotion recognition API to analyze this data and recognize the user's emotions. As output, it generates the user's emotional information.

[1559] Step 7:

[1560] The server adjusts the notification method for payment details based on information from the emotion engine. As input, it receives the user's emotional information. Specifically, if it recognizes that the user is dissatisfied, it instructs the system to provide a payment detail with a detailed explanation. If it recognizes that the user is happy or satisfied, it feeds that information back to the system and instructs it to take the same steps when a similar transaction occurs. As output, it responds optimally according to the emotion.

[1561] (Application example 1)

[1562] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1563] Conventional transaction information management systems had the problem of being unable to respond quickly and appropriately to inquiries from business partners regarding payment details. Furthermore, because they responded uniformly without considering the user's feelings, there was a risk of user satisfaction declining. This posed a risk of damaging trusting relationships with business partners.

[1564] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1565] In this invention, the server includes means for managing transaction information with business partners, means for accepting inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiries and generating payment details, means for notifying the inquirer of the generated payment details, means including an emotion engine for recognizing the user's emotions, and means for adjusting the notification method according to the user's emotions. This makes it possible to respond quickly and appropriately to inquiries from business partners and to provide an optimal response according to the user's emotions.

[1566] "Transaction information" refers to detailed data relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction content, and the like.

[1567] "Payment details" is a list of detailed payment details generated based on transaction information, and includes the transaction amount, transaction date and time, transaction details, etc.

[1568] "Inquiry" refers to a question or request for confirmation from a business partner regarding payment details.

[1569] An "emotion engine" is a technology that recognizes a user's emotions from their tone of voice, facial expressions, choice of words, etc.

[1570] "Notification method" refers to the means or method for transmitting the generated payment details to the trading partner.

[1571] "Business partner" refers to the company or individual that is the subject of business information.

[1572] "User" refers to the entity that manages transaction information and makes inquiries.

[1573] "Server" refers to a computer system that manages transaction information and responds to inquiries.

[1574] A system for implementing this invention manages transaction information and responds to inquiries from business partners regarding payment details. The system includes a server for managing transaction information, a terminal for accepting inquiries, and an emotion engine for recognizing user emotions.

[1575] The server manages transaction information using a MySQL (registered trademark) database. Transaction information includes the transaction amount, transaction date and time, and transaction details for each customer. When a user makes an inquiry through their terminal, the server automatically extracts the relevant transaction information and generates a payment breakdown.

[1576] The generated payment details are sent to the inquirer via the terminal. The notification method is adjusted according to the user's emotions by an emotion engine. The emotion engine uses Microsoft Azure Cognitive Services to analyze the user's tone of voice and facial expressions to recognize emotions.

[1577] As a concrete example, consider the case where a user makes an inquiry about a transaction using a smartphone application. When the user inputs an inquiry such as "Please tell me the payment details for Supplier A," the server extracts the transaction information for Supplier A from the MySQL® database and generates a payment detail.

[1578] The emotion engine then analyzes the user's tone of voice and facial expressions, adjusting the notification method to provide a detailed explanation if it detects that the user is dissatisfied, or a simple notification if it detects that the user is satisfied.

[1579] An example of a prompt for the generative AI model is as follows:

[1580] "The user has made an inquiry regarding a transaction. Please generate a payment breakdown based on the following information and notify the user.

[1581] Account: Account A

[1582] Transaction amount: 100,000 yen

[1583] Transaction Date: October 1, 2023

[1584] Transaction details: Product purchase

[1585] Also, recognize the user's emotions from their tone of voice and facial expressions and respond appropriately."

[1586] In this way, the system can respond quickly and appropriately to inquiries from business partners and provide optimal responses according to the user's feelings.

[1587] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1588] Step 1:

[1589] The user uses a terminal to input an inquiry about a transaction. The input inquiry is sent to the server. The input data includes the name of the customer, the transaction amount, the transaction date and time, and the transaction details.

[1590] Step 2:

[1591] The server analyzes the received inquiry and extracts the relevant transaction information from the MySQL® database. Based on the input data, the database is searched using criteria such as the client name and transaction date and time, and the relevant transaction information is obtained.

[1592] Step 3:

[1593] The server generates a payment breakdown based on the extracted transaction information, processing data such as the transaction amount, transaction date and time, and transaction details, and compiling it into a payment breakdown.

[1594] Step 4:

[1595] The server temporarily stores the generated payment details and then invokes the emotion engine, which uses Microsoft Azure Cognitive Services to analyze the user's tone of voice and facial expressions. The input data is the user's voice and image data, and the output data is the user's emotional information.

[1596] Step 5:

[1597] The emotion engine recognizes the user's emotions and returns the results to the server. For example, if the user is dissatisfied, it outputs "angry," and if they are satisfied, it outputs "happy."

[1598] Step 6:

[1599] The server receives emotion information from the emotion engine and adjusts the notification method. If the user is dissatisfied, it adds a detailed explanation of the payment details, and if the user is satisfied, it sends a brief notification. The input data is emotion information, and the output data is the adjusted notification content.

[1600] Step 7:

[1601] The server sends the adjusted notification content to the terminal, which then displays the received notification content to the user. The user can check the payment details based on the transaction information and an appropriate explanation according to their emotions.

[1602] In this way, the system can respond quickly and appropriately to inquiries from business partners and provide optimal responses according to the user's feelings.

[1603] Example 2

[1604] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1605] Conventional transaction information management systems have difficulty responding quickly and accurately to inquiries from business partners regarding payment details. Furthermore, they are unable to respond in response to the user's emotions, making it difficult to improve user satisfaction. In particular, when a user is dissatisfied, they require a detailed explanation, but conventional systems do not automate this process.

[1606] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1607] In this invention, the server includes means for managing transaction information with business partners, means for accepting inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiries and generating payment details, means for notifying the source of the inquiries of the generated payment details, means including an emotion engine for recognizing the user's emotions, and means for adjusting the method of notifying the payment details based on feedback from the emotion engine. This enables quick and accurate responses to inquiries from business partners and optimal responses according to the user's emotions.

[1608] "Transaction information" refers to information relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction details, etc.

[1609] "Inquiry" means a question or request from a business partner regarding payment details.

[1610] "Payment details" refers to detailed payment details generated based on transaction information, and includes the transaction amount, transaction date and time, transaction details, etc.

[1611] An "emotion engine" refers to software or hardware that recognizes a user's emotions from their tone of voice, facial expressions, choice of words, etc.

[1612] "Feedback" refers to information provided to the system based on the user's emotions as recognized by the emotion engine.

[1613] The "notification method" refers to the means by which the generated payment details are communicated to the inquirer, and includes email, push notification, etc.

[1614] "Server" refers to a computer system that manages transaction information, accepts inquiries, generates and notifies payment details, and operates the emotion engine.

[1615] "Database" refers to a data management system for storing transaction information and retrieving the information as needed.

[1616] "User" refers to a business partner or an individual or corporation that uses the system.

[1617] This invention is a system that manages transaction information and responds quickly and accurately to inquiries from business partners regarding payment details. It also recognizes the user's emotions and responds optimally accordingly.

[1618] System configuration

[1619] Management of transaction information

[1620] The server stores transaction information in a database. Transaction information includes the transaction amount, transaction date and time, transaction details, etc. For example, when a new transaction occurs, the server adds that information to the database. Database management systems such as MySQL (registered trademark) and PostgreSQL are used.

[1621] Receiving inquiries

[1622] A user makes a query using a device. The device sends the query to the server through a web browser or mobile application. For example, a representative at Client A might type, "Please tell me the payment details for last month's transactions." The query is sent to the server as an HTTP request.

[1623] Extracting information from a database

[1624] When the server receives a query from a user, it extracts the relevant transaction information from the database. Specifically, it uses an SQL query to search for transaction information for trading partner A. For example, it executes the query "SELECT FROM transactions WHERE client_id = 'A' AND date >= '2023-09-01' AND date <= '2023-09-30'".

[1625] Generate payment details

[1626] The server generates a payment statement based on the extracted transaction information. The payment statement details the transaction amount, date, and time, and transaction details. For example, a Python script can be used to format the extracted data and convert it into the payment statement format.

[1627] Payment details notification

[1628] The server automatically notifies the inquirer of the generated payment details. Notification methods include email and push notification. For example, the server sends the payment details to business partner A via email using the SMTP protocol.

[1629] Emotion Engine Operation

[1630] When a user makes a query, the device sends the user's tone of voice, facial expressions, and word choice to the emotion engine, which then uses voice recognition software (e.g., Google Cloud Speech-to-Text) and facial expression recognition software (e.g., Microsoft Azure Face API) to recognize the user's emotions.

[1631] Responding according to emotions

[1632] The server receives feedback from the emotion engine and adjusts how it communicates the transaction details. For example, if it detects that the user is dissatisfied, it will prompt the server to provide a transaction detail with a detailed explanation. Conversely, if it detects that the user is satisfied, it will feed that information back and prompt the server to repeat the process for similar transactions.

[1633] Specific examples

[1634] When Customer A inquires, "Please tell me the payment details for last month's transactions," the server extracts last month's transaction information from the database and generates a payment detail. The generated payment detail is then sent to Customer A via email. If the emotion engine recognizes that Customer A's representative is dissatisfied at the time of the inquiry, the server will provide a payment detail with a detailed explanation.

[1635] Prompt Sentence Examples

[1636] "In response to an inquiry from Supplier A, please generate a payment breakdown based on last month's transaction information and send an email with a detailed explanation."

[1637] This system automates responses to inquiries from business partners, reducing man-hours. In addition, by using an emotion engine, it is possible to provide optimal responses based on the user's emotions.

[1638] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1639] Step 1:

[1640] The server stores transaction information in a database. As input, new transaction information (transaction amount, transaction date and time, transaction details) is provided. The server takes this information and inserts it into the database using an SQL query. As output, the new transaction information is added to the database. Specifically, the server executes the following SQL query:

[1641] sql

[1642] INSERT INTO transactions (client_id, amount, date, description) VALUES ('A', 1000, '2023-09-15', 'Product Purchase')

[1643] Step 2:

[1644] A user makes a query using a terminal. As input, the user enters the query content (e.g., "Please tell me the payment details for last month's transactions") into the terminal. The terminal sends this information as an HTTP request to the server. As output, the query content is sent to the server. Specifically, the terminal sends the following HTTP request to the server:

[1645] http

[1646] POST / api / inquiry

[1647] Content-Type: application / json

[1648] {

[1649] "client_id": "A",

[1650] "query": "What is the payment breakdown for last month's transactions?"

[1651] }

[1652] Step 3:

[1653] When the server receives a query from a user, it extracts the relevant transaction information from the database. The query content and customer ID are provided as input. The server uses an SQL query to search for the transaction information from the database. The relevant transaction information is extracted as output. Specifically, the server executes the following SQL query:

[1654] sql

[1655] SELECT FROM transactions WHERE client_id = 'A' AND date >= '2023-09-01' AND date <= '2023-09-30'

[1656] Step 4:

[1657] The server generates a payment breakdown based on the extracted transaction information. The extracted transaction information is provided as input. The server uses a Python script to format the transaction information and convert it into a payment breakdown format. The payment breakdown is generated as output. Specifically, the server performs the following processes:

[1658] python

[1659] def generate_payment_details(transactions):

[1660] details = "Account: A\n"

[1661] for transactions in transactions:

[1662] details += f"Transaction amount: {transaction['amount']} yen\n"

[1663] details += f"Transaction date and time: {transaction['date']}\n"

[1664] details += f"Transaction details: {transaction['description']}\n"

[1665] return details

[1666] Step 5:

[1667] The server automatically notifies the inquirer of the generated payment details. As input, the generated payment details and the inquirer's contact information are provided. The server sends the payment details by email using the SMTP protocol. As output, the inquirer is notified of the payment details. Specifically, the server sends an email like the one below.

[1668] email

[1669] To: clientA@example.com

[1670] Subject: Payment details

[1671] Customer: A

[1672] Transaction amount: 1000 yen

[1673] Transaction Date: 2023-09-15

[1674] Transaction details: Product purchase

[1675] Step 6:

[1676] When a user makes a query, the device sends the user's tone of voice, facial expression, choice of words, etc. to the emotion engine. The user's audio and video data are provided as input. The device sends this data to the emotion engine. As output, the emotion engine recognizes the user's emotion. Specifically, the device sends the following API request to the emotion engine:

[1677] http

[1678] POST / api / emotion

[1679] Content-Type: application / json

[1680] {

[1681] "audio": "base64_encoded_audio_data",

[1682] "video": "base64_encoded_video_data"

[1683] }

[1684] Step 7:

[1685] The server receives feedback from the emotion engine and adjusts the notification method for the payment details. Feedback information from the emotion engine is provided as input. The server uses this information to decide whether to generate a payment details with detailed explanations or a regular payment details. As output, the optimal payment details are generated and notified. Specifically, the server performs the following processes:

[1686] python

[1687] def adjust_notification_based_on_emotion(emotion_feedback, payment_details):

[1688] if emotion_feedback == "unhappy":

[1689] payment_details += "\nDetailed Description:\nThis transaction is for a purchase made on September 15, 2023. The transaction amount was 1000 yen, and the item was delivered the next day."

[1690] return payment_details

[1691]

[1692] (Application example 2)

[1693] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1694] Conventional transaction information management systems have difficulty responding quickly and accurately to inquiries from business partners regarding payment details. Furthermore, they respond uniformly without considering the user's feelings, which can lead to a decline in user satisfaction. While appropriate responses are required when users feel dissatisfied or angry, conventional systems are unable to recognize such emotions and adjust their responses accordingly. This reduces the efficiency of inquiries and makes it difficult to improve user satisfaction.

[1695] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1696] In this invention, the server includes means for managing transaction information with business partners, means for accepting inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiry and generating a payment detail, means for notifying the inquirer of the generated payment detail, means for recognizing the user's emotion, and means for adjusting the notification method based on the recognized emotion. This makes it possible to respond quickly and accurately to inquiries from business partners, and further improve user satisfaction by providing an optimal response according to the user's emotion.

[1697] "Means for managing transaction information" refers to a system that stores information about transactions with business partners in a database and has the functions to update, search, and display that information as needed.

[1698] The "means for accepting inquiries regarding payment details" is a system that provides an interface for receiving questions or requests regarding payment details from business partners and initiating processing accordingly.

[1699] "Means for automatically extracting transaction information and generating payment details" refers to a system that has the function of automatically searching for relevant transaction information from a database based on received inquiries and creating payment details based on that information.

[1700] The "means for notifying the inquirer of the generated payment details" is a system having a function for automatically sending and notifying the supplier of the generated payment details.

[1701] The "means for recognizing user emotions" is a system that has the function of analyzing and recognizing emotions from the user's tone of voice, facial expressions, choice of words, etc.

[1702] The "means for adjusting the notification method based on the recognized emotion" is a system that has the function of optimizing the content and method of notification according to the user's emotion and taking appropriate action.

[1703] As an embodiment of the present invention, a system for managing transaction information and responding to inquiries from business partners is constructed. A specific embodiment of this system is shown below.

[1704] System configuration

[1705] The system consists of the following main components:

[1706] 1. Database Server: Manages the database for storing transaction information. SQLite can be used.

[1707] 2. Emotion Recognition Engine: An engine that analyzes the user's tone of voice and facial expressions to recognize emotions. EmotionEngine is used.

[1708] 3. Notification Service: A service for notifying the trading partner of the generated payment details. NotificationService is used.

[1709] 4. User interface: An interface for receiving inquiries from business partners. Implemented as a smartphone application.

[1710] Program processing

[1711] The server performs the process in the following procedure.

[1712] 1. Database connection: Connect to the database that stores transaction information using SQLite.

[1713] 2. Initialize the emotion engine: Recognize the user's emotions using the EmotionEngine.

[1714] 3. Initialize the notification service: Send notifications using NotificationService.

[1715] 4. Inquiry processing: Receives the client ID and inquiry details and extracts the relevant transaction information from the database.

[1716] 5. Generate payment details: Generate payment details based on the extracted transaction information.

[1717] 6. Emotion Recognition: Recognize user emotions using EmotionEngine.

[1718] 7. Adjust notification method: Adjust notification method according to user's emotions.

[1719] Specific examples

[1720] For example, if user A asks, "Tell me about your recent transactions," the system operates as follows:

[1721] 1. Extract user A's transaction information from the database.

[1722] 2. Generate payment details based on the extracted transaction information.

[1723] 3. Recognize User A's emotions from his / her tone of voice.

[1724] 4. If User A is dissatisfied, provide a detailed breakdown of the payment.

[1725] Prompt Sentence Examples

[1726] User A: Tell me about your recent transactions.

[1727] System: Extracting transaction information. Please wait a moment.

[1728] System: Transaction date and time: 2023-10-01, Amount: 10,000 yen, Content: Purchase of product A

[1729] System: Transaction date and time: 2023-10-05, Amount: 5,000 yen, Content: Purchase of product B

[1730] System: Detailed payment details have been provided.

[1731] In this way, the system can respond quickly and accurately to inquiries from business partners, and can also provide optimal responses based on the user's emotions, thereby improving user satisfaction.

[1732] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1733] Step 1:

[1734] The server connects to the database that stores transaction information using SQLite. The input is database connection information, and the output is the establishment of a database connection. In this step, a database connection object is created, allowing subsequent data manipulation.

[1735] Step 2:

[1736] The server initializes the EmotionEngine and prepares to recognize the user's emotions. The input required is the EmotionEngine's configuration information, and the output is a message indicating that the emotion recognition engine has been initialized. In this step, the emotion recognition engine is started and ready to analyze the user's emotions.

[1737] Step 3:

[1738] The server initializes the NotificationService and prepares to send notifications. The input requires configuration information for the NotificationService, and the output is the completion of initialization of the NotificationService. In this step, the NotificationService is started and is ready to notify the customer of the generated payment details.

[1739] Step 4:

[1740] The terminal accepts inquiries from business partners. The input requires the content of the inquiry from the business partner, and the output is the receipt of the content of the inquiry. In this step, the user makes an inquiry, and the content is input into the system.

[1741] Step 5:

[1742] The server extracts the relevant transaction information from the database based on the received query. The query content and the customer ID are required as input, and the relevant transaction information is obtained as output. In this step, the database query is executed and the transaction information is extracted.

[1743] Step 6:

[1744] The server generates a payment breakdown based on the extracted transaction information. The extracted transaction information is required as input, and the generated payment breakdown is obtained as output. In this step, the transaction information is analyzed and a payment breakdown is created.

[1745] Step 7:

[1746] The server uses the EmotionEngine to recognize the user's emotions. The inputs are the user's tone of voice and facial expressions, and the output is the recognized emotions. In this step, the user's emotions are analyzed and emotion data is generated.

[1747] Step 8:

[1748] The server adjusts the notification method based on the recognized emotion. The inputs are the recognized emotion and the generated payment details, and the output is the adjusted notification method. In this step, the content and method of the notification are optimized according to the user's emotion.

[1749] Step 9:

[1750] The server notifies the customer of the generated payment details using the NotificationService. The inputs are the adjusted notification method and the payment details, and the output is the notification completion. In this step, the payment details are sent to the customer and the notification is completed.

[1751] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1752] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1753] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are listed.

[1754] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1755] [Fourth embodiment]

[1756] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1757] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1758] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1759] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1760] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1761] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1762] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1763] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1764] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1765] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1766] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1767] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1768] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1769] "Example 1"

[1770] The system of the present invention stores transaction information in a database and provides an interface for accepting inquiries from business partners. When an inquiry is received, the system automatically extracts the relevant transaction information from the database and generates a payment breakdown. The generated payment breakdown is automatically notified to the source of the inquiry. For example, when an inquiry is received from business partner A, the system extracts transaction information with business partner A from the database and generates a payment breakdown based on the transaction amount, transaction date and time, and transaction details. The generated payment breakdown is automatically notified to business partner A. This makes it possible to automate responses to inquiries regarding payment breakdowns and reduce labor costs.

[1771] "Example 2"

[1772] The system of the present invention stores transaction information in a database and provides an interface for accepting inquiries from business partners. When an inquiry is received, the system automatically extracts the relevant transaction information from the database and generates a payment breakdown. The generated payment breakdown is automatically notified to the source of the inquiry. For example, when an inquiry is received from business partner A, the system extracts transaction information with business partner A from the database and generates a payment breakdown based on the transaction amount, transaction date and time, and transaction details. The generated payment breakdown is automatically notified to business partner A. This makes it possible to automate responses to inquiries regarding payment breakdowns and reduce labor costs.

[1773] The processing flow of each embodiment will be described below.

[1774] "Example 1"

[1775] Step 1: A customer inquiry is entered into the system, for example via a web interface or email.

[1776] Step 2: When the system receives an inquiry, it automatically extracts the relevant transaction information from the database based on the customer information contained in the inquiry (e.g., customer name, ID, etc.).

[1777] Step 3: Generate a payment breakdown from the extracted transaction information. The payment breakdown includes information such as the transaction amount, transaction date and time, and transaction content.

[1778] Step 4: The generated payment details are sent to the inquirer, for example via email or a web interface.

[1779] "Example 2"

[1780] Step 1: A customer inquiry is entered into the system, for example via a web interface or email.

[1781] Step 2: When the system receives an inquiry, it automatically extracts the relevant transaction information from the database based on the customer information contained in the inquiry (e.g., customer name, ID, etc.).

[1782] Step 3: Generate a payment breakdown from the extracted transaction information. The payment breakdown includes information such as the transaction amount, transaction date and time, and transaction content.

[1783] Step 4: The generated payment details are sent to the inquirer, for example via email or a web interface.

[1784] Example 1

[1785] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1786] Conventional transaction information management systems require manual responses to inquiries about payment details from business partners, which requires a significant amount of time and effort. Manual responses also carry the risk of human error, resulting in inaccuracies. Furthermore, the complicated process of inputting and managing transaction information makes efficient operation difficult.

[1787] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1788] In this invention, the server includes means for managing transaction information with business partners, means for accepting inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiry and generating a payment detail, means for notifying the inquirer of the generated payment detail, means for providing an interface for inputting transaction information, means for storing the transaction information in a database, means for recording the inquiry content in a log file, and means for notifying the payment detail by email. This makes it possible to automate the management of transaction information and response to inquiries, thereby reducing labor hours and improving accuracy.

[1789] "Transaction information" refers to detailed data relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction content, and the like.

[1790] "Business partner" refers to a customer or client who receives goods or services.

[1791] "Payment details" is information provided to a trading partner that indicates details of a transaction, including the transaction amount, transaction date and time, transaction content, and the like.

[1792] "Inquiry" refers to a request from a business partner for information or confirmation.

[1793] A "server" refers to a computer system that processes and manages data on a network.

[1794] A "database" refers to a system for systematically storing and managing data such as transaction information.

[1795] An "interface" refers to the means or method by which a user interacts with a system.

[1796] A "log file" refers to a file that records system actions and events.

[1797] "Email" refers to a means of sending and receiving messages electronically.

[1798] MODE FOR CARRYING OUT THE INVENTION

[1799] The present invention relates to a system for managing transaction information and automatically responding to inquiries from business partners regarding payment details. A specific embodiment of this system will be described below.

[1800] System configuration

[1801] This system consists of three main components: a server, a terminal, and a user. The server plays a central role in managing transaction information, accepting inquiries, and generating and notifying payment details. The terminal provides an interface for users to input transaction information and make inquiries. The user is the entity that inputs transaction information and makes inquiries.

[1802] Hardware and software used

[1803] The server uses a general web server (for example, Apache (registered trademark) or Nginx (registered trademark)), and the database uses a relational database such as MySQL (registered trademark) or PostgreSQL. Programming languages ​​such as Python and Java are used to implement the program. The terminal uses a web browser for user access.

[1804] Data processing and calculation

[1805] The server receives the transaction information entered by the user and stores it in a database. When an inquiry is received from a business partner, the server extracts the relevant transaction information from the database and generates a payment breakdown. The generated payment breakdown is then sent to the business partner by email.

[1806] Specific examples

[1807] For example, if a business partner A inquires, "Please tell me the details of transactions for September 2023," the server will process the inquiry using the following procedure.

[1808] 1. The server accepts an inquiry from business partner A.

[1809] 2. The server extracts trading information for trading partner A for September 2023 from the database.

[1810] 3. Based on the extracted transaction information, the server generates a payment breakdown including the transaction amount, transaction date and time, and transaction details.

[1811] 4. The server sends the generated payment details to Customer A via email.

[1812] Prompt Sentence Examples

[1813] "In response to an inquiry from Business Partner A asking for a transaction breakdown for September 2023, please create a program that will extract the relevant transaction information from the database, generate a payment breakdown, and notify the customer by email."

[1814] In this way, this system automates the management of transaction information and response to inquiries, thereby improving the efficiency and accuracy of operations.

[1815] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1816] Step 1:

[1817] The user enters the transaction information.

[1818] The user accesses a web form for entering transaction information and enters information such as the client name, transaction amount, transaction date and time, and transaction details. Specifically, the user enters "Client name: Client A, transaction amount: 100,000 yen, transaction date and time: 2023-09-15, transaction details: product purchase" and clicks the "Submit" button. The entered data is sent to the server.

[1819] Step 2:

[1820] The server stores the transaction information in a database.

[1821] The server receives the transaction information sent by the user and stores it in the database. Specifically, the server executes the SQL query "INSERT INTO transactions (client_name, amount, date, description) VALUES ('Customer A', 100000, '2023-09-15', 'Product Purchase');". The input is the transaction information sent by the user, and the output is the transaction information stored in the database.

[1822] Step 3:

[1823] A business partner makes an inquiry.

[1824] The business partner accesses the interface for making an inquiry and enters the details of the inquiry. Specifically, business partner A enters "Please tell me the transaction details for September 2023" and clicks the "Send" button. The entered inquiry details are sent to the server.

[1825] Step 4:

[1826] The server accepts the query.

[1827] The server accepts inquiries from business partners and records the inquiry details in a log file. Specifically, the server records a log stating, "An inquiry from business partner A has been accepted." The input is the inquiry details sent by the business partner, and the output is the inquiry details recorded in the log file.

[1828] Step 5:

[1829] The server retrieves the relevant transaction information from the database.

[1830] The server extracts the relevant transaction information from the database based on the query. Specifically, the server executes the SQL query "SELECT FROM transactions WHERE client_name = 'Customer A' AND date LIKE '2023-09%';". The input is the query, and the output is the extracted transaction information.

[1831] Step 6:

[1832] The server generates the payment details.

[1833] The server generates a payment breakdown based on the extracted transaction information. Specifically, the server generates the following breakdown: "Transaction breakdown for customer A in September 2023: 1. Transaction amount: 100,000 yen, Transaction date and time: 2023-09-15, Transaction content: Product purchase." The input is the extracted transaction information, and the output is the generated payment breakdown.

[1834] Step 7:

[1835] The server notifies the customer of the payment details generated.

[1836] The server notifies the client of the generated payment details by email. Specifically, the server records a log stating "Payment details have been sent to client A by email" and sends the email via the SMTP server. The input is the generated payment details, and the output is the email sent to the client.

[1837] (Application example 1)

[1838] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1839] With conventional transaction information management systems, it was difficult to respond quickly and accurately to inquiries about payment details from business partners. Furthermore, there was a problem in that analyzing the content of inquiries and extracting the appropriate transaction information required a great deal of time and effort. Furthermore, there was a lack of a way for users to easily check transaction information via smartphone.

[1840] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1841] In this invention, the server includes means for managing transaction information with business partners, means for accepting inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiry and generating a payment detail, means for notifying the originator of the inquiry of the generated payment detail, means for displaying the transaction information via an application installed on the smartphone, and means for analyzing the inquiry using a generative AI model and extracting transaction information based on a prompt sentence. This allows for quick and accurate responses to inquiries from business partners and enables users to easily check transaction information via their smartphones.

[1842] "Transaction information" refers to information relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction details, etc.

[1843] "Payment details" is detailed payment information generated based on the transaction amount, transaction date and time, and transaction content for each business partner.

[1844] "Inquiry" refers to a question or request for confirmation from a business partner regarding payment details.

[1845] A "smartphone" is a multi-functional mobile device that can connect to the Internet and run applications in addition to the functions of a mobile phone.

[1846] An "application" is a software program that is installed on a smartphone and provides specific functions or services.

[1847] A "generative AI model" is a model that uses artificial intelligence technology to analyze data and automatically perform specific tasks.

[1848] A "prompt" is an instruction entered into a generative AI model, which serves as a trigger for extracting specific information.

[1849] The following system configuration will be described as an embodiment of the present invention.

[1850] System Configuration

[1851] The system includes a server, a smartphone, and a generative AI model. The server manages transaction information and generates payment details based on inquiries. The smartphone provides an interface for users to check the transaction information. The generative AI model analyzes the inquiry and extracts transaction information based on prompts.

[1852] Program processing explanation

[1853] Hardware:

[1854] Server: Database management system (e.g. SQLite)

[1855] Smartphone: Multi-function mobile device

[1856] software:

[1857] SQLite: Database Management System

[1858] Python: a programming language

[1859] Generative AI model: A data analysis model using artificial intelligence technology

[1860] Data processing and calculation:

[1861] 1. Connect to the database and create tables:

[1862] The server uses SQLite to create a database and tables to store the transaction information.

[1863] 2. Insert transaction information:

[1864] The server inserts the new transaction information into the database.

[1865] 3. Enquiry Processing:

[1866] The server retrieves transaction information for the specified merchant from the database.

[1867] 4. Generate payment details:

[1868] The server generates a payment breakdown based on the extracted transaction information.

[1869] 5. User Notice:

[1870] The generated payment details are displayed to the user via their smartphone.

[1871] 6. Use of generative AI models:

[1872] The generative AI model analyzes the query and extracts transaction information based on the prompt.

[1873] Specific examples

[1874] For example, if a user uses a smartphone to inquire about transaction information regarding "Customer A," they might enter a prompt like the following:

[1875] Example prompt sentence:

[1876] "Please tell me the transaction information regarding business partner A."

[1877] Once the prompt is entered, the generative AI model analyzes the query, and the server extracts the relevant transaction information from the database, after which a payment breakdown is generated and notified to the user via their smartphone.

[1878] In this way, the present invention allows for quick and accurate responses to inquiries from business partners and allows users to easily check transaction information via their smartphones.

[1879] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1880] Step 1:

[1881] The server connects to the SQLite database and creates a table to store the transaction information.

[1882] Input: Database connection information

[1883] Output: A table to store transaction information

[1884] What happens: The server connects to the SQLite database and creates a table named "transactions" with columns for transaction ID, customer, transaction amount, transaction date and time, and transaction details.

[1885] Step 2:

[1886] The server inserts the new transaction information into the database.

[1887] Input: Customer, transaction amount, transaction details

[1888] Output: New transaction information is added to the database

[1889] Specific operation: The server receives the client, transaction amount, and transaction details, obtains the current date and time, and inserts this information into the "transactions" table.

[1890] Step 3:

[1891] A user uses a smartphone to make an inquiry about a business partner.

[1892] Input: Prompt statement (e.g., "Please tell me the transaction information about Customer A.")

[1893] Output: The query is sent to the server

[1894] Specific operation: The user opens the application on their smartphone and enters a query about a client. The entered prompt is sent to the server.

[1895] Step 4:

[1896] The server uses a generative AI model to analyze the query and extract transaction information based on the prompt text.

[1897] Input: prompt statement

[1898] Output: Extracted transaction information

[1899] Specific operation: The server inputs a prompt sentence into the generative AI model, which then analyzes the query. Based on the analysis results, the server extracts the transaction information of the relevant trading partner from the database.

[1900] Step 5:

[1901] The server generates a payment breakdown based on the extracted transaction information.

[1902] Input: Extracted transaction information

[1903] Output: Payment details

[1904] Specific operation: Based on the extracted transaction information, the server generates a payment breakdown including the transaction ID, transaction amount, transaction date and time, and transaction details.

[1905] Step 6:

[1906] The server notifies the smartphone of the generated payment details.

[1907] Input: Payment details

[1908] Output: Payment details displayed on smartphone

[1909] Specific operation: The server sends the generated payment details to the smartphone, where the user can check them through the application.

[1910] Step 7:

[1911] Users can check their payment details via their smartphone.

[1912] Input: Payment details displayed on smartphone

[1913] Output: Payment details confirmed by the user

[1914] Specific operation: The user opens the application on their smartphone and checks the displayed payment details.

[1915] Example 2

[1916] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1917] With conventional transaction information management systems, inquiries about payment details from business partners had to be handled manually, which was a time-consuming process. Furthermore, manual responses carried the risk of human error, making it difficult to respond to business partners promptly. This could result in reduced operational efficiency and a loss of trust from business partners.

[1918] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1919] In this invention, the server includes means for managing transaction information with business partners, means for receiving inquiries from business partners regarding payment details, means for automatically extracting relevant transaction information based on the inquiry and generating a payment detail, means for notifying the inquirer of the generated payment detail, means for a user to input transaction information, means for the server to store the transaction information in a database, means for the server to extract relevant transaction information from the database, means for the server to generate a payment detail, and means for notifying the inquirer of the generated payment detail. This makes it possible to automate responses to inquiries regarding payment details and reduce man-hours.

[1920] "Transaction information" refers to information relating to transactions conducted with a business partner, including the transaction amount, transaction date and time, transaction details, etc.

[1921] "Business Partner" means a party with whom a transaction is conducted using the system.

[1922] "Payment details" is information showing details of the amount to be paid to the business partner, including the transactio...

Claims

1. A means for managing transaction information with business partners; A means for accepting inquiries from business partners regarding payment details; means for automatically extracting relevant transaction information based on the inquiry and generating a payment breakdown; A means for notifying the inquirer of the generated payment details; a means for displaying transaction information via the application; A means for analyzing the inquiry using a generative AI model and extracting transaction information based on a prompt sentence; A system including:

2. The transaction information includes at least one of the transaction amount, transaction date and time, and transaction content for each transaction partner. The system of claim 1 .

3. A means for managing transaction information with business partners; A means for accepting inquiries from business partners regarding payment details; means for automatically extracting relevant transaction information based on the inquiry and generating a payment breakdown; A means for notifying the inquirer of the generated payment details; A means for adjusting a notification method according to a user's emotion recognized by an emotion engine that recognizes the user's emotion; A system including:

Images