system

Abstract

Provide a system. A means for receiving order information; A means for parsing required fields from the received order information; a means for detecting missing required items of order information; A means for detecting missing information for each item of the order information; means for detecting improper quantities in the order information; means for generating an order acceptance message if there are no deficiencies; A system including:

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] With the spread of online shopping and e-commerce, a large number of orders are processed every day. However, if there are any errors in the order details entered by the customer, the cumbersome task of manually checking the details and requesting corrections can reduce business efficiency. This manual work not only consumes time and effort, increasing operational costs, but can also affect customer satisfaction. Therefore, there is a need for a system that can automatically detect errors in order details and process them efficiently. [Means for solving the problem]

[0005] The present invention relates to an automatic response system for inquiries about incomplete order contents, and includes the following means.

[0006] 1. A means of receiving order information.

[0007] 2. A means of parsing required fields (e.g., order_id, customer_id, items) from the received order information.

[0008] 3. A means of detecting missing required items of order information.

[0009] 4. A means to detect missing information for each item (e.g., item_id, quantity).

[0010] 5. A means to detect inappropriate quantities of each item (e.g., quantity less than 0).

[0011] 6. A means for generating an order acceptance message if the order information is complete.

[0012] This allows the system to automatically detect errors in order contents and return error messages, reducing the need for manual confirmation and correction requests and significantly improving business efficiency.

[0013] "Order Information" refers to all information relating to products and services ordered by customers in e-commerce or online shopping.

[0014] "Required Fields" are basic data items that must be included in the order information to ensure accurate processing of the order.

[0015] The "analyzing means" has the function of analyzing received order information, extracting and verifying necessary data, and converting it into a form that can be used in the next processing step.

[0016] The "detection means" has the function of evaluating whether the order information and each of its components meets predetermined standards and identifying any deficiencies or problems.

[0017] An "order acceptance message" is a message sent to notify the customer that the order has been accepted after the order information has been confirmed to be complete.

[0018] "Item" means a separate product or service unit ordered by a Customer that is part of the Order Information.

[0019] "item_id" is an identifier that uniquely identifies each item and is provided as part of the order information.

[0020] "Quantity" indicates the number or amount of each item ordered and is provided as part of the order information. [Brief explanation of the drawings]

[0021] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9]1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0022] 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.

[0023] First, the terms used in the following description will be explained.

[0024] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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."

[0029] [First embodiment]

[0030] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0031] 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.

[0032] 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).

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0042] The present invention is described in detail below with reference to an embodiment thereof. The present system is an automatic response system for inquiries about incomplete order contents, which receives order information according to a specific procedure, automatically detects any incompleteness, and responds accordingly.

[0043] Server Operation

[0044] 1. The server sets up a dedicated endpoint to receive POST requests from users, which contain order information in JSON format.

[0045] 2. The server parses the JSON order information from the request body, which returns the entire order as a dictionary object.

[0046] 3. The server checks whether all required fields (order_id, customer_id, items) are present in the parsed order information, thereby detecting the basic defect.

[0047] 4. The server then checks for missing information for each item in the order information, specifically checking whether each item has an item_id and quantity.

[0048] 5. The server checks whether the quantity of each item is a valid value (usually 0 or greater), which detects whether an invalid value for quantity has been entered.

[0049] 6. If any of these checks fail, the server generates an appropriate error message and returns it to the user. If there are no errors, the server generates a message stating that the order is successful and returns it to the user.

[0050] Device behavior

[0051] 1. A user enters a new order at a terminal and sends it to the system.

[0052] 2. The terminal constructs the order information in the appropriate format (JSON format) and sends a POST request to the server's dedicated endpoint.

[0053] 3. The device receives the response from the server and decides the next action based on it. For example, if an error message is returned, it displays the items that need to be corrected to the user.

[0054] User Actions

[0055] 1. The user uses the interface on the terminal to enter order information, including the order_id, customer_id, item_id and quantity for each item.

[0056] 2. The user checks the entered order information and presses the submit button. This action sends the order information to the server.

[0057] 3. The user receives a response from the server. If the order is correct, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message.

[0058] Specific examples

[0059] Normal order case

[0060] The user enters the following order information on the terminal and submits it:

[0061] json

[0062] {

[0063] "order_id": "ORD12345",

[0064] "customer_id": "CUST54321",

[0065] "items": [

[0066] {"item_id": "ITEM001", "quantity": 2},

[0067] {"item_id": "ITEM002", "quantity": 5}

[0068] ]

[0069] }

[0070] The server receives this and performs checks at each step. If all checks pass, it returns a message to the user indicating that the order is correct.

[0071] Cases of defective orders

[0072] The user enters the following order information on the terminal and submits it:

[0073] json

[0074] {

[0075] "order_id": "ORD12345",

[0076] "items": [

[0077] {"item_id": "ITEM001"},

[0078] {"item_id": "ITEM002", "quantity": -1}

[0079] ]

[0080] }

[0081] The server receives this and detects that a required field is missing (no customer_id) and the quantity is incorrect (quantity is -1), which causes the server to return the following error message to the user:

[0082] json

[0083] {

[0084] "status": "error",

[0085] "message": "Required fields are missing"

[0086] }

[0087] or

[0088] json

[0089] {

[0090] "status": "error",

[0091] "message": "Invalid quantity: {'item_id': 'ITEM002', 'quantity': -1}"

[0092] }

[0093] This system automatically detects any errors in the order contents and responds quickly, thereby improving work efficiency and customer satisfaction.

[0094] The processing flow will be explained below.

[0095] Step 1:

[0096] The server receives a POST request to a dedicated endpoint and receives the order information sent by the user from the terminal as JSON format data.

[0097] Step 2:

[0098] The server parses the received request body and converts the JSON data into a dictionary-style object. Through this parsing, the entire order information is obtained as data.

[0099] Step 3:

[0100] The server checks whether all required fields, order_id, customer_id, and items, are present in the order information. If these fields are missing, the server generates and returns an error message.

[0101] Step 4:

[0102] The server checks whether the item_id and quantity are present for each item in items. If they are missing, the server generates and returns a detailed error message.

[0103] Step 5:

[0104] The server checks whether the quantity value for each item in items is greater than 0, i.e., whether it is an invalid quantity. If an invalid quantity is detected, the server generates and returns an error message indicating this.

[0105] Step 6:

[0106] If the server passes all checks, it generates a success message indicating that the order information is correct and returns it to the user.

[0107] Step 7:

[0108] The user receives the response message returned from the server, and if an error message is included, corrects the order information according to the instructions. If there are no errors, the user confirms that the order has been accepted.

[0109] Step 8:

[0110] If necessary, the user can send the corrected order information back to the server for recheck.

[0111] Example 1

[0112] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0113] The process of manually reviewing order information is time-consuming and prone to human error. This reduces the efficiency of order processing operations and risks lowering customer satisfaction. Furthermore, incomplete order information can cause delays throughout the entire process. Therefore, there is a need for a system that can automatically review order information and take appropriate action.

[0114] 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.

[0115] In this invention, the server includes means for receiving order information, means for analyzing the received order information in JSON format, means for detecting missing required items in the order information, means for detecting missing information for each item in the order information, means for detecting inappropriate quantities in the order information, means for generating an order acceptance message if there are no errors, and means for generating and returning an appropriate error message if there are errors, thereby enabling automatic inspection of order information and error handling.

[0116] "Order information" refers to information provided when a customer places an order for a product or service, and typically includes items such as order_id, customer_id, and items.

[0117] "JSON format" is an abbreviation for JavaScript (registered trademark) Object Notation, and is a text format for expressing data in a format that is easy for humans to read and machines to parse.

[0118] A "server" is a computer system that provides various services and data in response to requests from clients over a network.

[0119] An "endpoint" is a URL or URI that a client uses to send a specific request to a server.

[0120] A "POST request" is a type of request method in the HTTP protocol, and is mainly used to send data to a server.

[0121] "Required fields" are data fields that are absolutely necessary for order information to be considered valid in the system, and in this invention include order_id, customer_id, and items.

[0122] An "item" is a product or service within an order, and is an individual data entry that includes an item_id and a quantity.

[0123] An "error message" is a message that the system displays to notify the user when it detects a defect or error.

[0124] An "order acceptance message" is a confirmation message returned from the server to the user when the order information is determined to be normal.

[0125] The present invention is described in detail below with reference to an embodiment thereof. The present system is an automatic response system for inquiries about incomplete order contents, which receives order information according to a specific procedure, automatically detects any incompleteness, and responds accordingly.

[0126] Hardware and software used

[0127] server

[0128] The server is a computer system running on a network that processes order information in response to requests from clients (user terminals). The server uses, for example, the Flask framework implemented in Python.

[0129] Terminal

[0130] A terminal is a device where a user enters order information and sends it to a server. It includes smartphones, tablets, and PCs with a web browser or mobile app installed. In the case of a web browser, order information is constructed in JSON format using JavaScript and sent to the server via an HTTP POST request.

[0131] Data processing and calculation methods

[0132] Server Operation

[0133] 1. The server sets up a dedicated endpoint and receives a POST request from the user, which contains order information in JSON format.

[0134] 2. The server parses the received JSON data and obtains it as a dictionary-style object using the Python json library.

[0135] 3. The server checks if the order_id, customer_id, and items exist in the parsed data using a Python if statement.

[0136] 4. The server checks whether the item_id and quantity exist for each item in the items list.

[0137] 5. Check that the quantity of each item is greater than or equal to 0. If the value is invalid, generate an error message.

[0138] 6. If there are no errors, a message is generated stating that the order is normal and returned to the user. If there are errors, an appropriate error message is generated and returned.

[0139] Device behavior

[0140] 1. A user enters a new order on a device, either on a web form or in a mobile app, by entering the order_id, customer_id, item_id for each item, and quantity into the appropriate fields.

[0141] 2. The terminal constructs the input order information in JSON format, for example, by using JavaScript.

[0142] 3. The device sends the constructed JSON data to the server via an HTTP POST request.

[0143] User Actions

[0144] 1. The user uses the terminal interface to enter the order_id, customer_id, item_id and quantity for each item.

[0145] 2. The user checks the entered order information and presses the send button, which sends the order information to the server.

[0146] 3. The user checks the response from the server. If the order is normal, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message.

[0147] Specific examples

[0148] Normal order case

[0149] The user types the following into a terminal and submits:

[0150] Order ID: ORD12345

[0151] Customer ID: CUST54321

[0152] Item ID: ITEM001, Quantity: 2

[0153] Item ID: ITEM002, Quantity: 5

[0154] The server receives this, performs checks at each step, and if all checks are passed, returns a message to the user indicating that the order contents are correct.

[0155] Cases of defective orders

[0156] The user types the following into a terminal and submits:

[0157] Order ID: ORD12345

[0158] Item ID: ITEM001

[0159] Item ID: ITEM002, Quantity: -1

[0160] The server receives this and detects that a required field is missing (no customer_id) and the quantity is incorrect (quantity is -1), which causes the server to return an appropriate error message to the user.

[0161] As described above, this system can automatically detect errors in order information and respond quickly, thereby improving business efficiency and customer satisfaction.

[0162] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0163] Specific explanation of processing steps

[0164] Server Processing Steps

[0165] Step 1:

[0166] The server receives a POST request from the user to a dedicated endpoint (e.g. / order), which is configured using the Flask framework. As input, it takes the order information in JSON format in the request body, and as output, it retrieves this data using request.get_json().

[0167] Step 2:

[0168] The server parses the received JSON data and converts it into a dictionary-style object. It uses the Python json library to retrieve the data as follows: order_data = request.get_json(). It receives JSON data as input and obtains dictionary-style data as output.

[0169] Step 3:

[0170] The server checks whether all required fields (order_id, customer_id, items) are present in the parsed data. It uses a Python if statement to check, for example, if 'order_id' not in order_data. It receives dictionary-format data as input and returns the result of the existence check (True / False) as output.

[0171] Step 4:

[0172] The server checks whether the item_id and quantity exist for each item in the items list. For each item, it performs a loop like "for item in order_data['items']" and checks if "item_id" not in item or if "quantity" not in item. It receives the items list as input and returns the result of the existence check (True / False) as output.

[0173] Step 5:

[0174] The server checks whether the quantity of each item is greater than or equal to 0. It checks with a condition such as if item['quantity'] < 0, and generates an error message if the value is invalid. It receives the quantity of each item as input, and returns the result (True / False) of whether it is an appropriate value as output.

[0175] Step 6:

[0176] If there are no errors, a message stating that the order is successful is generated and returned to the user. A response is generated as follows: return jsonify(status="success", message="The order is successful"). If there are errors, an appropriate error message is generated and returned. The results of each check are received as input, and a response message is generated as output.

[0177] Terminal processing steps

[0178] Step 1:

[0179] A user enters a new order on a terminal, entering the order_id, customer_id, item_id and quantity for each item into a web form or mobile app interface. As input, it takes the user's input data and as output, it holds the order information.

[0180] Step 2:

[0181] The terminal constructs the entered order information in JSON format. For example, it constructs the data using JavaScript as follows: let orderData = { "order_id": "ORD12345", "customer_id": "CUST54321", "items": [{"item_id": "ITEM001", "quantity": 2}, {"item_id": "ITEM002", "quantity": 5}]};. It receives the user's input data as input and creates JSON-formatted order information as output.

[0182] Step 3:

[0183] The terminal sends the constructed JSON data to the server via an HTTP POST request. It uses fetch or axios to send it as follows: fetch(' / order', { method: 'POST', headers: { 'Content-Type': 'application / json'}, body: JSON.stringify(orderData)});. It receives JSON-formatted order information as input and sends the data to the server as output.

[0184] Step 4:

[0185] The terminal receives the response from the server. For example, it obtains the response from the server using response.json() in JavaScript. It receives the response data from the server as input and obtains the response message as output.

[0186] Step 5:

[0187] If an error message is returned, display the item that needs to be corrected to the user. If a correct response is returned, display that the order has been accepted. As input, it takes the response from the server and as output, it creates an appropriate message to display to the user.

[0188] User processing steps

[0189] Step 1:

[0190] The user uses the terminal interface to enter the order_id, customer_id, item_id and quantity for each item, or uses text boxes and dropdowns in a web form, or enters their order information as input.

[0191] Step 2:

[0192] The user checks the order information they entered and presses the send button. This action sends the order information to the server. The order information entered on the terminal is checked as input, and the send action is executed as output.

[0193] Step 3:

[0194] The user checks the response from the server. If the order is normal, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message. The response message from the server is received as input, and the appropriate action is taken as output.

[0195] (Application example 1)

[0196] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0197] In conventional ordering systems, errors that occur when entering order information (for example, missing required fields, incorrect quantities, etc.) are a frequent problem for users. When an error occurs, it must be corrected manually, which takes time and effort. This not only reduces the efficiency of the entire ordering process and customer satisfaction, but also places a heavy burden on administrative procedures. Furthermore, delayed detection of errors can lead to delivery delays and inventory management issues. Therefore, there is a need for a system that can quickly and automatically detect errors in order information and prompt users to take immediate action.

[0198] 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.

[0199] In this invention, the server includes means for receiving order information, means for analyzing required items from the received order information, means for detecting missing required items in the order information, means for detecting missing information for each item in the order information, means for detecting inappropriate quantities in the order information, means for generating an order acceptance message if there are no errors, means for inputting order information and sending a POST request to the endpoint using a smartphone device, means for receiving a response from the server and determining the next action based on the response, and means for displaying an error message and prompting the user to correct the error. This makes it possible to quickly and automatically detect errors in the order information and provide the user with instructions to correct the error in real time.

[0200] "Order information" refers to all the information entered by a user when placing an order, and is a data set including the order_id, customer_id, and items data.

[0201] "Required fields" refer to the main information elements that are essential for order information, such as order_id, customer_id, and items.

[0202] "Means of receiving" refers to the mechanism by which data is acquired from the outside and incorporated into the system.

[0203] The "means for analyzing" is a process for analyzing the received data and extracting and shaping the necessary information elements.

[0204] "Means of detection" are mechanisms for detecting abnormalities or deficiencies based on specific conditions or rules.

[0205] "Inappropriate quantity" refers to a situation where the quantity included in the order information is inappropriate, such as when a negative number or an extremely large number is included.

[0206] An "order acceptance message" is a notification of acceptance sent after confirming that the order information is appropriate.

[0207] A "smartphone device" refers to a multi-functional mobile terminal that has the functionality of a mobile phone and is capable of various information processing functions.

[0208] An "endpoint" is a resource on a server for sending specific data and is a specific URL that receives API requests.

[0209] A "POST request" is one of the HTTP methods for sending data from a client to a server.

[0210] The "means for receiving a response" is the process of obtaining a response from the server and performing internal processing.

[0211] An "error message" is a message intended to inform the user about a detected error.

[0212] "Means to prompt corrections" refers to a mechanism that instructs the user to correct errors if they are found.

[0213] To put the present invention into practice, a system is constructed that automatically detects and promptly addresses any inaccuracies in order information, primarily using a server and a smartphone device (terminal). A specific embodiment of this system is described below.

[0214] Server Operation

[0215] The server receives, analyzes, and detects errors in order information. Specifically, it uses the following hardware and software:

[0216] Hardware: A computer for the server. Cloud-based servers are also available.

[0217] Software: Flask (lightweight web application framework), Python (programming language).

[0218] The server's role is to:

[0219] 1. Receiving method: The server sets up a dedicated endpoint to receive POST requests from users, which contain order information in JSON format.

[0220] 2. Parsing method: The server parses the JSON-formatted order information from the request body and obtains the entire order as a dictionary-format object.

[0221] 3. Method for detecting defects: Check the required items in the order information (order_id, customer_id, items) and the details of each item (item_id, quantity) to detect any defects.

[0222] 4. Response generation means: If there are no errors, a message indicating that the order is successful is generated and returned to the user. If there are errors, an appropriate error message is generated.

[0223] Terminal (smartphone) operation

[0224] The user inputs order information using a smartphone device and transmits it to the server using the following software:

[0225] Software: React Native (cross-platform framework), Axios (HTTP client).

[0226] The terminal roles are as follows:

[0227] 1. Input means: Provides an interface for users to input and submit order information via a smartphone app.

[0228] 2. Transmission method: Order information is constructed in the appropriate format (JSON format) and sent as a POST request to a dedicated endpoint on the server.

[0229] 3. Response receiving means: Receives a response from the server, and if it is normal, displays a message that the order has been accepted. If there is an error, displays an error message and prompts the user to make corrections.

[0230] User behavior

[0231] The user uses the interface on the terminal to enter order information and send it to the server, specifically:

[0232] 1. Enter order information: Enter the order_id, customer_id, item_id and quantity of each item as order information.

[0233] 2. Press the Send button: Check the order information you entered and press the Send button to send it to the server.

[0234] 3. Response review: Receive the response from the server, and if there are no errors, confirm that the order has been accepted. If there are errors, make the necessary corrections based on the error message.

[0235] Specific examples

[0236] Successful order case:

[0237] The user enters and submits the following order information:

[0238] {

[0239] "order_id": "ORD12345",

[0240] "customer_id": "CUST54321",

[0241] "items": [

[0242] {"item_id": "ITEM001", "quantity": 2},

[0243] {"item_id": "ITEM002", "quantity": 5}

[0244] ]

[0245] }

[0246] The server receives this and performs checks at each step, and if all checks pass, returns a message to the user indicating that the order is correct.

[0247] In case of an incomplete order:

[0248] The user enters and submits the following order information:

[0249] {

[0250] "order_id": "ORD12345",

[0251] "items": [

[0252] {"item_id": "ITEM001"},

[0253] {"item_id": "ITEM002", "quantity": -1}

[0254] ]

[0255] }

[0256] The server receives this and detects that a required field is missing (no customer_id) and the quantity is incorrect (quantity is -1), which causes the server to return the following error message to the user:

[0257] {

[0258] "status": "error",

[0259] "message": "Required fields are missing"

[0260] }

[0261] or

[0262] {

[0263] "status": "error",

[0264] "message": "Invalid quantity: {'item_id': 'ITEM002', 'quantity': -1}"

[0265] }

[0266] Prompt Sentence Examples

[0267] Prompt statement:

[0268] "Please input the order information including order_id, customer_id, and items with item_id and quantity. Make sure all required fields are filled and quantities are valid."

[0269] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0270] Step 1:

[0271] Input: The user inputs the order information on the smartphone device.

[0272] Specific operation: The user enters the order_id, customer_id, item_id and quantity of each item into the input fields of the smartphone app. This forms the order information.

[0273] Step 2:

[0274] Input: The user presses the submit button.

[0275] Specific operation: The entered order information is constructed in JSON format within the smartphone device.

[0276] Step 3:

[0277] Input: The smartphone device sends the constructed order information in JSON format to the server endpoint via a POST request.

[0278] Specific operation: The smartphone device sends a POST request to the specified endpoint of the server via the network. This request contains order information in JSON format.

[0279] Step 4:

[0280] Input: The server receives a POST request.

[0281] What happens: The server endpoint captures the request and extracts the JSON data from the request body.

[0282] Step 5:

[0283] Input: The server parses the received order information.

[0284] Specific operation: The server parses the extracted JSON data and obtains it as a dictionary-style object. Specifically, it separates information such as order_id, customer_id, and items.

[0285] Step 6:

[0286] Input: The server checks for missing required fields based on the analysis results.

[0287] Specific operation: The server checks whether the order_id, customer_id, and items exist in the order information it retrieves. If any required items are missing, it will proceed to the next step.

[0288] Step 7:

[0289] Input: The server checks each item for missing information.

[0290] Specific operation: The server checks whether the item_id and quantity are present for each element in the items list. If any information is missing, it proceeds to the next step.

[0291] Step 8:

[0292] Input: The server checks the quantity for validity.

[0293] Specific operation: The server checks whether the quantity of each item is greater than or equal to 0. If an invalid quantity is detected, it proceeds to the next step.

[0294] Step 9:

[0295] Input: The server determines whether there are any errors.

[0296] Specific operation: Determine whether there are any defects based on the past check results. If there are any defects, generate an error message. If there are no defects, generate an order acceptance message.

[0297] Step 10:

[0298] Input: The server sends the message back to the user.

[0299] Specific operation: The server generates a message (error or acceptance) in JSON format according to the judgment result and returns it to the smartphone device as a response.

[0300] Step 11:

[0301] Input: The device receives a response from the server.

[0302] Specific operation: The smartphone device receives the response from the server and analyzes the content.

[0303] Step 12:

[0304] Input: The device determines the next action based on the analysis results.

[0305] Specific operation: Based on the response from the server, if the order is normal, an order acceptance message is displayed; if there is an error, an error message is displayed on the screen to prompt the user to correct the error.

[0306] Example prompt sentence:

[0307] "Please input the order information including order_id, customer_id, and items with item_id and quantity. Make sure all required fields are filled and quantities are valid."

[0308] 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.

[0309] The following describes in detail the mode for carrying out the present invention. This system combines an emotion engine with an automatic response system for inquiries about incomplete order contents, receives order information according to a specific procedure, automatically detects and responds to any incompleteness, and recognizes the user's emotions and provides feedback.

[0310] Server Operation

[0311] 1. The server sets up a dedicated endpoint to receive POST requests from users, which contain order information in JSON format.

[0312] 2. The server parses the JSON-formatted order information from the request body, obtaining the entire order information as a dictionary-format object.

[0313] 3. The server checks whether all required fields (order_id, customer_id, items) are present in the parsed order information. If these fields are missing, the server generates and returns an error message.

[0314] 4. The server then checks for missing information for each item in the order information, specifically checking whether each item has an item_id and quantity.

[0315] 5. The server checks whether the quantity of each item in the order information is a valid value (usually 0 or greater), thereby detecting whether an invalid value for quantity has been entered.

[0316] 6. If any errors are detected in any of the above steps, the server generates an error message and returns it to the user. If no errors are detected, the server generates a success message indicating that the order is successful and returns it to the user.

[0317] 7. The server recognizes the user's emotions using the emotion engine, and provides appropriate feedback to the user based on the inspection result (success or error) of the order information and the emotion data.

[0318] Device behavior

[0319] 1. A user enters a new order at a terminal and sends it to the system.

[0320] 2. The terminal constructs the order information in the appropriate format (JSON format) and sends a POST request to the server's dedicated endpoint.

[0321] 3. The device receives the response from the server and decides the next action based on it. For example, if an error message is returned, it displays the items that need to be corrected to the user. It also displays feedback based on the emotion engine.

[0322] User Actions

[0323] 1. The user uses the interface on the terminal to enter order information, including the order_id, customer_id, item_id and quantity for each item.

[0324] 2. The user checks the entered order information and presses the submit button. This action sends the order information to the server.

[0325] 3. The user receives a response from the server. If the order is correct, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message.

[0326] 4. Users also receive feedback from the emotion engine. For example, when a flaw is detected, the emotion engine recognizes the user's stress or confusion and provides gentle feedback and support accordingly.

[0327] Specific examples

[0328] Normal order case

[0329] The user enters the following order information on the terminal and submits it:

[0330] json

[0331] {

[0332] "order_id": "ORD12345",

[0333] "customer_id": "CUST54321",

[0334] "items": [

[0335] {"item_id": "ITEM001", "quantity": 2},

[0336] {"item_id": "ITEM002", "quantity": 5}

[0337] ]

[0338] }

[0339] The server receives this and performs checks at each step. If all checks pass, it returns a message to the user indicating that the order is correct. The emotion engine also recognizes the user's satisfaction and provides positive feedback to that effect.

[0340] Cases of defective orders

[0341] The user enters the following order information on the terminal and submits it:

[0342] json

[0343] {

[0344] "order_id": "ORD12345",

[0345] "items": [

[0346] {"item_id": "ITEM001"},

[0347] {"item_id": "ITEM002", "quantity": -1}

[0348] ]

[0349] }

[0350] The server receives this and detects that a required field is missing (no customer_id) and the quantity is incorrect (quantity is -1), which causes the server to return the following error message to the user:

[0351] json

[0352] {

[0353] "status": "error",

[0354] "message": "Required fields are missing"

[0355] }

[0356] or

[0357] json

[0358] {

[0359] "status": "error",

[0360] "message": "Invalid quantity: {'item_id': 'ITEM002', 'quantity': -1}"

[0361] }

[0362] Additionally, the emotion engine recognizes when a user is confused or stressed and offers corresponding supportive or encouraging messages:

[0363] json

[0364] {

[0365] "status": "error",

[0366] "message": "Invalid quantity: {'item_id': 'ITEM002', 'quantity': -1}",

[0367] "emotion_feedback": "We're sorry you encountered an issue. Please enter the required information and try again."

[0368] }

[0369] This system automatically detects errors in order details and responds quickly, thereby improving operational efficiency and customer satisfaction. In addition, the introduction of an emotion engine improves the user experience and helps build good relationships with customers.

[0370] The processing flow will be explained below.

[0371] Step 1:

[0372] The server receives a POST request to a dedicated endpoint and receives the order information sent by the user from the terminal as JSON format data.

[0373] Step 2:

[0374] The server parses the received request body and converts the JSON data into a dictionary-style object. Through this parsing, the entire order information is obtained as data.

[0375] Step 3:

[0376] The server checks whether all required items (order_id, customer_id, and items) are present in the order information. If these items are missing, the server generates and returns an error message.

[0377] Step 4:

[0378] The server checks whether the item_id and quantity are present for each item in items. If they are missing, the server generates and returns a detailed error message.

[0379] Step 5:

[0380] The server checks whether the quantity value for each item in items is greater than 0, i.e., whether it is an invalid quantity. If an invalid quantity is detected, the server generates and returns an error message indicating this.

[0381] Step 6:

[0382] The server generates an error or success message based on the result of detecting the order information and returns it to the user. If there are no errors, it generates a success message indicating that the order is normal.

[0383] Step 7:

[0384] The server uses an emotion engine to recognize the user's emotions in real time, and provides appropriate feedback to the user based on the inspection result (success or error) of the order information and the emotion data.

[0385] Step 8:

[0386] The device receives the response from the server and decides the next action based on it. For example, if an error message is returned, it will display the items that need to be corrected to the user and also display feedback from the emotion engine.

[0387] Step 9:

[0388] The user receives the response message returned from the server, and if an error message is included, corrects the order information according to the instructions. If there are no errors, the user confirms that the order has been accepted.

[0389] Step 10:

[0390] If necessary, the user can resubmit the revised order information to the server for rechecking, and receive feedback from the emotion engine again.

[0391] Example 2

[0392] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0393] Conventional order processing systems have had the problem of requiring a lot of time and effort to detect errors in order information. Furthermore, when a user submits an order with errors, the system provides little feedback, which hinders the user experience. In particular, the lack of appropriate feedback and support for orders with errors was a factor that led to a decline in user satisfaction.

[0394] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for receiving order information, a means for analyzing required items from the received order information, a means for detecting whether required items are missing from the order information, a means for detecting whether information on each item is missing from the order information, a means for detecting inappropriate quantities in the order information, a means for generating an order acceptance message if there are no deficiencies, a means for detecting an emotional state, and a means for generating feedback based on the emotional state. This makes it possible to quickly and automatically detect deficiencies in the order content and provide appropriate feedback that also takes the user's emotions into consideration.

[0395] "Order Information" means data entered by a user when placing an order, including an identifier, customer identifier, item list, and other related information.

[0396] "Required items" are particularly important elements of the order information, and include an identifier, a customer identifier, and an item list.

[0397] An "identifier" is information that uniquely identifies a particular order, and typically refers to an order number or ID.

[0398] "Customer identifier" refers to information that uniquely identifies the customer who placed the order, such as customer ID or account information.

[0399] An "item list" is data that lists information about each item included in an order.

[0400] An "item identifier" is information that uniquely identifies each item in an item list, and typically refers to the product ID.

[0401] "Quantity" is information indicating the number of items ordered, and is usually expressed as an integer value.

[0402] "Emotional state" refers to the type and intensity of emotions a user experiences when placing an order and receiving feedback about it.

[0403] "Feedback" refers to response messages that return information to the user about the status or deficiencies of an order, including additional support messages based on emotional state.

[0404] "Analysis" refers to the process of deciphering received data and extracting necessary information.

[0405] "Detection" refers to the process of finding items or deficiencies that meet specific conditions.

[0406] "Generation" refers to the process of creating new data or messages.

[0407] "Reception" refers to the process of taking in data from outside.

[0408] The following describes in detail the mode for carrying out the present invention. This system combines an emotion engine with an automatic response system for inquiries about order defects. It receives order information according to a specific procedure, automatically detects and responds to any defects, and recognizes the user's emotions and provides feedback. The system consists of three main elements: a server, a terminal, and a user.

[0409] Server Operation

[0410] 1. The server sets up a dedicated endpoint to receive POST requests from users, which contain order information in JSON format.

[0411] 2. The server parses the JSON-formatted order information from the request body, extracting the entire order information as a dictionary-format object.

[0412] 3. The server checks whether all required items (identifier, customer identifier, item list) are present in the parsed order information. If these items are missing, the server generates and returns an error message.

[0413] 4. The server then checks for missing information for each item in the order information, specifically checking whether each item has an item identifier and quantity.

[0414] 5. The server checks whether the quantity of each item in the order information is a valid value (usually 0 or greater), thereby detecting whether an invalid value for quantity has been entered.

[0415] 6. If any errors are detected in any of the above steps, the server generates an error message and returns it to the user. If no errors are detected, the server generates a success message indicating that the order is successful and returns it to the user.

[0416] 7. The server recognizes the user's emotions using the emotion engine, and provides appropriate feedback to the user based on the inspection result (success or error) of the order information and the emotion data.

[0417] Device behavior

[0418] 1. A user enters a new order at a terminal and sends it to the system.

[0419] 2. The terminal constructs the order information in the appropriate format (JSON format) and sends a POST request to the server's dedicated endpoint.

[0420] 3. The device receives the response from the server and decides the next action based on it. For example, if an error message is returned, it displays the items that need to be corrected to the user. It also displays feedback based on the emotion engine.

[0421] User Actions

[0422] 1. The user uses the interface on the terminal to enter order information, including the identifier, customer identifier, item identifier and quantity for each item.

[0423] 2. The user checks the entered order information and presses the submit button. This action sends the order information to the server.

[0424] 3. The user receives a response from the server. If the order is successful, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message.

[0425] 4. Users also receive feedback from the emotion engine. For example, when a flaw is detected, the emotion engine recognizes the user's stress or confusion and provides gentle feedback and support accordingly.

[0426] Specific examples

[0427] Normal order case

[0428] A user enters the following order information on the terminal and submits it:

[0429] Prompt statement:

[0430] Order ID: ORD12345

[0431] Customer ID: CUST54321

[0432] item:

[0433] Item ID: ITEM001, Quantity: 2

[0434] Item ID: ITEM002, Quantity: 5

[0435] The server receives this and performs checks at each step. If all checks pass, it returns a message to the user indicating that the order is correct. The emotion engine also recognizes the user's satisfaction and provides positive feedback to that effect.

[0436] Cases of defective orders

[0437] A user enters the following order information on the terminal and submits it:

[0438] Prompt statement:

[0439] Order ID: ORD12345

[0440] item:

[0441] Item ID: ITEM001

[0442] Item ID: ITEM002, Quantity: -1

[0443] The server receives this and detects that a required field is missing (no customer ID) and the quantity is incorrect (quantity is -1), which causes the server to return the following error message to the user:

[0444] "Required items are missing"

[0445] or

[0446] "Invalid quantity: Item ID: ITEM002, Quantity: -1"

[0447] Additionally, the emotion engine recognizes when a user is confused or stressed and offers corresponding supportive or encouraging messages:

[0448] "Sorry for the problem. Please enter the required information and try again."

[0449] This system automatically detects errors in order details and responds quickly, thereby improving operational efficiency and customer satisfaction. In addition, the introduction of an emotion engine improves the user experience and helps build good relationships with customers.

[0450] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0451] Server Operation

[0452] Step 1:

[0453] The server has a dedicated endpoint that receives POST requests from users, which contain order information in JSON format. The input is JSON data as a POST request, and the output is a parseable JSON object.

[0454] Step 2:

[0455] The server parses the JSON order information from the request body. This parses the entire order information as a dictionary object. The input is the received JSON data, and the output is a dictionary object.

[0456] Step 3:

[0457] The server checks whether all required items (identifier, customer identifier, item list) are present in the parsed order information. If these items are missing, the server generates and returns an error message. The input is a dictionary object, and the output is a Boolean value of the check result and an error message.

[0458] Step 4:

[0459] The server checks whether the item identifier and quantity are present for each item in the order information. If they are missing, the server generates an error message for that item. The input is a dictionary object, and the output is a Boolean result of the check and an error message.

[0460] Step 5:

[0461] The server checks whether the quantity of each item in the order information is a valid value (usually 0 or greater). If the quantity is invalid, the server generates an error message. The input is a dictionary object, and the output is a Boolean value of the check result and an error message.

[0462] Step 6:

[0463] If any errors are detected at any of the above steps, the server generates an error message and returns it to the user. If no errors are found, it generates a success message stating that the order is normal and returns it to the user. The input is the check result at each step, and the output is an error message or a success message.

[0464] Step 7:

[0465] The server uses an emotion engine to recognize the user's emotion. Based on the inspection result (success or error) of the order information and the emotion data, it provides appropriate feedback to the user. The input is the inspection result and user interaction data, and the output is a feedback message based on the emotion.

[0466] Device behavior

[0467] Step 1:

[0468] A user enters a new order on a terminal and sends it to the system. The input is the data the user entered into the interface, and the output is the constructed order information in JSON format.

[0469] Step 2:

[0470] The terminal constructs the order information in the appropriate format (JSON format) and sends a POST request to a dedicated endpoint on the server. The input is the data entered by the user, and the output is the JSON data sent to the server.

[0471] Step 3:

[0472] The device receives the response from the server and determines the next action based on that. For example, if an error message is returned, it displays the items that need to be corrected to the user. It also displays feedback from the emotion engine. The input is the response message from the server, and the output is the feedback message displayed to the user.

[0473] User Actions

[0474] Step 1:

[0475] The user uses the interface on the terminal to enter order information, including an identifier, a customer identifier, an item identifier and a quantity for each item. The input is the data entered by the user into the interface, and the output is confirmation of the input fields displayed on the terminal.

[0476] Step 2:

[0477] The user confirms the entered order information and presses the send button. This action sends the order information to the server. The input is the confirmed order information, and the output is a trigger for sending to the server.

[0478] Step 3:

[0479] The user receives a response from the server. If the order is normal, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message. The input is the response message from the server, and the output is the action to correct or confirm the order.

[0480] Step 4:

[0481] The user also receives feedback from the emotion engine. For example, when a flaw is detected, the emotion engine recognizes the user's stress or confusion and provides gentle feedback and support accordingly. The input is the feedback message from the emotion engine, and the output is the user's next action (correction or resubmission).

[0482] (Application example 2)

[0483] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0484] While conventional order management systems can detect errors in order information, they have the problem of not being able to properly manage the user's feelings and provide feedback. As a result, when users feel stressed or confused, they are unable to respond quickly and appropriately, which can lead to a poor user experience. Furthermore, there is a demand for smartphone applications that allow users to easily enter appropriate order information and receive immediate feedback.

[0485] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving order information, means for analyzing required items from the received order information, means for detecting whether required items in the order information are missing, means for detecting whether information on each item in the order information is missing, means for detecting inappropriate quantities in the order information, means for generating an order acceptance message if there are no defects, means for recognizing the user's emotions, and means for providing feedback based on the user's emotions. This makes it possible to quickly detect defects in the order content and provide appropriate feedback based on the user's emotions.

[0486] "Order information" refers to detailed order information entered by a user when purchasing a product or service.

[0487] "Required items" are important data items that are indispensable within the order information, and examples include order_id, customer_id, and items.

[0488] "Quantity" is a numerical value that indicates the number of each item in the order information.

[0489] An "emotion engine" is a system that recognizes and analyzes emotions from the text, voice, facial expressions, etc. entered by the user.

[0490] "Feedback" refers to the reply or response that a system provides to a user, particularly one that is appropriate in response to the user's emotions.

[0491] A "server" is a computer system that receives requests from clients and returns responses to those requests.

[0492] An "order acceptance message" is a message sent to a user when the order information is normal, informing the user that the order has been accepted.

[0493] An "incomplete" is when required data or information is missing or incorrect in the order information.

[0494] "Means for analysis" refers to systems or software that have the function of breaking down and analyzing the received data and extracting the necessary information.

[0495] "Means of detection" are systems or software that have the functionality to find missing information or inappropriate values.

[0496] A "means for providing feedback" is a system or software that has the functionality to generate and provide an appropriate reply or response based on the user's emotions and the status of the order information.

[0497] The following is a detailed description of an embodiment of the present invention. This system combines an automatic response system for inquiries about incomplete order contents with an emotion engine, and the server, terminal, and user each play their role according to a specific procedure.

[0498] The server sets up a dedicated endpoint and receives POST requests from users. This request contains order information in JSON format. The server parses the JSON-formatted order information from the request body and obtains it as a dictionary-format object. Next, it checks whether all required fields (order_id, customer_id, items) are present in the order information, and if any are missing, it generates and returns an error message. It also checks the item_id and quantity for each item to ensure that the quantity is an appropriate value (0 or greater). This detects whether an invalid value for the quantity has been entered. If there are no errors, it generates a success message stating that the order is normal and returns it to the user.

[0499] The server then uses an emotion engine to recognize the user's emotions. It is recommended to use an external service (e.g., Hume AI) for this emotion recognition. The emotion engine analyzes the user's input text to detect emotions such as stress or confusion. To provide feedback based on the detected emotion, the server generates an appropriate support message along with a success or error message.

[0500] The terminal helps the user enter a new order and submit it to the system. The order is constructed in the appropriate format (JSON) and a POST request is sent to a dedicated endpoint on the server. When a response is received from the server, it determines the next action to take. If an error message is returned, it displays the items that need to be corrected to the user, as well as feedback from the emotion engine.

[0501] The user inputs order information using the interface on the terminal, confirms it, and then submits it. The submitted data is checked by the server, and if the order is correct, the user receives a confirmation message, or if there is a problem, an error message and emotional feedback.

[0502] As a concrete example, consider the case of a successful order. Consider the case where a user enters the following order information on a terminal and submits it:

[0503] {

[0504] "order_id": "ORD12345",

[0505] "customer_id": "CUST54321",

[0506] "items": [

[0507] {"item_id": "ITEM001", "quantity": 2},

[0508] {"item_id": "ITEM002", "quantity": 5}

[0509] ]

[0510] }

[0511] The server receives this and checks each step. If all checks pass, it returns a message to the user indicating that the order is correct. The emotion engine also recognizes the user's satisfaction and provides positive feedback.

[0512] Also, consider the following example of an incomplete order:

[0513] {

[0514] "order_id": "ORD12345",

[0515] "items": [

[0516] {"item_id": "ITEM001"},

[0517] {"item_id": "ITEM002", "quantity": -1}

[0518] ]

[0519] }

[0520] The server receives this and detects the lack of required fields (no customer_id) and the inappropriate quantity (quantity is -1). Along with the error message, the server's emotion engine recognizes the user's confusion and stress and provides a corresponding support message.

[0521] Examples of prompts for a generative AI model might include:

[0522] Detect the order information entered by the user and display an error message for any incomplete items. Also, use a sentiment engine to analyze the user's sentiment and display appropriate feedback. The order information is as follows:

[0523] {

[0524] "order_id": "ORD67890",

[0525] "customer_id": "CUST12345",

[0526] "items": [

[0527] {"item_id": "ITEM123", "quantity": 1}

[0528] ],

[0529] "user_message": "I'm having trouble placing my order."

[0530] }

[0531] This system automatically detects errors in order details and responds quickly, improving operational efficiency and customer satisfaction. In addition, the introduction of an emotion engine improves the user experience and helps build good relationships with customers.

[0532] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0533] Step 1:

[0534] The user enters order information on the terminal. Specifically, the user uses a dedicated interface to enter the order_id, customer_id, and item_id and quantity of each item, and then presses the submit button. This creates the order information in JSON format.

[0535] Input: order_id, customer_id, item_id, quantity

[0536] Output: Order information in JSON format

[0537] Step 2:

[0538] The terminal sends the constructed JSON-formatted order information to the server. Specifically, the terminal sends a POST request to a dedicated endpoint on the server, with the order information included in the request body.

[0539] Input: Order information in JSON format

[0540] Output: POST request

[0541] Step 3:

[0542] The server receives the POST request sent from the terminal. Specifically, it receives the request at a dedicated endpoint, extracts the order information from the request body, and parses it into a dictionary-style object.

[0543] Input: POST request

[0544] Output: Order information in dictionary format

[0545] Step 4:

[0546] The server checks whether all required fields (order_id, customer_id, items) are present in the received order information. If any fields are missing, it generates and returns an error message.

[0547] Input: Order information in dictionary format

[0548] Output: Error message or proceed to next step

[0549] Step 5:

[0550] The server checks whether each item in the order information has an item_id and quantity. If the information is insufficient, it generates and returns an error message. It also checks whether the quantity is valid and returns an error message if it is inappropriate.

[0551] Input: Order information in dictionary format

[0552] Output: Error message or proceed to next step

[0553] Step 6:

[0554] If all checks are passed, the server generates a success message indicating that the order contents are correct and returns it to the user.

[0555] Input: Order information in dictionary format

[0556] Output: Success message

[0557] Step 7:

[0558] The server uses an emotion engine to recognize the user's emotions. Specifically, it sends message data from the user to an emotion recognition library (e.g., Hume AI) to obtain emotion data.

[0559] Input: User's message data

[0560] Output: Emotion data

[0561] Step 8:

[0562] The server generates appropriate feedback based on the emotion data. For example, it generates a supportive message if the user is confused, or positive feedback if the user is satisfied. This feedback is polite and sensitive to the user's emotions.

[0563] Input: Emotion data

[0564] Output: Feedback message

[0565] Step 9:

[0566] The user receives a response from the server on their terminal, and if the response is a success message, they know that their order has been accepted, or if there are any issues, they see an error message and emotion-based feedback.

[0567] Input: Response message from the server

[0568] Output: Messages to be displayed (success message, error message, feedback message)

[0569] This series of steps realizes a system that can automatically detect incomplete order information and provide feedback that is sensitive to the user's emotions.

[0570] 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.

[0571] 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> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0572] 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.

[0573] [Second embodiment]

[0574] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0575] 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.

[0576] 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).

[0577] 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.

[0578] 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.

[0579] 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).

[0580] 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.

[0581] 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.

[0582] 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.

[0583] 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.

[0584] 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.

[0585] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0586] The present invention is described in detail below with reference to an embodiment thereof. The present system is an automatic response system for inquiries about incomplete order contents, which receives order information according to a specific procedure, automatically detects any incompleteness, and responds accordingly.

[0587] Server Operation

[0588] 1. The server sets up a dedicated endpoint to receive POST requests from users, which contain order information in JSON format.

[0589] 2. The server parses the JSON order information from the request body, which returns the entire order as a dictionary object.

[0590] 3. The server checks whether all required fields (order_id, customer_id, items) are present in the parsed order information, thereby detecting the basic defect.

[0591] 4. The server then checks for missing information for each item in the order information, specifically checking whether each item has an item_id and quantity.

[0592] 5. The server checks whether the quantity of each item is a valid value (usually 0 or greater), which detects whether an invalid value for quantity has been entered.

[0593] 6. If any of these checks fail, the server generates an appropriate error message and returns it to the user. If there are no errors, the server generates a message stating that the order is successful and returns it to the user.

[0594] Device behavior

[0595] 1. A user enters a new order at a terminal and sends it to the system.

[0596] 2. The terminal constructs the order information in the appropriate format (JSON format) and sends a POST request to the server's dedicated endpoint.

[0597] 3. The device receives the response from the server and decides the next action based on it. For example, if an error message is returned, it displays the items that need to be corrected to the user.

[0598] User Actions

[0599] 1. The user uses the interface on the terminal to enter order information, including the order_id, customer_id, item_id and quantity for each item.

[0600] 2. The user checks the entered order information and presses the submit button. This action sends the order information to the server.

[0601] 3. The user receives a response from the server. If the order is correct, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message.

[0602] Specific examples

[0603] Normal order case

[0604] The user enters the following order information on the terminal and submits it:

[0605] json

[0606] {

[0607] "order_id": "ORD12345",

[0608] "customer_id": "CUST54321",

[0609] "items": [

[0610] {"item_id": "ITEM001", "quantity": 2},

[0611] {"item_id": "ITEM002", "quantity": 5}

[0612] ]

[0613] }

[0614] The server receives this and performs checks at each step. If all checks pass, it returns a message to the user indicating that the order is correct.

[0615] Cases of defective orders

[0616] The user enters the following order information on the terminal and submits it:

[0617] json

[0618] {

[0619] "order_id": "ORD12345",

[0620] "items": [

[0621] {"item_id": "ITEM001"},

[0622] {"item_id": "ITEM002", "quantity": -1}

[0623] ]

[0624] }

[0625] The server receives this and detects that a required field is missing (no customer_id) and the quantity is incorrect (quantity is -1), which causes the server to return the following error message to the user:

[0626] json

[0627] {

[0628] "status": "error",

[0629] "message": "Required fields are missing"

[0630] }

[0631] or

[0632] json

[0633] {

[0634] "status": "error",

[0635] "message": "Invalid quantity: {'item_id': 'ITEM002', 'quantity': -1}"

[0636] }

[0637] This system automatically detects any errors in the order contents and responds quickly, thereby improving work efficiency and customer satisfaction.

[0638] The processing flow will be explained below.

[0639] Step 1:

[0640] The server receives a POST request to a dedicated endpoint and receives the order information sent by the user from the terminal as JSON format data.

[0641] Step 2:

[0642] The server parses the received request body and converts the JSON data into a dictionary-style object. Through this parsing, the entire order information is obtained as data.

[0643] Step 3:

[0644] The server checks whether all required fields, order_id, customer_id, and items, are present in the order information. If these fields are missing, the server generates and returns an error message.

[0645] Step 4:

[0646] The server checks whether the item_id and quantity are present for each item in items. If they are missing, the server generates and returns a detailed error message.

[0647] Step 5:

[0648] The server checks whether the quantity value for each item in items is greater than 0, i.e., whether it is an invalid quantity. If an invalid quantity is detected, the server generates and returns an error message indicating this.

[0649] Step 6:

[0650] If the server passes all checks, it generates a success message indicating that the order information is correct and returns it to the user.

[0651] Step 7:

[0652] The user receives the response message returned from the server, and if an error message is included, corrects the order information according to the instructions. If there are no errors, the user confirms that the order has been accepted.

[0653] Step 8:

[0654] If necessary, the user can send the corrected order information back to the server for recheck.

[0655] Example 1

[0656] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0657] The process of manually reviewing order information is time-consuming and prone to human error. This reduces the efficiency of order processing operations and risks lowering customer satisfaction. Furthermore, incomplete order information can cause delays throughout the entire process. Therefore, there is a need for a system that can automatically review order information and take appropriate action.

[0658] 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.

[0659] In this invention, the server includes means for receiving order information, means for analyzing the received order information in JSON format, means for detecting missing required items in the order information, means for detecting missing information for each item in the order information, means for detecting inappropriate quantities in the order information, means for generating an order acceptance message if there are no errors, and means for generating and returning an appropriate error message if there are errors, thereby enabling automatic inspection of order information and error handling.

[0660] "Order information" refers to information provided when a customer places an order for a product or service, and typically includes items such as order_id, customer_id, and items.

[0661] "JSON format" stands for JavaScript Object Notation, a text format for representing data in a format that is easy for humans to read and machines to parse.

[0662] A "server" is a computer system that provides various services and data in response to requests from clients over a network.

[0663] An "endpoint" is a URL or URI that a client uses to send a specific request to a server.

[0664] A "POST request" is a type of request method in the HTTP protocol, and is mainly used to send data to a server.

[0665] "Required fields" are data fields that are absolutely necessary for order information to be considered valid in the system, and in this invention include order_id, customer_id, and items.

[0666] An "item" is a product or service within an order, and is an individual data entry that includes an item_id and a quantity.

[0667] An "error message" is a message that the system displays to notify the user when it detects a defect or error.

[0668] An "order acceptance message" is a confirmation message returned from the server to the user when the order information is determined to be normal.

[0669] The present invention is described in detail below with reference to an embodiment thereof. The present system is an automatic response system for inquiries about incomplete order contents, which receives order information according to a specific procedure, automatically detects any incompleteness, and responds accordingly.

[0670] Hardware and software used

[0671] server

[0672] The server is a computer system running on a network that processes order information in response to requests from clients (user terminals). The server uses, for example, the Flask framework implemented in Python.

[0673] Terminal

[0674] A terminal is a device where a user enters order information and sends it to a server. It includes smartphones, tablets, and PCs with a web browser or mobile app installed. In the case of a web browser, order information is constructed in JSON format using JavaScript and sent to the server via an HTTP POST request.

[0675] Data processing and calculation methods

[0676] Server Operation

[0677] 1. The server sets up a dedicated endpoint and receives a POST request from the user, which contains order information in JSON format.

[0678] 2. The server parses the received JSON data and obtains it as a dictionary-style object using the Python json library.

[0679] 3. The server checks if the order_id, customer_id, and items exist in the parsed data using a Python if statement.

[0680] 4. The server checks whether the item_id and quantity exist for each item in the items list.

[0681] 5. Check that the quantity of each item is greater than or equal to 0. If the value is invalid, generate an error message.

[0682] 6. If there are no errors, a message is generated stating that the order is normal and returned to the user. If there are errors, an appropriate error message is generated and returned.

[0683] Device behavior

[0684] 1. A user enters a new order on a device, either on a web form or in a mobile app, by entering the order_id, customer_id, item_id for each item, and quantity into the appropriate fields.

[0685] 2. The terminal constructs the input order information in JSON format, for example, by using JavaScript.

[0686] 3. The device sends the constructed JSON data to the server via an HTTP POST request.

[0687] User Actions

[0688] 1. The user uses the terminal interface to enter the order_id, customer_id, item_id and quantity for each item.

[0689] 2. The user checks the entered order information and presses the send button, which sends the order information to the server.

[0690] 3. The user checks the response from the server. If the order is normal, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message.

[0691] Specific examples

[0692] Normal order case

[0693] The user types the following into a terminal and submits:

[0694] Order ID: ORD12345

[0695] Customer ID: CUST54321

[0696] Item ID: ITEM001, Quantity: 2

[0697] Item ID: ITEM002, Quantity: 5

[0698] The server receives this, performs checks at each step, and if all checks are passed, returns a message to the user indicating that the order contents are correct.

[0699] Cases of defective orders

[0700] The user types the following into a terminal and submits:

[0701] Order ID: ORD12345

[0702] Item ID: ITEM001

[0703] Item ID: ITEM002, Quantity: -1

[0704] The server receives this and detects that a required field is missing (no customer_id) and the quantity is incorrect (quantity is -1), which causes the server to return an appropriate error message to the user.

[0705] As described above, this system can automatically detect errors in order information and respond quickly, thereby improving business efficiency and customer satisfaction.

[0706] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0707] Specific explanation of processing steps

[0708] Server Processing Steps

[0709] Step 1:

[0710] The server receives a POST request from the user to a dedicated endpoint (e.g. / order), which is configured using the Flask framework. As input, it takes the order information in JSON format in the request body, and as output, it retrieves this data using request.get_json().

[0711] Step 2:

[0712] The server parses the received JSON data and converts it into a dictionary-style object. It uses the Python json library to retrieve the data as follows: order_data = request.get_json(). It receives JSON data as input and obtains dictionary-style data as output.

[0713] Step 3:

[0714] The server checks whether all required fields (order_id, customer_id, items) are present in the parsed data. It uses a Python if statement to check, for example, if 'order_id' not in order_data. It receives dictionary-format data as input and returns the result of the existence check (True / False) as output.

[0715] Step 4:

[0716] The server checks whether the item_id and quantity exist for each item in the items list. For each item, it performs a loop like "for item in order_data['items']" and checks if "item_id" not in item or if "quantity" not in item. It receives the items list as input and returns the result of the existence check (True / False) as output.

[0717] Step 5:

[0718] The server checks whether the quantity of each item is greater than or equal to 0. It checks with a condition such as if item['quantity'] < 0, and generates an error message if the value is invalid. It receives the quantity of each item as input, and returns the result (True / False) of whether it is an appropriate value as output.

[0719] Step 6:

[0720] If there are no errors, a message stating that the order is successful is generated and returned to the user. A response is generated as follows: return jsonify(status="success", message="The order is successful"). If there are errors, an appropriate error message is generated and returned. The results of each check are received as input, and a response message is generated as output.

[0721] Terminal processing steps

[0722] Step 1:

[0723] A user enters a new order on a terminal, entering the order_id, customer_id, item_id and quantity for each item into a web form or mobile app interface. As input, it takes the user's input data and as output, it holds the order information.

[0724] Step 2:

[0725] The terminal constructs the entered order information in JSON format. For example, it constructs the data using JavaScript as follows: let orderData = { "order_id": "ORD12345", "customer_id": "CUST54321", "items": [{"item_id": "ITEM001", "quantity": 2}, {"item_id": "ITEM002", "quantity": 5}]};. It receives the user's input data as input and creates JSON-formatted order information as output.

[0726] Step 3:

[0727] The terminal sends the constructed JSON data to the server via an HTTP POST request. It uses fetch or axios to send it as follows: fetch(' / order', { method: 'POST', headers: { 'Content-Type': 'application / json'}, body: JSON.stringify(orderData)});. It receives JSON-formatted order information as input and sends the data to the server as output.

[0728] Step 4:

[0729] The terminal receives the response from the server. For example, it obtains the response from the server using response.json() in JavaScript. It receives the response data from the server as input and obtains the response message as output.

[0730] Step 5:

[0731] If an error message is returned, display the item that needs to be corrected to the user. If a correct response is returned, display that the order has been accepted. As input, it takes the response from the server and as output, it creates an appropriate message to display to the user.

[0732] User processing steps

[0733] Step 1:

[0734] The user uses the terminal interface to enter the order_id, customer_id, item_id and quantity for each item, or uses text boxes and dropdowns in a web form, or enters their order information as input.

[0735] Step 2:

[0736] The user checks the order information they entered and presses the send button. This action sends the order information to the server. The order information entered on the terminal is checked as input, and the send action is executed as output.

[0737] Step 3:

[0738] The user checks the response from the server. If the order is normal, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message. The response message from the server is received as input, and the appropriate action is taken as output.

[0739] (Application example 1)

[0740] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0741] In conventional ordering systems, errors that occur when entering order information (for example, missing required fields, incorrect quantities, etc.) are a frequent problem for users. When an error occurs, it must be corrected manually, which takes time and effort. This not only reduces the efficiency of the entire ordering process and customer satisfaction, but also places a heavy burden on administrative procedures. Furthermore, delayed detection of errors can lead to delivery delays and inventory management issues. Therefore, there is a need for a system that can quickly and automatically detect errors in order information and prompt users to take immediate action.

[0742] 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.

[0743] In this invention, the server includes means for receiving order information, means for analyzing required items from the received order information, means for detecting missing required items in the order information, means for detecting missing information for each item in the order information, means for detecting inappropriate quantities in the order information, means for generating an order acceptance message if there are no errors, means for inputting order information and sending a POST request to the endpoint using a smartphone device, means for receiving a response from the server and determining the next action based on the response, and means for displaying an error message and prompting the user to correct the error. This makes it possible to quickly and automatically detect errors in the order information and provide the user with instructions to correct the error in real time.

[0744] "Order information" refers to all the information entered by a user when placing an order, and is a data set including the order_id, customer_id, and items data.

[0745] "Required fields" refer to the main information elements that are essential for order information, such as order_id, customer_id, and items.

[0746] "Means of receiving" refers to the mechanism by which data is acquired from the outside and incorporated into the system.

[0747] The "means for analyzing" is a process for analyzing the received data and extracting and shaping the necessary information elements.

[0748] "Means of detection" are mechanisms for detecting abnormalities or deficiencies based on specific conditions or rules.

[0749] "Inappropriate quantity" refers to a situation where the quantity included in the order information is inappropriate, such as when a negative number or an extremely large number is included.

[0750] An "order acceptance message" is a notification of acceptance sent after confirming that the order information is appropriate.

[0751] A "smartphone device" refers to a multi-functional mobile terminal that has the functionality of a mobile phone and is capable of various information processing functions.

[0752] An "endpoint" is a resource on a server for sending specific data and is a specific URL that receives API requests.

[0753] A "POST request" is one of the HTTP methods for sending data from a client to a server.

[0754] The "means for receiving a response" is the process of obtaining a response from the server and performing internal processing.

[0755] An "error message" is a message intended to inform the user about a detected error.

[0756] "Means to prompt corrections" refers to a mechanism that instructs the user to correct errors if they are found.

[0757] To put the present invention into practice, a system is constructed that automatically detects and promptly addresses any inaccuracies in order information, primarily using a server and a smartphone device (terminal). A specific embodiment of this system is described below.

[0758] Server Operation

[0759] The server receives, analyzes, and detects errors in order information. Specifically, it uses the following hardware and software:

[0760] Hardware: A computer for the server. Cloud-based servers are also available.

[0761] Software: Flask (lightweight web application framework), Python (programming language).

[0762] The server's role is to:

[0763] 1. Receiving method: The server sets up a dedicated endpoint to receive POST requests from users, which contain order information in JSON format.

[0764] 2. Parsing method: The server parses the JSON-formatted order information from the request body and obtains the entire order as a dictionary-format object.

[0765] 3. Method for detecting defects: Check the required items in the order information (order_id, customer_id, items) and the details of each item (item_id, quantity) to detect any defects.

[0766] 4. Response generation means: If there are no errors, a message indicating that the order is successful is generated and returned to the user. If there are errors, an appropriate error message is generated.

[0767] Terminal (smartphone) operation

[0768] The user inputs order information using a smartphone device and transmits it to the server using the following software:

[0769] Software: React Native (cross-platform framework), Axios (HTTP client).

[0770] The terminal roles are as follows:

[0771] 1. Input means: Provides an interface for users to input and submit order information via a smartphone app.

[0772] 2. Transmission method: Order information is constructed in the appropriate format (JSON format) and sent as a POST request to a dedicated endpoint on the server.

[0773] 3. Response receiving means: Receives a response from the server, and if it is normal, displays a message that the order has been accepted. If there is an error, displays an error message and prompts the user to make corrections.

[0774] User behavior

[0775] The user uses the interface on the terminal to enter order information and send it to the server, specifically:

[0776] 1. Enter order information: Enter the order_id, customer_id, item_id and quantity of each item as order information.

[0777] 2. Press the Send button: Check the order information you entered and press the Send button to send it to the server.

[0778] 3. Response review: Receive the response from the server, and if there are no errors, confirm that the order has been accepted. If there are errors, make the necessary corrections based on the error message.

[0779] Specific examples

[0780] Successful order case:

[0781] The user enters and submits the following order information:

[0782] {

[0783] "order_id": "ORD12345",

[0784] "customer_id": "CUST54321",

[0785] "items": [

[0786] {"item_id": "ITEM001", "quantity": 2},

[0787] {"item_id": "ITEM002", "quantity": 5}

[0788] ]

[0789] }

[0790] The server receives this and performs checks at each step, and if all checks pass, returns a message to the user indicating that the order is correct.

[0791] In case of an incomplete order:

[0792] The user enters and submits the following order information:

[0793] {

[0794] "order_id": "ORD12345",

[0795] "items": [

[0796] {"item_id": "ITEM001"},

[0797] {"item_id": "ITEM002", "quantity": -1}

[0798] ]

[0799] }

[0800] The server receives this and detects that a required field is missing (no customer_id) and the quantity is incorrect (quantity is -1), which causes the server to return the following error message to the user:

[0801] {

[0802] "status": "error",

[0803] "message": "Required fields are missing"

[0804] }

[0805] or

[0806] {

[0807] "status": "error",

[0808] "message": "Invalid quantity: {'item_id': 'ITEM002', 'quantity': -1}"

[0809] }

[0810] Prompt Sentence Examples

[0811] Prompt statement:

[0812] "Please input the order information including order_id, customer_id, and items with item_id and quantity. Make sure all required fields are filled and quantities are valid."

[0813] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0814] Step 1:

[0815] Input: The user inputs the order information on the smartphone device.

[0816] Specific operation: The user enters the order_id, customer_id, item_id and quantity of each item into the input fields of the smartphone app. This forms the order information.

[0817] Step 2:

[0818] Input: The user presses the submit button.

[0819] Specific operation: The entered order information is constructed in JSON format within the smartphone device.

[0820] Step 3:

[0821] Input: The smartphone device sends the constructed order information in JSON format to the server endpoint via a POST request.

[0822] Specific operation: The smartphone device sends a POST request to the specified endpoint of the server via the network. This request contains order information in JSON format.

[0823] Step 4:

[0824] Input: The server receives a POST request.

[0825] What happens: The server endpoint captures the request and extracts the JSON data from the request body.

[0826] Step 5:

[0827] Input: The server parses the received order information.

[0828] Specific operation: The server parses the extracted JSON data and obtains it as a dictionary-style object. Specifically, it separates information such as order_id, customer_id, and items.

[0829] Step 6:

[0830] Input: The server checks for missing required fields based on the analysis results.

[0831] Specific operation: The server checks whether the order_id, customer_id, and items exist in the order information it retrieves. If any required items are missing, it will proceed to the next step.

[0832] Step 7:

[0833] Input: The server checks each item for missing information.

[0834] Specific operation: The server checks whether the item_id and quantity are present for each element in the items list. If any information is missing, it proceeds to the next step.

[0835] Step 8:

[0836] Input: The server checks the quantity for validity.

[0837] Specific operation: The server checks whether the quantity of each item is greater than or equal to 0. If an invalid quantity is detected, it proceeds to the next step.

[0838] Step 9:

[0839] Input: The server determines whether there are any errors.

[0840] Specific operation: Determine whether there are any defects based on the past check results. If there are any defects, generate an error message. If there are no defects, generate an order acceptance message.

[0841] Step 10:

[0842] Input: The server sends the message back to the user.

[0843] Specific operation: The server generates a message (error or acceptance) in JSON format according to the judgment result and returns it to the smartphone device as a response.

[0844] Step 11:

[0845] Input: The device receives a response from the server.

[0846] Specific operation: The smartphone device receives the response from the server and analyzes the content.

[0847] Step 12:

[0848] Input: The device determines the next action based on the analysis results.

[0849] Specific operation: Based on the response from the server, if the order is normal, an order acceptance message is displayed; if there is an error, an error message is displayed on the screen to prompt the user to correct the error.

[0850] Example prompt sentence:

[0851] "Please input the order information including order_id, customer_id, and items with item_id and quantity. Make sure all required fields are filled and quantities are valid."

[0852] 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.

[0853] The following describes in detail the mode for carrying out the present invention. This system combines an emotion engine with an automatic response system for inquiries about incomplete order contents, receives order information according to a specific procedure, automatically detects and responds to any incompleteness, and recognizes the user's emotions and provides feedback.

[0854] Server Operation

[0855] 1. The server sets up a dedicated endpoint to receive POST requests from users, which contain order information in JSON format.

[0856] 2. The server parses the JSON-formatted order information from the request body, obtaining the entire order information as a dictionary-format object.

[0857] 3. The server checks whether all required fields (order_id, customer_id, items) are present in the parsed order information. If these fields are missing, the server generates and returns an error message.

[0858] 4. The server then checks for missing information for each item in the order information, specifically checking whether each item has an item_id and quantity.

[0859] 5. The server checks whether the quantity of each item in the order information is a valid value (usually 0 or greater), thereby detecting whether an invalid value for quantity has been entered.

[0860] 6. If any errors are detected in any of the above steps, the server generates an error message and returns it to the user. If no errors are detected, the server generates a success message indicating that the order is successful and returns it to the user.

[0861] 7. The server recognizes the user's emotions using the emotion engine, and provides appropriate feedback to the user based on the inspection result (success or error) of the order information and the emotion data.

[0862] Device behavior

[0863] 1. A user enters a new order at a terminal and sends it to the system.

[0864] 2. The terminal constructs the order information in the appropriate format (JSON format) and sends a POST request to the server's dedicated endpoint.

[0865] 3. The device receives the response from the server and decides the next action based on it. For example, if an error message is returned, it displays the items that need to be corrected to the user. It also displays feedback based on the emotion engine.

[0866] User Actions

[0867] 1. The user uses the interface on the terminal to enter order information, including the order_id, customer_id, item_id and quantity for each item.

[0868] 2. The user checks the entered order information and presses the submit button. This action sends the order information to the server.

[0869] 3. The user receives a response from the server. If the order is correct, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message.

[0870] 4. Users also receive feedback from the emotion engine. For example, when a flaw is detected, the emotion engine recognizes the user's stress or confusion and provides gentle feedback and support accordingly.

[0871] Specific examples

[0872] Normal order case

[0873] The user enters the following order information on the terminal and submits it:

[0874] json

[0875] {

[0876] "order_id": "ORD12345",

[0877] "customer_id": "CUST54321",

[0878] "items": [

[0879] {"item_id": "ITEM001", "quantity": 2},

[0880] {"item_id": "ITEM002", "quantity": 5}

[0881] ]

[0882] }

[0883] The server receives this and performs checks at each step. If all checks pass, it returns a message to the user indicating that the order is correct. The emotion engine also recognizes the user's satisfaction and provides positive feedback to that effect.

[0884] Cases of defective orders

[0885] The user enters the following order information on the terminal and submits it:

[0886] json

[0887] {

[0888] "order_id": "ORD12345",

[0889] "items": [

[0890] {"item_id": "ITEM001"},

[0891] {"item_id": "ITEM002", "quantity": -1}

[0892] ]

[0893] }

[0894] The server receives this and detects that a required field is missing (no customer_id) and the quantity is incorrect (quantity is -1), which causes the server to return the following error message to the user:

[0895] json

[0896] {

[0897] "status": "error",

[0898] "message": "Required fields are missing"

[0899] }

[0900] or

[0901] json

[0902] {

[0903] "status": "error",

[0904] "message": "Invalid quantity: {'item_id': 'ITEM002', 'quantity': -1}"

[0905] }

[0906] Additionally, the emotion engine recognizes when a user is confused or stressed and offers corresponding supportive or encouraging messages:

[0907] json

[0908] {

[0909] "status": "error",

[0910] "message": "Invalid quantity: {'item_id': 'ITEM002', 'quantity': -1}",

[0911] "emotion_feedback": "We're sorry you encountered an issue. Please enter the required information and try again."

[0912] }

[0913] This system automatically detects errors in order details and responds quickly, thereby improving operational efficiency and customer satisfaction. In addition, the introduction of an emotion engine improves the user experience and helps build good relationships with customers.

[0914] The processing flow will be explained below.

[0915] Step 1:

[0916] The server receives a POST request to a dedicated endpoint and receives the order information sent by the user from the terminal as JSON format data.

[0917] Step 2:

[0918] The server parses the received request body and converts the JSON data into a dictionary-style object. Through this parsing, the entire order information is obtained as data.

[0919] Step 3:

[0920] The server checks whether all required items (order_id, customer_id, and items) are present in the order information. If these items are missing, the server generates and returns an error message.

[0921] Step 4:

[0922] The server checks whether the item_id and quantity are present for each item in items. If they are missing, the server generates and returns a detailed error message.

[0923] Step 5:

[0924] The server checks whether the quantity value for each item in items is greater than 0, i.e., whether it is an invalid quantity. If an invalid quantity is detected, the server generates and returns an error message indicating this.

[0925] Step 6:

[0926] The server generates an error or success message based on the result of detecting the order information and returns it to the user. If there are no errors, it generates a success message indicating that the order is normal.

[0927] Step 7:

[0928] The server uses an emotion engine to recognize the user's emotions in real time, and provides appropriate feedback to the user based on the inspection result (success or error) of the order information and the emotion data.

[0929] Step 8:

[0930] The device receives the response from the server and decides the next action based on it. For example, if an error message is returned, it will display the items that need to be corrected to the user and also display feedback from the emotion engine.

[0931] Step 9:

[0932] The user receives the response message returned from the server, and if an error message is included, corrects the order information according to the instructions. If there are no errors, the user confirms that the order has been accepted.

[0933] Step 10:

[0934] If necessary, the user can resubmit the revised order information to the server for rechecking, and receive feedback from the emotion engine again.

[0935] Example 2

[0936] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0937] Conventional order processing systems have had the problem of requiring a lot of time and effort to detect errors in order information. Furthermore, when a user submits an order with errors, the system provides little feedback, which hinders the user experience. In particular, the lack of appropriate feedback and support for orders with errors was a factor that led to a decline in user satisfaction.

[0938] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for receiving order information, a means for analyzing required items from the received order information, a means for detecting whether required items are missing from the order information, a means for detecting whether information on each item is missing from the order information, a means for detecting inappropriate quantities in the order information, a means for generating an order acceptance message if there are no deficiencies, a means for detecting an emotional state, and a means for generating feedback based on the emotional state. This makes it possible to quickly and automatically detect deficiencies in the order content and provide appropriate feedback that also takes the user's emotions into consideration.

[0939] "Order Information" means data entered by a user when placing an order, including an identifier, customer identifier, item list, and other related information.

[0940] "Required items" are particularly important elements of the order information, and include an identifier, a customer identifier, and an item list.

[0941] An "identifier" is information that uniquely identifies a particular order, and typically refers to an order number or ID.

[0942] "Customer identifier" refers to information that uniquely identifies the customer who placed the order, such as customer ID or account information.

[0943] An "item list" is data that lists information about each item included in an order.

[0944] An "item identifier" is information that uniquely identifies each item in an item list, and typically refers to the product ID.

[0945] "Quantity" is information indicating the number of items ordered, and is usually expressed as an integer value.

[0946] "Emotional state" refers to the type and intensity of emotions a user experiences when placing an order and receiving feedback about it.

[0947] "Feedback" refers to response messages that return information to the user about the status or deficiencies of an order, including additional support messages based on emotional state.

[0948] "Analysis" refers to the process of deciphering received data and extracting necessary information.

[0949] "Detection" refers to the process of finding items or deficiencies that meet specific conditions.

[0950] "Generation" refers to the process of creating new data or messages.

[0951] "Reception" refers to the process of taking in data from outside.

[0952] The following describes in detail the mode for carrying out the present invention. This system combines an emotion engine with an automatic response system for inquiries about order defects. It receives order information according to a specific procedure, automatically detects and responds to any defects, and recognizes the user's emotions and provides feedback. The system consists of three main elements: a server, a terminal, and a user.

[0953] Server Operation

[0954] 1. The server sets up a dedicated endpoint to receive POST requests from users, which contain order information in JSON format.

[0955] 2. The server parses the JSON-formatted order information from the request body, extracting the entire order information as a dictionary-format object.

[0956] 3. The server checks whether all required items (identifier, customer identifier, item list) are present in the parsed order information. If these items are missing, the server generates and returns an error message.

[0957] 4. The server then checks for missing information for each item in the order information, specifically checking whether each item has an item identifier and quantity.

[0958] 5. The server checks whether the quantity of each item in the order information is a valid value (usually 0 or greater), thereby detecting whether an invalid value for quantity has been entered.

[0959] 6. If any errors are detected in any of the above steps, the server generates an error message and returns it to the user. If no errors are detected, the server generates a success message indicating that the order is successful and returns it to the user.

[0960] 7. The server recognizes the user's emotions using the emotion engine, and provides appropriate feedback to the user based on the inspection result (success or error) of the order information and the emotion data.

[0961] Device behavior

[0962] 1. A user enters a new order at a terminal and sends it to the system.

[0963] 2. The terminal constructs the order information in the appropriate format (JSON format) and sends a POST request to the server's dedicated endpoint.

[0964] 3. The device receives the response from the server and decides the next action based on it. For example, if an error message is returned, it displays the items that need to be corrected to the user. It also displays feedback based on the emotion engine.

[0965] User Actions

[0966] 1. The user uses the interface on the terminal to enter order information, including the identifier, customer identifier, item identifier and quantity for each item.

[0967] 2. The user checks the entered order information and presses the submit button. This action sends the order information to the server.

[0968] 3. The user receives a response from the server. If the order is successful, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message.

[0969] 4. Users also receive feedback from the emotion engine. For example, when a flaw is detected, the emotion engine recognizes the user's stress or confusion and provides gentle feedback and support accordingly.

[0970] Specific examples

[0971] Normal order case

[0972] A user enters the following order information on the terminal and submits it:

[0973] Prompt statement:

[0974] Order ID: ORD12345

[0975] Customer ID: CUST54321

[0976] item:

[0977] Item ID: ITEM001, Quantity: 2

[0978] Item ID: ITEM002, Quantity: 5

[0979] The server receives this and performs checks at each step. If all checks pass, it returns a message to the user indicating that the order is correct. The emotion engine also recognizes the user's satisfaction and provides positive feedback to that effect.

[0980] Cases of defective orders

[0981] A user enters the following order information on the terminal and submits it:

[0982] Prompt statement:

[0983] Order ID: ORD12345

[0984] item:

[0985] Item ID: ITEM001

[0986] Item ID: ITEM002, Quantity: -1

[0987] The server receives this and detects that a required field is missing (no customer ID) and the quantity is incorrect (quantity is -1), which causes the server to return the following error message to the user:

[0988] "Required items are missing"

[0989] or

[0990] "Invalid quantity: Item ID: ITEM002, Quantity: -1"

[0991] Additionally, the emotion engine recognizes when a user is confused or stressed and offers corresponding supportive or encouraging messages:

[0992] "Sorry for the problem. Please enter the required information and try again."

[0993] This system automatically detects errors in order details and responds quickly, thereby improving operational efficiency and customer satisfaction. In addition, the introduction of an emotion engine improves the user experience and helps build good relationships with customers.

[0994] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0995] Server Operation

[0996] Step 1:

[0997] The server has a dedicated endpoint that receives POST requests from users, which contain order information in JSON format. The input is JSON data as a POST request, and the output is a parseable JSON object.

[0998] Step 2:

[0999] The server parses the JSON order information from the request body. This parses the entire order information as a dictionary object. The input is the received JSON data, and the output is a dictionary object.

[1000] Step 3:

[1001] The server checks whether all required items (identifier, customer identifier, item list) are present in the parsed order information. If these items are missing, the server generates and returns an error message. The input is a dictionary object, and the output is a Boolean value of the check result and an error message.

[1002] Step 4:

[1003] The server checks whether the item identifier and quantity are present for each item in the order information. If they are missing, the server generates an error message for that item. The input is a dictionary object, and the output is a Boolean result of the check and an error message.

[1004] Step 5:

[1005] The server checks whether the quantity of each item in the order information is a valid value (usually 0 or greater). If the quantity is invalid, the server generates an error message. The input is a dictionary object, and the output is a Boolean value of the check result and an error message.

[1006] Step 6:

[1007] If any errors are detected at any of the above steps, the server generates an error message and returns it to the user. If no errors are found, it generates a success message stating that the order is normal and returns it to the user. The input is the check result at each step, and the output is an error message or a success message.

[1008] Step 7:

[1009] The server uses an emotion engine to recognize the user's emotion. Based on the inspection result (success or error) of the order information and the emotion data, it provides appropriate feedback to the user. The input is the inspection result and user interaction data, and the output is a feedback message based on the emotion.

[1010] Device behavior

[1011] Step 1:

[1012] A user enters a new order on a terminal and sends it to the system. The input is the data the user entered into the interface, and the output is the constructed order information in JSON format.

[1013] Step 2:

[1014] The terminal constructs the order information in the appropriate format (JSON format) and sends a POST request to a dedicated endpoint on the server. The input is the data entered by the user, and the output is the JSON data sent to the server.

[1015] Step 3:

[1016] The device receives the response from the server and determines the next action based on that. For example, if an error message is returned, it displays the items that need to be corrected to the user. It also displays feedback from the emotion engine. The input is the response message from the server, and the output is the feedback message displayed to the user.

[1017] User Actions

[1018] Step 1:

[1019] The user uses the interface on the terminal to enter order information, including an identifier, a customer identifier, an item identifier and a quantity for each item. The input is the data entered by the user into the interface, and the output is confirmation of the input fields displayed on the terminal.

[1020] Step 2:

[1021] The user confirms the entered order information and presses the send button. This action sends the order information to the server. The input is the confirmed order information, and the output is a trigger for sending to the server.

[1022] Step 3:

[1023] The user receives a response from the server. If the order is normal, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message. The input is the response message from the server, and the output is the action to correct or confirm the order.

[1024] Step 4:

[1025] The user also receives feedback from the emotion engine. For example, when a flaw is detected, the emotion engine recognizes the user's stress or confusion and provides gentle feedback and support accordingly. The input is the feedback message from the emotion engine, and the output is the user's next action (correction or resubmission).

[1026] (Application example 2)

[1027] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1028] While conventional order management systems can detect errors in order information, they have the problem of not being able to properly manage the user's feelings and provide feedback. As a result, when users feel stressed or confused, they are unable to respond quickly and appropriately, which can lead to a poor user experience. Furthermore, there is a demand for smartphone applications that allow users to easily enter appropriate order information and receive immediate feedback.

[1029] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving order information, means for analyzing required items from the received order information, means for detecting whether required items in the order information are missing, means for detecting whether information on each item in the order information is missing, means for detecting inappropriate quantities in the order information, means for generating an order acceptance message if there are no defects, means for recognizing the user's emotions, and means for providing feedback based on the user's emotions. This makes it possible to quickly detect defects in the order content and provide appropriate feedback based on the user's emotions.

[1030] "Order information" refers to detailed order information entered by a user when purchasing a product or service.

[1031] "Required items" are important data items that are indispensable within the order information, and examples include order_id, customer_id, and items.

[1032] "Quantity" is a numerical value that indicates the number of each item in the order information.

[1033] An "emotion engine" is a system that recognizes and analyzes emotions from the text, voice, facial expressions, etc. entered by the user.

[1034] "Feedback" refers to the reply or response that a system provides to a user, particularly one that is appropriate in response to the user's emotions.

[1035] A "server" is a computer system that receives requests from clients and returns responses to those requests.

[1036] An "order acceptance message" is a message sent to a user when the order information is normal, informing the user that the order has been accepted.

[1037] An "incomplete" is when required data or information is missing or incorrect in the order information.

[1038] "Means for analysis" refers to systems or software that have the function of breaking down and analyzing the received data and extracting the necessary information.

[1039] "Means of detection" are systems or software that have the functionality to find missing information or inappropriate values.

[1040] A "means for providing feedback" is a system or software that has the functionality to generate and provide an appropriate reply or response based on the user's emotions and the status of the order information.

[1041] The following is a detailed description of an embodiment of the present invention. This system combines an automatic response system for inquiries about incomplete order contents with an emotion engine, and the server, terminal, and user each play their role according to a specific procedure.

[1042] The server sets up a dedicated endpoint and receives POST requests from users. This request contains order information in JSON format. The server parses the JSON-formatted order information from the request body and obtains it as a dictionary-format object. Next, it checks whether all required fields (order_id, customer_id, items) are present in the order information, and if any are missing, it generates and returns an error message. It also checks the item_id and quantity for each item to ensure that the quantity is an appropriate value (0 or greater). This detects whether an invalid value for the quantity has been entered. If there are no errors, it generates a success message stating that the order is normal and returns it to the user.

[1043] The server then uses an emotion engine to recognize the user's emotions. It is recommended to use an external service (e.g., Hume AI) for this emotion recognition. The emotion engine analyzes the user's input text to detect emotions such as stress or confusion. To provide feedback based on the detected emotion, the server generates an appropriate support message along with a success or error message.

[1044] The terminal helps the user enter a new order and submit it to the system. The order is constructed in the appropriate format (JSON) and a POST request is sent to a dedicated endpoint on the server. When a response is received from the server, it determines the next action to take. If an error message is returned, it displays the items that need to be corrected to the user, as well as feedback from the emotion engine.

[1045] The user inputs order information using the interface on the terminal, confirms it, and then submits it. The submitted data is checked by the server, and if the order is correct, the user receives a confirmation message, or if there is a problem, an error message and emotional feedback.

[1046] As a concrete example, consider the case of a successful order. Consider the case where a user enters the following order information on a terminal and submits it:

[1047] {

[1048] "order_id": "ORD12345",

[1049] "customer_id": "CUST54321",

[1050] "items": [

[1051] {"item_id": "ITEM001", "quantity": 2},

[1052] {"item_id": "ITEM002", "quantity": 5}

[1053] ]

[1054] }

[1055] The server receives this and checks each step. If all checks pass, it returns a message to the user indicating that the order is correct. The emotion engine also recognizes the user's satisfaction and provides positive feedback.

[1056] Also, consider the following example of an incomplete order:

[1057] {

[1058] "order_id": "ORD12345",

[1059] "items": [

[1060] {"item_id": "ITEM001"},

[1061] {"item_id": "ITEM002", "quantity": -1}

[1062] ]

[1063] }

[1064] The server receives this and detects the lack of required fields (no customer_id) and the inappropriate quantity (quantity is -1). Along with the error message, the server's emotion engine recognizes the user's confusion and stress and provides a corresponding support message.

[1065] Examples of prompts for a generative AI model might include:

[1066] Detect the order information entered by the user and display an error message for any incomplete items. Also, use a sentiment engine to analyze the user's sentiment and display appropriate feedback. The order information is as follows:

[1067] {

[1068] "order_id": "ORD67890",

[1069] "customer_id": "CUST12345",

[1070] "items": [

[1071] {"item_id": "ITEM123", "quantity": 1}

[1072] ],

[1073] "user_message": "I'm having trouble placing my order."

[1074] }

[1075] This system automatically detects errors in order details and responds quickly, improving operational efficiency and customer satisfaction. In addition, the introduction of an emotion engine improves the user experience and helps build good relationships with customers.

[1076] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1077] Step 1:

[1078] The user enters order information on the terminal. Specifically, the user uses a dedicated interface to enter the order_id, customer_id, and item_id and quantity of each item, and then presses the submit button. This creates the order information in JSON format.

[1079] Input: order_id, customer_id, item_id, quantity

[1080] Output: Order information in JSON format

[1081] Step 2:

[1082] The terminal sends the constructed JSON-formatted order information to the server. Specifically, the terminal sends a POST request to a dedicated endpoint on the server, with the order information included in the request body.

[1083] Input: Order information in JSON format

[1084] Output: POST request

[1085] Step 3:

[1086] The server receives the POST request sent from the terminal. Specifically, it receives the request at a dedicated endpoint, extracts the order information from the request body, and parses it into a dictionary-style object.

[1087] Input: POST request

[1088] Output: Order information in dictionary format

[1089] Step 4:

[1090] The server checks whether all required fields (order_id, customer_id, items) are present in the received order information. If any fields are missing, it generates and returns an error message.

[1091] Input: Order information in dictionary format

[1092] Output: Error message or proceed to next step

[1093] Step 5:

[1094] The server checks whether each item in the order information has an item_id and quantity. If the information is insufficient, it generates and returns an error message. It also checks whether the quantity is valid and returns an error message if it is inappropriate.

[1095] Input: Order information in dictionary format

[1096] Output: Error message or proceed to next step

[1097] Step 6:

[1098] If all checks are passed, the server generates a success message indicating that the order contents are correct and returns it to the user.

[1099] Input: Order information in dictionary format

[1100] Output: Success message

[1101] Step 7:

[1102] The server uses an emotion engine to recognize the user's emotions. Specifically, it sends message data from the user to an emotion recognition library (e.g., Hume AI) to obtain emotion data.

[1103] Input: User's message data

[1104] Output: Emotion data

[1105] Step 8:

[1106] The server generates appropriate feedback based on the emotion data. For example, it generates a supportive message if the user is confused, or positive feedback if the user is satisfied. This feedback is polite and sensitive to the user's emotions.

[1107] Input: Emotion data

[1108] Output: Feedback message

[1109] Step 9:

[1110] The user receives a response from the server on their terminal, and if the response is a success message, they know that their order has been accepted, or if there are any issues, they see an error message and emotion-based feedback.

[1111] Input: Response message from the server

[1112] Output: Messages to be displayed (success message, error message, feedback message)

[1113] This series of steps realizes a system that can automatically detect incomplete order information and provide feedback that is sensitive to the user's emotions.

[1114] 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.

[1115] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1116] 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.

[1117] [Third embodiment]

[1118] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1119] 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.

[1120] 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).

[1121] 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.

[1122] 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.

[1123] 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).

[1124] 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.

[1125] 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.

[1126] 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.

[1127] 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.

[1128] 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.

[1129] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1130] The present invention is described in detail below with reference to an embodiment thereof. The present system is an automatic response system for inquiries about incomplete order contents, which receives order information according to a specific procedure, automatically detects any incompleteness, and responds accordingly.

[1131] Server Operation

[1132] 1. The server sets up a dedicated endpoint to receive POST requests from users, which contain order information in JSON format.

[1133] 2. The server parses the JSON order information from the request body, which returns the entire order as a dictionary object.

[1134] 3. The server checks whether all required fields (order_id, customer_id, items) are present in the parsed order information, thereby detecting the basic defect.

[1135] 4. The server then checks for missing information for each item in the order information, specifically checking whether each item has an item_id and quantity.

[1136] 5. The server checks whether the quantity of each item is a valid value (usually 0 or greater), which detects whether an invalid value for quantity has been entered.

[1137] 6. If any of these checks fail, the server generates an appropriate error message and returns it to the user. If there are no errors, the server generates a message stating that the order is successful and returns it to the user.

[1138] Device behavior

[1139] 1. A user enters a new order at a terminal and sends it to the system.

[1140] 2. The terminal constructs the order information in the appropriate format (JSON format) and sends a POST request to the server's dedicated endpoint.

[1141] 3. The device receives the response from the server and decides the next action based on it. For example, if an error message is returned, it displays the items that need to be corrected to the user.

[1142] User Actions

[1143] 1. The user uses the interface on the terminal to enter order information, including the order_id, customer_id, item_id and quantity for each item.

[1144] 2. The user checks the entered order information and presses the submit button. This action sends the order information to the server.

[1145] 3. The user receives a response from the server. If the order is correct, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message.

[1146] Specific examples

[1147] Normal order case

[1148] The user enters the following order information on the terminal and submits it:

[1149] json

[1150] {

[1151] "order_id": "ORD12345",

[1152] "customer_id": "CUST54321",

[1153] "items": [

[1154] {"item_id": "ITEM001", "quantity": 2},

[1155] {"item_id": "ITEM002", "quantity": 5}

[1156] ]

[1157] }

[1158] The server receives this and performs checks at each step. If all checks pass, it returns a message to the user indicating that the order is correct.

[1159] Cases of defective orders

[1160] The user enters the following order information on the terminal and submits it:

[1161] json

[1162] {

[1163] "order_id": "ORD12345",

[1164] "items": [

[1165] {"item_id": "ITEM001"},

[1166] {"item_id": "ITEM002", "quantity": -1}

[1167] ]

[1168] }

[1169] The server receives this and detects that a required field is missing (no customer_id) and the quantity is incorrect (quantity is -1), which causes the server to return the following error message to the user:

[1170] json

[1171] {

[1172] "status": "error",

[1173] "message": "Required fields are missing"

[1174] }

[1175] or

[1176] json

[1177] {

[1178] "status": "error",

[1179] "message": "Invalid quantity: {'item_id': 'ITEM002', 'quantity': -1}"

[1180] }

[1181] This system automatically detects any errors in the order contents and responds quickly, thereby improving work efficiency and customer satisfaction.

[1182] The processing flow will be explained below.

[1183] Step 1:

[1184] The server receives a POST request to a dedicated endpoint and receives the order information sent by the user from the terminal as JSON format data.

[1185] Step 2:

[1186] The server parses the received request body and converts the JSON data into a dictionary-style object. Through this parsing, the entire order information is obtained as data.

[1187] Step 3:

[1188] The server checks whether all required fields, order_id, customer_id, and items, are present in the order information. If these fields are missing, the server generates and returns an error message.

[1189] Step 4:

[1190] The server checks whether the item_id and quantity are present for each item in items. If they are missing, the server generates and returns a detailed error message.

[1191] Step 5:

[1192] The server checks whether the quantity value for each item in items is greater than 0, i.e., whether it is an invalid quantity. If an invalid quantity is detected, the server generates and returns an error message indicating this.

[1193] Step 6:

[1194] If the server passes all checks, it generates a success message indicating that the order information is correct and returns it to the user.

[1195] Step 7:

[1196] The user receives the response message returned from the server, and if an error message is included, corrects the order information according to the instructions. If there are no errors, the user confirms that the order has been accepted.

[1197] Step 8:

[1198] If necessary, the user can send the corrected order information back to the server for recheck.

[1199] Example 1

[1200] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1201] The process of manually reviewing order information is time-consuming and prone to human error. This reduces the efficiency of order processing operations and risks lowering customer satisfaction. Furthermore, incomplete order information can cause delays throughout the entire process. Therefore, there is a need for a system that can automatically review order information and take appropriate action.

[1202] 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.

[1203] In this invention, the server includes means for receiving order information, means for analyzing the received order information in JSON format, means for detecting missing required items in the order information, means for detecting missing information for each item in the order information, means for detecting inappropriate quantities in the order information, means for generating an order acceptance message if there are no errors, and means for generating and returning an appropriate error message if there are errors, thereby enabling automatic inspection of order information and error handling.

[1204] "Order information" refers to information provided when a customer places an order for a product or service, and typically includes items such as order_id, customer_id, and items.

[1205] "JSON format" stands for JavaScript Object Notation, a text format for representing data in a format that is easy for humans to read and machines to parse.

[1206] A "server" is a computer system that provides various services and data in response to requests from clients over a network.

[1207] An "endpoint" is a URL or URI that a client uses to send a specific request to a server.

[1208] A "POST request" is a type of request method in the HTTP protocol, and is mainly used to send data to a server.

[1209] "Required fields" are data fields that are absolutely necessary for order information to be considered valid in the system, and in this invention include order_id, customer_id, and items.

[1210] An "item" is a product or service within an order, and is an individual data entry that includes an item_id and a quantity.

[1211] An "error message" is a message that the system displays to notify the user when it detects a defect or error.

[1212] An "order acceptance message" is a confirmation message returned from the server to the user when the order information is determined to be normal.

[1213] The present invention is described in detail below with reference to an embodiment thereof. The present system is an automatic response system for inquiries about incomplete order contents, which receives order information according to a specific procedure, automatically detects any incompleteness, and responds accordingly.

[1214] Hardware and software used

[1215] server

[1216] The server is a computer system running on a network that processes order information in response to requests from clients (user terminals). The server uses, for example, the Flask framework implemented in Python.

[1217] Terminal

[1218] A terminal is a device where a user enters order information and sends it to a server. It includes smartphones, tablets, and PCs with a web browser or mobile app installed. In the case of a web browser, order information is constructed in JSON format using JavaScript and sent to the server via an HTTP POST request.

[1219] Data processing and calculation methods

[1220] Server Operation

[1221] 1. The server sets up a dedicated endpoint and receives a POST request from the user, which contains order information in JSON format.

[1222] 2. The server parses the received JSON data and obtains it as a dictionary-style object using the Python json library.

[1223] 3. The server checks if the order_id, customer_id, and items exist in the parsed data using a Python if statement.

[1224] 4. The server checks whether the item_id and quantity exist for each item in the items list.

[1225] 5. Check that the quantity of each item is greater than or equal to 0. If the value is invalid, generate an error message.

[1226] 6. If there are no errors, a message is generated stating that the order is normal and returned to the user. If there are errors, an appropriate error message is generated and returned.

[1227] Device behavior

[1228] 1. A user enters a new order on a device, either on a web form or in a mobile app, by entering the order_id, customer_id, item_id for each item, and quantity into the appropriate fields.

[1229] 2. The terminal constructs the input order information in JSON format, for example, by using JavaScript.

[1230] 3. The device sends the constructed JSON data to the server via an HTTP POST request.

[1231] User Actions

[1232] 1. The user uses the terminal interface to enter the order_id, customer_id, item_id and quantity for each item.

[1233] 2. The user checks the entered order information and presses the send button, which sends the order information to the server.

[1234] 3. The user checks the response from the server. If the order is normal, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message.

[1235] Specific examples

[1236] Normal order case

[1237] The user types the following into a terminal and submits:

[1238] Order ID: ORD12345

[1239] Customer ID: CUST54321

[1240] Item ID: ITEM001, Quantity: 2

[1241] Item ID: ITEM002, Quantity: 5

[1242] The server receives this, performs checks at each step, and if all checks are passed, returns a message to the user indicating that the order contents are correct.

[1243] Cases of defective orders

[1244] The user types the following into a terminal and submits:

[1245] Order ID: ORD12345

[1246] Item ID: ITEM001

[1247] Item ID: ITEM002, Quantity: -1

[1248] The server receives this and detects that a required field is missing (no customer_id) and the quantity is incorrect (quantity is -1), which causes the server to return an appropriate error message to the user.

[1249] As described above, this system can automatically detect errors in order information and respond quickly, thereby improving business efficiency and customer satisfaction.

[1250] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1251] Specific explanation of processing steps

[1252] Server Processing Steps

[1253] Step 1:

[1254] The server receives a POST request from the user to a dedicated endpoint (e.g. / order), which is configured using the Flask framework. As input, it takes the order information in JSON format in the request body, and as output, it retrieves this data using request.get_json().

[1255] Step 2:

[1256] The server parses the received JSON data and converts it into a dictionary-style object. It uses the Python json library to retrieve the data as follows: order_data = request.get_json(). It receives JSON data as input and obtains dictionary-style data as output.

[1257] Step 3:

[1258] The server checks whether all required fields (order_id, customer_id, items) are present in the parsed data. It uses a Python if statement to check, for example, if 'order_id' not in order_data. It receives dictionary-format data as input and returns the result of the existence check (True / False) as output.

[1259] Step 4:

[1260] The server checks whether the item_id and quantity exist for each item in the items list. For each item, it performs a loop like "for item in order_data['items']" and checks if "item_id" not in item or if "quantity" not in item. It receives the items list as input and returns the result of the existence check (True / False) as output.

[1261] Step 5:

[1262] The server checks whether the quantity of each item is greater than or equal to 0. It checks with a condition such as if item['quantity'] < 0, and generates an error message if the value is invalid. It receives the quantity of each item as input, and returns the result (True / False) of whether it is an appropriate value as output.

[1263] Step 6:

[1264] If there are no errors, a message stating that the order is successful is generated and returned to the user. A response is generated as follows: return jsonify(status="success", message="The order is successful"). If there are errors, an appropriate error message is generated and returned. The results of each check are received as input, and a response message is generated as output.

[1265] Terminal processing steps

[1266] Step 1:

[1267] A user enters a new order on a terminal, entering the order_id, customer_id, item_id and quantity for each item into a web form or mobile app interface. As input, it takes the user's input data and as output, it holds the order information.

[1268] Step 2:

[1269] The terminal constructs the entered order information in JSON format. For example, it constructs the data using JavaScript as follows: let orderData = { "order_id": "ORD12345", "customer_id": "CUST54321", "items": [{"item_id": "ITEM001", "quantity": 2}, {"item_id": "ITEM002", "quantity": 5}]};. It receives the user's input data as input and creates JSON-formatted order information as output.

[1270] Step 3:

[1271] The terminal sends the constructed JSON data to the server via an HTTP POST request. It uses fetch or axios to send it as follows: fetch(' / order', { method: 'POST', headers: { 'Content-Type': 'application / json'}, body: JSON.stringify(orderData)});. It receives JSON-formatted order information as input and sends the data to the server as output.

[1272] Step 4:

[1273] The terminal receives the response from the server. For example, it obtains the response from the server using response.json() in JavaScript. It receives the response data from the server as input and obtains the response message as output.

[1274] Step 5:

[1275] If an error message is returned, display the item that needs to be corrected to the user. If a correct response is returned, display that the order has been accepted. As input, it takes the response from the server and as output, it creates an appropriate message to display to the user.

[1276] User processing steps

[1277] Step 1:

[1278] The user uses the terminal interface to enter the order_id, customer_id, item_id and quantity for each item, or uses text boxes and dropdowns in a web form, or enters their order information as input.

[1279] Step 2:

[1280] The user checks the order information they entered and presses the send button. This action sends the order information to the server. The order information entered on the terminal is checked as input, and the send action is executed as output.

[1281] Step 3:

[1282] The user checks the response from the server. If the order is normal, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message. The response message from the server is received as input, and the appropriate action is taken as output.

[1283] (Application example 1)

[1284] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1285] In conventional ordering systems, errors that occur when entering order information (for example, missing required fields, incorrect quantities, etc.) are a frequent problem for users. When an error occurs, it must be corrected manually, which takes time and effort. This not only reduces the efficiency of the entire ordering process and customer satisfaction, but also places a heavy burden on administrative procedures. Furthermore, delayed detection of errors can lead to delivery delays and inventory management issues. Therefore, there is a need for a system that can quickly and automatically detect errors in order information and prompt users to take immediate action.

[1286] 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.

[1287] In this invention, the server includes means for receiving order information, means for analyzing required items from the received order information, means for detecting missing required items in the order information, means for detecting missing information for each item in the order information, means for detecting inappropriate quantities in the order information, means for generating an order acceptance message if there are no errors, means for inputting order information and sending a POST request to the endpoint using a smartphone device, means for receiving a response from the server and determining the next action based on the response, and means for displaying an error message and prompting the user to correct the error. This makes it possible to quickly and automatically detect errors in the order information and provide the user with instructions to correct the error in real time.

[1288] "Order information" refers to all the information entered by a user when placing an order, and is a data set including the order_id, customer_id, and items data.

[1289] "Required fields" refer to the main information elements that are essential for order information, such as order_id, customer_id, and items.

[1290] "Means of receiving" refers to the mechanism by which data is acquired from the outside and incorporated into the system.

[1291] The "means for analyzing" is a process for analyzing the received data and extracting and shaping the necessary information elements.

[1292] "Means of detection" are mechanisms for detecting abnormalities or deficiencies based on specific conditions or rules.

[1293] "Inappropriate quantity" refers to a situation where the quantity included in the order information is inappropriate, such as when a negative number or an extremely large number is included.

[1294] An "order acceptance message" is a notification of acceptance sent after confirming that the order information is appropriate.

[1295] A "smartphone device" refers to a multi-functional mobile terminal that has the functionality of a mobile phone and is capable of various information processing functions.

[1296] An "endpoint" is a resource on a server for sending specific data and is a specific URL that receives API requests.

[1297] A "POST request" is one of the HTTP methods for sending data from a client to a server.

[1298] The "means for receiving a response" is the process of obtaining a response from the server and performing internal processing.

[1299] An "error message" is a message intended to inform the user about a detected error.

[1300] "Means to prompt corrections" refers to a mechanism that instructs the user to correct errors if they are found.

[1301] To put the present invention into practice, a system is constructed that automatically detects and promptly addresses any inaccuracies in order information, primarily using a server and a smartphone device (terminal). A specific embodiment of this system is described below.

[1302] Server Operation

[1303] The server receives, analyzes, and detects errors in order information. Specifically, it uses the following hardware and software:

[1304] Hardware: A computer for the server. Cloud-based servers are also available.

[1305] Software: Flask (lightweight web application framework), Python (programming language).

[1306] The server's role is to:

[1307] 1. Receiving method: The server sets up a dedicated endpoint to receive POST requests from users, which contain order information in JSON format.

[1308] 2. Parsing method: The server parses the JSON-formatted order information from the request body and obtains the entire order as a dictionary-format object.

[1309] 3. Method for detecting defects: Check the required items in the order information (order_id, customer_id, items) and the details of each item (item_id, quantity) to detect any defects.

[1310] 4. Response generation means: If there are no errors, a message indicating that the order is successful is generated and returned to the user. If there are errors, an appropriate error message is generated.

[1311] Terminal (smartphone) operation

[1312] The user inputs order information using a smartphone device and transmits it to the server using the following software:

[1313] Software: React Native (cross-platform framework), Axios (HTTP client).

[1314] The terminal roles are as follows:

[1315] 1. Input means: Provides an interface for users to input and submit order information via a smartphone app.

[1316] 2. Transmission method: Order information is constructed in the appropriate format (JSON format) and sent as a POST request to a dedicated endpoint on the server.

[1317] 3. Response receiving means: Receives a response from the server, and if it is normal, displays a message that the order has been accepted. If there is an error, displays an error message and prompts the user to make corrections.

[1318] User behavior

[1319] The user uses the interface on the terminal to enter order information and send it to the server, specifically:

[1320] 1. Enter order information: Enter the order_id, customer_id, item_id and quantity of each item as order information.

[1321] 2. Press the Send button: Check the order information you entered and press the Send button to send it to the server.

[1322] 3. Response review: Receive the response from the server, and if there are no errors, confirm that the order has been accepted. If there are errors, make the necessary corrections based on the error message.

[1323] Specific examples

[1324] Successful order case:

[1325] The user enters and submits the following order information:

[1326] {

[1327] "order_id": "ORD12345",

[1328] "customer_id": "CUST54321",

[1329] "items": [

[1330] {"item_id": "ITEM001", "quantity": 2},

[1331] {"item_id": "ITEM002", "quantity": 5}

[1332] ]

[1333] }

[1334] The server receives this and performs checks at each step, and if all checks pass, returns a message to the user indicating that the order is correct.

[1335] In case of an incomplete order:

[1336] The user enters and submits the following order information:

[1337] {

[1338] "order_id": "ORD12345",

[1339] "items": [

[1340] {"item_id": "ITEM001"},

[1341] {"item_id": "ITEM002", "quantity": -1}

[1342] ]

[1343] }

[1344] The server receives this and detects that a required field is missing (no customer_id) and the quantity is incorrect (quantity is -1), which causes the server to return the following error message to the user:

[1345] {

[1346] "status": "error",

[1347] "message": "Required fields are missing"

[1348] }

[1349] or

[1350] {

[1351] "status": "error",

[1352] "message": "Invalid quantity: {'item_id': 'ITEM002', 'quantity': -1}"

[1353] }

[1354] Prompt Sentence Examples

[1355] Prompt statement:

[1356] "Please input the order information including order_id, customer_id, and items with item_id and quantity. Make sure all required fields are filled and quantities are valid."

[1357] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1358] Step 1:

[1359] Input: The user inputs the order information on the smartphone device.

[1360] Specific operation: The user enters the order_id, customer_id, item_id and quantity of each item into the input fields of the smartphone app. This forms the order information.

[1361] Step 2:

[1362] Input: The user presses the submit button.

[1363] Specific operation: The entered order information is constructed in JSON format within the smartphone device.

[1364] Step 3:

[1365] Input: The smartphone device sends the constructed order information in JSON format to the server endpoint via a POST request.

[1366] Specific operation: The smartphone device sends a POST request to the specified endpoint of the server via the network. This request contains order information in JSON format.

[1367] Step 4:

[1368] Input: The server receives a POST request.

[1369] What happens: The server endpoint captures the request and extracts the JSON data from the request body.

[1370] Step 5:

[1371] Input: The server parses the received order information.

[1372] Specific operation: The server parses the extracted JSON data and obtains it as a dictionary-style object. Specifically, it separates information such as order_id, customer_id, and items.

[1373] Step 6:

[1374] Input: The server checks for missing required fields based on the analysis results.

[1375] Specific operation: The server checks whether the order_id, customer_id, and items exist in the order information it retrieves. If any required items are missing, it will proceed to the next step.

[1376] Step 7:

[1377] Input: The server checks each item for missing information.

[1378] Specific operation: The server checks whether the item_id and quantity are present for each element in the items list. If any information is missing, it proceeds to the next step.

[1379] Step 8:

[1380] Input: The server checks the quantity for validity.

[1381] Specific operation: The server checks whether the quantity of each item is greater than or equal to 0. If an invalid quantity is detected, it proceeds to the next step.

[1382] Step 9:

[1383] Input: The server determines whether there are any errors.

[1384] Specific operation: Determine whether there are any defects based on the past check results. If there are any defects, generate an error message. If there are no defects, generate an order acceptance message.

[1385] Step 10:

[1386] Input: The server sends the message back to the user.

[1387] Specific operation: The server generates a message (error or acceptance) in JSON format according to the judgment result and returns it to the smartphone device as a response.

[1388] Step 11:

[1389] Input: The device receives a response from the server.

[1390] Specific operation: The smartphone device receives the response from the server and analyzes the content.

[1391] Step 12:

[1392] Input: The device determines the next action based on the analysis results.

[1393] Specific operation: Based on the response from the server, if the order is normal, an order acceptance message is displayed; if there is an error, an error message is displayed on the screen to prompt the user to correct the error.

[1394] Example prompt sentence:

[1395] "Please input the order information including order_id, customer_id, and items with item_id and quantity. Make sure all required fields are filled and quantities are valid."

[1396] 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.

[1397] The following describes in detail the mode for carrying out the present invention. This system combines an emotion engine with an automatic response system for inquiries about incomplete order contents, receives order information according to a specific procedure, automatically detects and responds to any incompleteness, and recognizes the user's emotions and provides feedback.

[1398] Server Operation

[1399] 1. The server sets up a dedicated endpoint to receive POST requests from users, which contain order information in JSON format.

[1400] 2. The server parses the JSON-formatted order information from the request body, obtaining the entire order information as a dictionary-format object.

[1401] 3. The server checks whether all required fields (order_id, customer_id, items) are present in the parsed order information. If these fields are missing, the server generates and returns an error message.

[1402] 4. The server then checks for missing information for each item in the order information, specifically checking whether each item has an item_id and quantity.

[1403] 5. The server checks whether the quantity of each item in the order information is a valid value (usually 0 or greater), thereby detecting whether an invalid value for quantity has been entered.

[1404] 6. If any errors are detected in any of the above steps, the server generates an error message and returns it to the user. If no errors are detected, the server generates a success message indicating that the order is successful and returns it to the user.

[1405] 7. The server recognizes the user's emotions using the emotion engine, and provides appropriate feedback to the user based on the inspection result (success or error) of the order information and the emotion data.

[1406] Device behavior

[1407] 1. A user enters a new order at a terminal and sends it to the system.

[1408] 2. The terminal constructs the order information in the appropriate format (JSON format) and sends a POST request to the server's dedicated endpoint.

[1409] 3. The device receives the response from the server and decides the next action based on it. For example, if an error message is returned, it displays the items that need to be corrected to the user. It also displays feedback based on the emotion engine.

[1410] User Actions

[1411] 1. The user uses the interface on the terminal to enter order information, including the order_id, customer_id, item_id and quantity for each item.

[1412] 2. The user checks the entered order information and presses the submit button. This action sends the order information to the server.

[1413] 3. The user receives a response from the server. If the order is correct, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message.

[1414] 4. Users also receive feedback from the emotion engine. For example, when a flaw is detected, the emotion engine recognizes the user's stress or confusion and provides gentle feedback and support accordingly.

[1415] Specific examples

[1416] Normal order case

[1417] The user enters the following order information on the terminal and submits it:

[1418] json

[1419] {

[1420] "order_id": "ORD12345",

[1421] "customer_id": "CUST54321",

[1422] "items": [

[1423] {"item_id": "ITEM001", "quantity": 2},

[1424] {"item_id": "ITEM002", "quantity": 5}

[1425] ]

[1426] }

[1427] The server receives this and performs checks at each step. If all checks pass, it returns a message to the user indicating that the order is correct. The emotion engine also recognizes the user's satisfaction and provides positive feedback to that effect.

[1428] Cases of defective orders

[1429] The user enters the following order information on the terminal and submits it:

[1430] json

[1431] {

[1432] "order_id": "ORD12345",

[1433] "items": [

[1434] {"item_id": "ITEM001"},

[1435] {"item_id": "ITEM002", "quantity": -1}

[1436] ]

[1437] }

[1438] The server receives this and detects that a required field is missing (no customer_id) and the quantity is incorrect (quantity is -1), which causes the server to return the following error message to the user:

[1439] json

[1440] {

[1441] "status": "error",

[1442] "message": "Required fields are missing"

[1443] }

[1444] or

[1445] json

[1446] {

[1447] "status": "error",

[1448] "message": "Invalid quantity: {'item_id': 'ITEM002', 'quantity': -1}"

[1449] }

[1450] Additionally, the emotion engine recognizes when a user is confused or stressed and offers corresponding supportive or encouraging messages:

[1451] json

[1452] {

[1453] "status": "error",

[1454] "message": "Invalid quantity: {'item_id': 'ITEM002', 'quantity': -1}",

[1455] "emotion_feedback": "We're sorry you encountered an issue. Please enter the required information and try again."

[1456] }

[1457] This system automatically detects errors in order details and responds quickly, thereby improving operational efficiency and customer satisfaction. In addition, the introduction of an emotion engine improves the user experience and helps build good relationships with customers.

[1458] The processing flow will be explained below.

[1459] Step 1:

[1460] The server receives a POST request to a dedicated endpoint and receives the order information sent by the user from the terminal as JSON format data.

[1461] Step 2:

[1462] The server parses the received request body and converts the JSON data into a dictionary-style object. Through this parsing, the entire order information is obtained as data.

[1463] Step 3:

[1464] The server checks whether all required items (order_id, customer_id, and items) are present in the order information. If these items are missing, the server generates and returns an error message.

[1465] Step 4:

[1466] The server checks whether the item_id and quantity are present for each item in items. If they are missing, the server generates and returns a detailed error message.

[1467] Step 5:

[1468] The server checks whether the quantity value for each item in items is greater than 0, i.e., whether it is an invalid quantity. If an invalid quantity is detected, the server generates and returns an error message indicating this.

[1469] Step 6:

[1470] The server generates an error or success message based on the result of detecting the order information and returns it to the user. If there are no errors, it generates a success message indicating that the order is normal.

[1471] Step 7:

[1472] The server uses an emotion engine to recognize the user's emotions in real time, and provides appropriate feedback to the user based on the inspection result (success or error) of the order information and the emotion data.

[1473] Step 8:

[1474] The device receives the response from the server and decides the next action based on it. For example, if an error message is returned, it will display the items that need to be corrected to the user and also display feedback from the emotion engine.

[1475] Step 9:

[1476] The user receives the response message returned from the server, and if an error message is included, corrects the order information according to the instructions. If there are no errors, the user confirms that the order has been accepted.

[1477] Step 10:

[1478] If necessary, the user can resubmit the revised order information to the server for rechecking, and receive feedback from the emotion engine again.

[1479] Example 2

[1480] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1481] Conventional order processing systems have had the problem of requiring a lot of time and effort to detect errors in order information. Furthermore, when a user submits an order with errors, the system provides little feedback, which hinders the user experience. In particular, the lack of appropriate feedback and support for orders with errors was a factor that led to a decline in user satisfaction.

[1482] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for receiving order information, a means for analyzing required items from the received order information, a means for detecting whether required items are missing from the order information, a means for detecting whether information on each item is missing from the order information, a means for detecting inappropriate quantities in the order information, a means for generating an order acceptance message if there are no deficiencies, a means for detecting an emotional state, and a means for generating feedback based on the emotional state. This makes it possible to quickly and automatically detect deficiencies in the order content and provide appropriate feedback that also takes the user's emotions into consideration.

[1483] "Order Information" means data entered by a user when placing an order, including an identifier, customer identifier, item list, and other related information.

[1484] "Required items" are particularly important elements of the order information, and include an identifier, a customer identifier, and an item list.

[1485] An "identifier" is information that uniquely identifies a particular order, and typically refers to an order number or ID.

[1486] "Customer identifier" refers to information that uniquely identifies the customer who placed the order, such as customer ID or account information.

[1487] An "item list" is data that lists information about each item included in an order.

[1488] An "item identifier" is information that uniquely identifies each item in an item list, and typically refers to the product ID.

[1489] "Quantity" is information indicating the number of items ordered, and is usually expressed as an integer value.

[1490] "Emotional state" refers to the type and intensity of emotions a user experiences when placing an order and receiving feedback about it.

[1491] "Feedback" refers to response messages that return information to the user about the status or deficiencies of an order, including additional support messages based on emotional state.

[1492] "Analysis" refers to the process of deciphering received data and extracting necessary information.

[1493] "Detection" refers to the process of finding items or deficiencies that meet specific conditions.

[1494] "Generation" refers to the process of creating new data or messages.

[1495] "Reception" refers to the process of taking in data from outside.

[1496] The following describes in detail the mode for carrying out the present invention. This system combines an emotion engine with an automatic response system for inquiries about order defects. It receives order information according to a specific procedure, automatically detects and responds to any defects, and recognizes the user's emotions and provides feedback. The system consists of three main elements: a server, a terminal, and a user.

[1497] Server Operation

[1498] 1. The server sets up a dedicated endpoint to receive POST requests from users, which contain order information in JSON format.

[1499] 2. The server parses the JSON-formatted order information from the request body, extracting the entire order information as a dictionary-format object.

[1500] 3. The server checks whether all required items (identifier, customer identifier, item list) are present in the parsed order information. If these items are missing, the server generates and returns an error message.

[1501] 4. The server then checks for missing information for each item in the order information, specifically checking whether each item has an item identifier and quantity.

[1502] 5. The server checks whether the quantity of each item in the order information is a valid value (usually 0 or greater), thereby detecting whether an invalid value for quantity has been entered.

[1503] 6. If any errors are detected in any of the above steps, the server generates an error message and returns it to the user. If no errors are detected, the server generates a success message indicating that the order is successful and returns it to the user.

[1504] 7. The server recognizes the user's emotions using the emotion engine, and provides appropriate feedback to the user based on the inspection result (success or error) of the order information and the emotion data.

[1505] Device behavior

[1506] 1. A user enters a new order at a terminal and sends it to the system.

[1507] 2. The terminal constructs the order information in the appropriate format (JSON format) and sends a POST request to the server's dedicated endpoint.

[1508] 3. The device receives the response from the server and decides the next action based on it. For example, if an error message is returned, it displays the items that need to be corrected to the user. It also displays feedback based on the emotion engine.

[1509] User Actions

[1510] 1. The user uses the interface on the terminal to enter order information, including the identifier, customer identifier, item identifier and quantity for each item.

[1511] 2. The user checks the entered order information and presses the submit button. This action sends the order information to the server.

[1512] 3. The user receives a response from the server. If the order is successful, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message.

[1513] 4. Users also receive feedback from the emotion engine. For example, when a flaw is detected, the emotion engine recognizes the user's stress or confusion and provides gentle feedback and support accordingly.

[1514] Specific examples

[1515] Normal order case

[1516] A user enters the following order information on the terminal and submits it:

[1517] Prompt statement:

[1518] Order ID: ORD12345

[1519] Customer ID: CUST54321

[1520] item:

[1521] Item ID: ITEM001, Quantity: 2

[1522] Item ID: ITEM002, Quantity: 5

[1523] The server receives this and performs checks at each step. If all checks pass, it returns a message to the user indicating that the order is correct. The emotion engine also recognizes the user's satisfaction and provides positive feedback to that effect.

[1524] Cases of defective orders

[1525] A user enters the following order information on the terminal and submits it:

[1526] Prompt statement:

[1527] Order ID: ORD12345

[1528] item:

[1529] Item ID: ITEM001

[1530] Item ID: ITEM002, Quantity: -1

[1531] The server receives this and detects that a required field is missing (no customer ID) and the quantity is incorrect (quantity is -1), which causes the server to return the following error message to the user:

[1532] "Required items are missing"

[1533] or

[1534] "Invalid quantity: Item ID: ITEM002, Quantity: -1"

[1535] Additionally, the emotion engine recognizes when a user is confused or stressed and offers corresponding supportive or encouraging messages:

[1536] "Sorry for the problem. Please enter the required information and try again."

[1537] This system automatically detects errors in order details and responds quickly, thereby improving operational efficiency and customer satisfaction. In addition, the introduction of an emotion engine improves the user experience and helps build good relationships with customers.

[1538] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1539] Server Operation

[1540] Step 1:

[1541] The server has a dedicated endpoint that receives POST requests from users, which contain order information in JSON format. The input is JSON data as a POST request, and the output is a parseable JSON object.

[1542] Step 2:

[1543] The server parses the JSON order information from the request body. This parses the entire order information as a dictionary object. The input is the received JSON data, and the output is a dictionary object.

[1544] Step 3:

[1545] The server checks whether all required items (identifier, customer identifier, item list) are present in the parsed order information. If these items are missing, the server generates and returns an error message. The input is a dictionary object, and the output is a Boolean value of the check result and an error message.

[1546] Step 4:

[1547] The server checks whether the item identifier and quantity are present for each item in the order information. If they are missing, the server generates an error message for that item. The input is a dictionary object, and the output is a Boolean result of the check and an error message.

[1548] Step 5:

[1549] The server checks whether the quantity of each item in the order information is a valid value (usually 0 or greater). If the quantity is invalid, the server generates an error message. The input is a dictionary object, and the output is a Boolean value of the check result and an error message.

[1550] Step 6:

[1551] If any errors are detected at any of the above steps, the server generates an error message and returns it to the user. If no errors are found, it generates a success message stating that the order is normal and returns it to the user. The input is the check result at each step, and the output is an error message or a success message.

[1552] Step 7:

[1553] The server uses an emotion engine to recognize the user's emotion. Based on the inspection result (success or error) of the order information and the emotion data, it provides appropriate feedback to the user. The input is the inspection result and user interaction data, and the output is a feedback message based on the emotion.

[1554] Device behavior

[1555] Step 1:

[1556] A user enters a new order on a terminal and sends it to the system. The input is the data the user entered into the interface, and the output is the constructed order information in JSON format.

[1557] Step 2:

[1558] The terminal constructs the order information in the appropriate format (JSON format) and sends a POST request to a dedicated endpoint on the server. The input is the data entered by the user, and the output is the JSON data sent to the server.

[1559] Step 3:

[1560] The device receives the response from the server and determines the next action based on that. For example, if an error message is returned, it displays the items that need to be corrected to the user. It also displays feedback from the emotion engine. The input is the response message from the server, and the output is the feedback message displayed to the user.

[1561] User Actions

[1562] Step 1:

[1563] The user uses the interface on the terminal to enter order information, including an identifier, a customer identifier, an item identifier and a quantity for each item. The input is the data entered by the user into the interface, and the output is confirmation of the input fields displayed on the terminal.

[1564] Step 2:

[1565] The user confirms the entered order information and presses the send button. This action sends the order information to the server. The input is the confirmed order information, and the output is a trigger for sending to the server.

[1566] Step 3:

[1567] The user receives a response from the server. If the order is normal, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message. The input is the response message from the server, and the output is the action to correct or confirm the order.

[1568] Step 4:

[1569] The user also receives feedback from the emotion engine. For example, when a flaw is detected, the emotion engine recognizes the user's stress or confusion and provides gentle feedback and support accordingly. The input is the feedback message from the emotion engine, and the output is the user's next action (correction or resubmission).

[1570] (Application example 2)

[1571] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1572] While conventional order management systems can detect errors in order information, they have the problem of not being able to properly manage the user's feelings and provide feedback. As a result, when users feel stressed or confused, they are unable to respond quickly and appropriately, which can lead to a poor user experience. Furthermore, there is a demand for smartphone applications that allow users to easily enter appropriate order information and receive immediate feedback.

[1573] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving order information, means for analyzing required items from the received order information, means for detecting whether required items in the order information are missing, means for detecting whether information on each item in the order information is missing, means for detecting inappropriate quantities in the order information, means for generating an order acceptance message if there are no defects, means for recognizing the user's emotions, and means for providing feedback based on the user's emotions. This makes it possible to quickly detect defects in the order content and provide appropriate feedback based on the user's emotions.

[1574] "Order information" refers to detailed order information entered by a user when purchasing a product or service.

[1575] "Required items" are important data items that are indispensable within the order information, and examples include order_id, customer_id, and items.

[1576] "Quantity" is a numerical value that indicates the number of each item in the order information.

[1577] An "emotion engine" is a system that recognizes and analyzes emotions from the text, voice, facial expressions, etc. entered by the user.

[1578] "Feedback" refers to the reply or response that a system provides to a user, particularly one that is appropriate in response to the user's emotions.

[1579] A "server" is a computer system that receives requests from clients and returns responses to those requests.

[1580] An "order acceptance message" is a message sent to a user when the order information is normal, informing the user that the order has been accepted.

[1581] An "incomplete" is when required data or information is missing or incorrect in the order information.

[1582] "Means for analysis" refers to systems or software that have the function of breaking down and analyzing the received data and extracting the necessary information.

[1583] "Means of detection" are systems or software that have the functionality to find missing information or inappropriate values.

[1584] A "means for providing feedback" is a system or software that has the functionality to generate and provide an appropriate reply or response based on the user's emotions and the status of the order information.

[1585] The following is a detailed description of an embodiment of the present invention. This system combines an automatic response system for inquiries about incomplete order contents with an emotion engine, and the server, terminal, and user each play their role according to a specific procedure.

[1586] The server sets up a dedicated endpoint and receives POST requests from users. This request contains order information in JSON format. The server parses the JSON-formatted order information from the request body and obtains it as a dictionary-format object. Next, it checks whether all required fields (order_id, customer_id, items) are present in the order information, and if any are missing, it generates and returns an error message. It also checks the item_id and quantity for each item to ensure that the quantity is an appropriate value (0 or greater). This detects whether an invalid value for the quantity has been entered. If there are no errors, it generates a success message stating that the order is normal and returns it to the user.

[1587] The server then uses an emotion engine to recognize the user's emotions. It is recommended to use an external service (e.g., Hume AI) for this emotion recognition. The emotion engine analyzes the user's input text to detect emotions such as stress or confusion. To provide feedback based on the detected emotion, the server generates an appropriate support message along with a success or error message.

[1588] The terminal helps the user enter a new order and submit it to the system. The order is constructed in the appropriate format (JSON) and a POST request is sent to a dedicated endpoint on the server. When a response is received from the server, it determines the next action to take. If an error message is returned, it displays the items that need to be corrected to the user, as well as feedback from the emotion engine.

[1589] The user inputs order information using the interface on the terminal, confirms it, and then submits it. The submitted data is checked by the server, and if the order is correct, the user receives a confirmation message, or if there is a problem, an error message and emotional feedback.

[1590] As a concrete example, consider the case of a successful order. Consider the case where a user enters the following order information on a terminal and submits it:

[1591] {

[1592] "order_id": "ORD12345",

[1593] "customer_id": "CUST54321",

[1594] "items": [

[1595] {"item_id": "ITEM001", "quantity": 2},

[1596] {"item_id": "ITEM002", "quantity": 5}

[1597] ]

[1598] }

[1599] The server receives this and checks each step. If all checks pass, it returns a message to the user indicating that the order is correct. The emotion engine also recognizes the user's satisfaction and provides positive feedback.

[1600] Also, consider the following example of an incomplete order:

[1601] {

[1602] "order_id": "ORD12345",

[1603] "items": [

[1604] {"item_id": "ITEM001"},

[1605] {"item_id": "ITEM002", "quantity": -1}

[1606] ]

[1607] }

[1608] The server receives this and detects the lack of required fields (no customer_id) and the inappropriate quantity (quantity is -1). Along with the error message, the server's emotion engine recognizes the user's confusion and stress and provides a corresponding support message.

[1609] Examples of prompts for a generative AI model might include:

[1610] Detect the order information entered by the user and display an error message for any incomplete items. Also, use a sentiment engine to analyze the user's sentiment and display appropriate feedback. The order information is as follows:

[1611] {

[1612] "order_id": "ORD67890",

[1613] "customer_id": "CUST12345",

[1614] "items": [

[1615] {"item_id": "ITEM123", "quantity": 1}

[1616] ],

[1617] "user_message": "I'm having trouble placing my order."

[1618] }

[1619] This system automatically detects errors in order details and responds quickly, improving operational efficiency and customer satisfaction. In addition, the introduction of an emotion engine improves the user experience and helps build good relationships with customers.

[1620] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1621] Step 1:

[1622] The user enters order information on the terminal. Specifically, the user uses a dedicated interface to enter the order_id, customer_id, and item_id and quantity of each item, and then presses the submit button. This creates the order information in JSON format.

[1623] Input: order_id, customer_id, item_id, quantity

[1624] Output: Order information in JSON format

[1625] Step 2:

[1626] The terminal sends the constructed JSON-formatted order information to the server. Specifically, the terminal sends a POST request to a dedicated endpoint on the server, with the order information included in the request body.

[1627] Input: Order information in JSON format

[1628] Output: POST request

[1629] Step 3:

[1630] The server receives the POST request sent from the terminal. Specifically, it receives the request at a dedicated endpoint, extracts the order information from the request body, and parses it into a dictionary-style object.

[1631] Input: POST request

[1632] Output: Order information in dictionary format

[1633] Step 4:

[1634] The server checks whether all required fields (order_id, customer_id, items) are present in the received order information. If any fields are missing, it generates and returns an error message.

[1635] Input: Order information in dictionary format

[1636] Output: Error message or proceed to next step

[1637] Step 5:

[1638] The server checks whether each item in the order information has an item_id and quantity. If the information is insufficient, it generates and returns an error message. It also checks whether the quantity is valid and returns an error message if it is inappropriate.

[1639] Input: Order information in dictionary format

[1640] Output: Error message or proceed to next step

[1641] Step 6:

[1642] If all checks are passed, the server generates a success message indicating that the order contents are correct and returns it to the user.

[1643] Input: Order information in dictionary format

[1644] Output: Success message

[1645] Step 7:

[1646] The server uses an emotion engine to recognize the user's emotions. Specifically, it sends message data from the user to an emotion recognition library (e.g., Hume AI) to obtain emotion data.

[1647] Input: User's message data

[1648] Output: Emotion data

[1649] Step 8:

[1650] The server generates appropriate feedback based on the emotion data. For example, it generates a supportive message if the user is confused, or positive feedback if the user is satisfied. This feedback is polite and sensitive to the user's emotions.

[1651] Input: Emotion data

[1652] Output: Feedback message

[1653] Step 9:

[1654] The user receives a response from the server on their terminal, and if the response is a success message, they know that their order has been accepted, or if there are any issues, they see an error message and emotion-based feedback.

[1655] Input: Response message from the server

[1656] Output: Messages to be displayed (success message, error message, feedback message)

[1657] This series of steps realizes a system that can automatically detect incomplete order information and provide feedback that is sensitive to the user's emotions.

[1658] 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.

[1659] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1660] 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.

[1661] [Fourth embodiment]

[1662] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1663] 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.

[1664] 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).

[1665] 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.

[1666] 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.

[1667] 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).

[1668] 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.

[1669] 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.

[1670] 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.

[1671] 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.

[1672] 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.

[1673] 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.

[1674] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1675] The present invention is described in detail below with reference to an embodiment thereof. The present system is an automatic response system for inquiries about incomplete order contents, which receives order information according to a specific procedure, automatically detects any incompleteness, and responds accordingly.

[1676] Server Operation

[1677] 1. The server sets up a dedicated endpoint to receive POST requests from users, which contain order information in JSON format.

[1678] 2. The server parses the JSON order information from the request body, which returns the entire order as a dictionary object.

[1679] 3. The server checks whether all required fields (order_id, customer_id, items) are present in the parsed order information, thereby detecting the basic defect.

[1680] 4. The server then checks for missing information for each item in the order information, specifically checking whether each item has an item_id and quantity.

[1681] 5. The server checks whether the quantity of each item is a valid value (usually 0 or greater), which detects whether an invalid value for quantity has been entered.

[1682] 6. If any of these checks fail, the server generates an appropriate error message and returns it to the user. If there are no errors, the server generates a message stating that the order is successful and returns it to the user.

[1683] Device behavior

[1684] 1. A user enters a new order at a terminal and sends it to the system.

[1685] 2. The terminal constructs the order information in the appropriate format (JSON format) and sends a POST request to the server's dedicated endpoint.

[1686] 3. The device receives the response from the server and decides the next action based on it. For example, if an error message is returned, it displays the items that need to be corrected to the user.

[1687] User Actions

[1688] 1. The user uses the interface on the terminal to enter order information, including the order_id, customer_id, item_id and quantity for each item.

[1689] 2. The user checks the entered order information and presses the submit button. This action sends the order information to the server.

[1690] 3. The user receives a response from the server. If the order is correct, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message.

[1691] Specific examples

[1692] Normal order case

[1693] The user enters the following order information on the terminal and submits it:

[1694] json

[1695] {

[1696] "order_id": "ORD12345",

[1697] "customer_id": "CUST54321",

[1698] "items": [

[1699] {"item_id": "ITEM001", "quantity": 2},

[1700] {"item_id": "ITEM002", "quantity": 5}

[1701] ]

[1702] }

[1703] The server receives this and performs checks at each step. If all checks pass, it returns a message to the user indicating that the order is correct.

[1704] Cases of defective orders

[1705] The user enters the following order information on the terminal and submits it:

[1706] json

[1707] {

[1708] "order_id": "ORD12345",

[1709] "items": [

[1710] {"item_id": "ITEM001"},

[1711] {"item_id": "ITEM002", "quantity": -1}

[1712] ]

[1713] }

[1714] The server receives this and detects that a required field is missing (no customer_id) and the quantity is incorrect (quantity is -1), which causes the server to return the following error message to the user:

[1715] json

[1716] {

[1717] "status": "error",

[1718] "message": "Required fields are missing"

[1719] }

[1720] or

[1721] json

[1722] {

[1723] "status": "error",

[1724] "message": "Invalid quantity: {'item_id': 'ITEM002', 'quantity': -1}"

[1725] }

[1726] This system automatically detects any errors in the order contents and responds quickly, thereby improving work efficiency and customer satisfaction.

[1727] The processing flow will be explained below.

[1728] Step 1:

[1729] The server receives a POST request to a dedicated endpoint and receives the order information sent by the user from the terminal as JSON format data.

[1730] Step 2:

[1731] The server parses the received request body and converts the JSON data into a dictionary-style object. Through this parsing, the entire order information is obtained as data.

[1732] Step 3:

[1733] The server checks whether all required fields, order_id, customer_id, and items, are present in the order information. If these fields are missing, the server generates and returns an error message.

[1734] Step 4:

[1735] The server checks whether the item_id and quantity are present for each item in items. If they are missing, the server generates and returns a detailed error message.

[1736] Step 5:

[1737] The server checks whether the quantity value for each item in items is greater than 0, i.e., whether it is an invalid quantity. If an invalid quantity is detected, the server generates and returns an error message indicating this.

[1738] Step 6:

[1739] If the server passes all checks, it generates a success message indicating that the order information is correct and returns it to the user.

[1740] Step 7:

[1741] The user receives the response message returned from the server, and if an error message is included, corrects the order information according to the instructions. If there are no errors, the user confirms that the order has been accepted.

[1742] Step 8:

[1743] If necessary, the user can send the corrected order information back to the server for recheck.

[1744] Example 1

[1745] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1746] The process of manually reviewing order information is time-consuming and prone to human error. This reduces the efficiency of order processing operations and risks lowering customer satisfaction. Furthermore, incomplete order information can cause delays throughout the entire process. Therefore, there is a need for a system that can automatically review order information and take appropriate action.

[1747] 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.

[1748] In this invention, the server includes means for receiving order information, means for analyzing the received order information in JSON format, means for detecting missing required items in the order information, means for detecting missing information for each item in the order information, means for detecting inappropriate quantities in the order information, means for generating an order acceptance message if there are no errors, and means for generating and returning an appropriate error message if there are errors, thereby enabling automatic inspection of order information and error handling.

[1749] "Order information" refers to information provided when a customer places an order for a product or service, and typically includes items such as order_id, customer_id, and items.

[1750] "JSON format" stands for JavaScript Object Notation, a text format for representing data in a format that is easy for humans to read and machines to parse.

[1751] A "server" is a computer system that provides various services and data in response to requests from clients over a network.

[1752] An "endpoint" is a URL or URI that a client uses to send a specific request to a server.

[1753] A "POST request" is a type of request method in the HTTP protocol, and is mainly used to send data to a server.

[1754] "Required fields" are data fields that are absolutely necessary for order information to be considered valid in the system, and in this invention include order_id, customer_id, and items.

[1755] An "item" is a product or service within an order, and is an individual data entry that includes an item_id and a quantity.

[1756] An "error message" is a message that the system displays to notify the user when it detects a defect or error.

[1757] An "order acceptance message" is a confirmation message returned from the server to the user when the order information is determined to be normal.

[1758] The present invention is described in detail below with reference to an embodiment thereof. The present system is an automatic response system for inquiries about incomplete order contents, which receives order information according to a specific procedure, automatically detects any incompleteness, and responds accordingly.

[1759] Hardware and software used

[1760] server

[1761] The server is a computer system running on a network that processes order information in response to requests from clients (user terminals). The server uses, for example, the Flask framework implemented in Python.

[1762] Terminal

[1763] A terminal is a device where a user enters order information and sends it to a server. It includes smartphones, tablets, and PCs with a web browser or mobile app installed. In the case of a web browser, order information is constructed in JSON format using JavaScript and sent to the server via an HTTP POST request.

[1764] Data processing and calculation methods

[1765] Server Operation

[1766] 1. The server sets up a dedicated endpoint and receives a POST request from the user, which contains order information in JSON format.

[1767] 2. The server parses the received JSON data and obtains it as a dictionary-style object using the Python json library.

[1768] 3. The server checks if the order_id, customer_id, and items exist in the parsed data using a Python if statement.

[1769] 4. The server checks whether the item_id and quantity exist for each item in the items list.

[1770] 5. Check that the quantity of each item is greater than or equal to 0. If the value is invalid, generate an error message.

[1771] 6. If there are no errors, a message is generated stating that the order is normal and returned to the user. If there are errors, an appropriate error message is generated and returned.

[1772] Device behavior

[1773] 1. A user enters a new order on a device, either on a web form or in a mobile app, by entering the order_id, customer_id, item_id for each item, and quantity into the appropriate fields.

[1774] 2. The terminal constructs the input order information in JSON format, for example, by using JavaScript.

[1775] 3. The device sends the constructed JSON data to the server via an HTTP POST request.

[1776] User Actions

[1777] 1. The user uses the terminal interface to enter the order_id, customer_id, item_id and quantity for each item.

[1778] 2. The user checks the entered order information and presses the send button, which sends the order information to the server.

[1779] 3. The user checks the response from the server. If the order is normal, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message.

[1780] Specific examples

[1781] Normal order case

[1782] The user types the following into a terminal and submits:

[1783] Order ID: ORD12345

[1784] Customer ID: CUST54321

[1785] Item ID: ITEM001, Quantity: 2

[1786] Item ID: ITEM002, Quantity: 5

[1787] The server receives this, performs checks at each step, and if all checks are passed, returns a message to the user indicating that the order contents are correct.

[1788] Cases of defective orders

[1789] The user types the following into a terminal and submits:

[1790] Order ID: ORD12345

[1791] Item ID: ITEM001

[1792] Item ID: ITEM002, Quantity: -1

[1793] The server receives this and detects that a required field is missing (no customer_id) and the quantity is incorrect (quantity is -1), which causes the server to return an appropriate error message to the user.

[1794] As described above, this system can automatically detect errors in order information and respond quickly, thereby improving business efficiency and customer satisfaction.

[1795] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1796] Specific explanation of processing steps

[1797] Server Processing Steps

[1798] Step 1:

[1799] The server receives a POST request from the user to a dedicated endpoint (e.g. / order), which is configured using the Flask framework. As input, it takes the order information in JSON format in the request body, and as output, it retrieves this data using request.get_json().

[1800] Step 2:

[1801] The server parses the received JSON data and converts it into a dictionary-style object. It uses the Python json library to retrieve the data as follows: order_data = request.get_json(). It receives JSON data as input and obtains dictionary-style data as output.

[1802] Step 3:

[1803] The server checks whether all required fields (order_id, customer_id, items) are present in the parsed data. It uses a Python if statement to check, for example, if 'order_id' not in order_data. It receives dictionary-format data as input and returns the result of the existence check (True / False) as output.

[1804] Step 4:

[1805] The server checks whether the item_id and quantity exist for each item in the items list. For each item, it performs a loop like "for item in order_data['items']" and checks if "item_id" not in item or if "quantity" not in item. It receives the items list as input and returns the result of the existence check (True / False) as output.

[1806] Step 5:

[1807] The server checks whether the quantity of each item is greater than or equal to 0. It checks with a condition such as if item['quantity'] < 0, and generates an error message if the value is invalid. It receives the quantity of each item as input, and returns the result (True / False) of whether it is an appropriate value as output.

[1808] Step 6:

[1809] If there are no errors, a message stating that the order is successful is generated and returned to the user. A response is generated as follows: return jsonify(status="success", message="The order is successful"). If there are errors, an appropriate error message is generated and returned. The results of each check are received as input, and a response message is generated as output.

[1810] Terminal processing steps

[1811] Step 1:

[1812] A user enters a new order on a terminal, entering the order_id, customer_id, item_id and quantity for each item into a web form or mobile app interface. As input, it takes the user's input data and as output, it holds the order information.

[1813] Step 2:

[1814] The terminal constructs the entered order information in JSON format. For example, it constructs the data using JavaScript as follows: let orderData = { "order_id": "ORD12345", "customer_id": "CUST54321", "items": [{"item_id": "ITEM001", "quantity": 2}, {"item_id": "ITEM002", "quantity": 5}]};. It receives the user's input data as input and creates JSON-formatted order information as output.

[1815] Step 3:

[1816] The terminal sends the constructed JSON data to the server via an HTTP POST request. It uses fetch or axios to send it as follows: fetch(' / order', { method: 'POST', headers: { 'Content-Type': 'application / json'}, body: JSON.stringify(orderData)});. It receives JSON-formatted order information as input and sends the data to the server as output.

[1817] Step 4:

[1818] The terminal receives the response from the server. For example, it obtains the response from the server using response.json() in JavaScript. It receives the response data from the server as input and obtains the response message as output.

[1819] Step 5:

[1820] If an error message is returned, display the item that needs to be corrected to the user. If a correct response is returned, display that the order has been accepted. As input, it takes the response from the server and as output, it creates an appropriate message to display to the user.

[1821] User processing steps

[1822] Step 1:

[1823] The user uses the terminal interface to enter the order_id, customer_id, item_id and quantity for each item, or uses text boxes and dropdowns in a web form, or enters their order information as input.

[1824] Step 2:

[1825] The user checks the order information they entered and presses the send button. This action sends the order information to the server. The order information entered on the terminal is checked as input, and the send action is executed as output.

[1826] Step 3:

[1827] The user checks the response from the server. If the order is normal, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message. The response message from the server is received as input, and the appropriate action is taken as output.

[1828] (Application example 1)

[1829] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1830] In conventional ordering systems, errors that occur when entering order information (for example, missing required fields, incorrect quantities, etc.) are a frequent problem for users. When an error occurs, it must be corrected manually, which takes time and effort. This not only reduces the efficiency of the entire ordering process and customer satisfaction, but also places a heavy burden on administrative procedures. Furthermore, delayed detection of errors can lead to delivery delays and inventory management issues. Therefore, there is a need for a system that can quickly and automatically detect errors in order information and prompt users to take immediate action.

[1831] 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.

[1832] In this invention, the server includes means for receiving order information, means for analyzing required items from the received order information, means for detecting missing required items in the order information, means for detecting missing information for each item in the order information, means for detecting inappropriate quantities in the order information, means for generating an order acceptance message if there are no errors, means for inputting order information and sending a POST request to the endpoint using a smartphone device, means for receiving a response from the server and determining the next action based on the response, and means for displaying an error message and prompting the user to correct the error. This makes it possible to quickly and automatically detect errors in the order information and provide the user with instructions to correct the error in real time.

[1833] "Order information" refers to all the information entered by a user when placing an order, and is a data set including the order_id, customer_id, and items data.

[1834] "Required fields" refer to the main information elements that are essential for order information, such as order_id, customer_id, and items.

[1835] "Means of receiving" refers to the mechanism by which data is acquired from the outside and incorporated into the system.

[1836] The "means for analyzing" is a process for analyzing the received data and extracting and shaping the necessary information elements.

[1837] "Means of detection" are mechanisms for detecting abnormalities or deficiencies based on specific conditions or rules.

[1838] "Inappropriate quantity" refers to a situation where the quantity included in the order information is inappropriate, such as when a negative number or an extremely large number is included.

[1839] An "order acceptance message" is a notification of acceptance sent after confirming that the order information is appropriate.

[1840] A "smartphone device" refers to a multi-functional mobile terminal that has the functionality of a mobile phone and is capable of various information processing functions.

[1841] An "endpoint" is a resource on a server for sending specific data and is a specific URL that receives API requests.

[1842] A "POST request" is one of the HTTP methods for sending data from a client to a server.

[1843] The "means for receiving a response" is the process of obtaining a response from the server and performing internal processing.

[1844] An "error message" is a message intended to inform the user about a detected error.

[1845] "Means to prompt corrections" refers to a mechanism that instructs the user to correct errors if they are found.

[1846] To put the present invention into practice, a system is constructed that automatically detects and promptly addresses any inaccuracies in order information, primarily using a server and a smartphone device (terminal). A specific embodiment of this system is described below.

[1847] Server Operation

[1848] The server receives, analyzes, and detects errors in order information. Specifically, it uses the following hardware and software:

[1849] Hardware: A computer for the server. Cloud-based servers are also available.

[1850] Software: Flask (lightweight web application framework), Python (programming language).

[1851] The server's role is to:

[1852] 1. Receiving method: The server sets up a dedicated endpoint to receive POST requests from users, which contain order information in JSON format.

[1853] 2. Parsing method: The server parses the JSON-formatted order information from the request body and obtains the entire order as a dictionary-format object.

[1854] 3. Method for detecting defects: Check the required items in the order information (order_id, customer_id, items) and the details of each item (item_id, quantity) to detect any defects.

[1855] 4. Response generation means: If there are no errors, a message indicating that the order is successful is generated and returned to the user. If there are errors, an appropriate error message is generated.

[1856] Terminal (smartphone) operation

[1857] The user inputs order information using a smartphone device and transmits it to the server using the following software:

[1858] Software: React Native (cross-platform framework), Axios (HTTP client).

[1859] The terminal roles are as follows:

[1860] 1. Input means: Provides an interface for users to input and submit order information via a smartphone app.

[1861] 2. Transmission method: Order information is constructed in the appropriate format (JSON format) and sent as a POST request to a dedicated endpoint on the server.

[1862] 3. Response receiving means: Receives a response from the server, and if it is normal, displays a message that the order has been accepted. If there is an error, displays an error message and prompts the user to make corrections.

[1863] User behavior

[1864] The user uses the interface on the terminal to enter order information and send it to the server, specifically:

[1865] 1. Enter order information: Enter the order_id, customer_id, item_id and quantity of each item as order information.

[1866] 2. Press the Send button: Check the order information you entered and press the Send button to send it to the server.

[1867] 3. Response review: Receive the response from the server, and if there are no errors, confirm that the order has been accepted. If there are errors, make the necessary corrections based on the error message.

[1868] Specific examples

[1869] Successful order case:

[1870] The user enters and submits the following order information:

[1871] {

[1872] "order_id": "ORD12345",

[1873] "customer_id": "CUST54321",

[1874] "items": [

[1875] {"item_id": "ITEM001", "quantity": 2},

[1876] {"item_id": "ITEM002", "quantity": 5}

[1877] ]

[1878] }

[1879] The server receives this and performs checks at each step, and if all checks pass, returns a message to the user indicating that the order is correct.

[1880] In case of an incomplete order:

[1881] The user enters and submits the following order information:

[1882] {

[1883] "order_id": "ORD12345",

[1884] "items": [

[1885] {"item_id": "ITEM001"},

[1886] {"item_id": "ITEM002", "quantity": -1}

[1887] ]

[1888] }

[1889] The server receives this and detects that a required field is missing (no customer_id) and the quantity is incorrect (quantity is -1), which causes the server to return the following error message to the user:

[1890] {

[1891] "status": "error",

[1892] "message": "Required fields are missing"

[1893] }

[1894] or

[1895] {

[1896] "status": "error",

[1897] "message": "Invalid quantity: {'item_id': 'ITEM002', 'quantity': -1}"

[1898] }

[1899] Prompt Sentence Examples

[1900] Prompt statement:

[1901] "Please input the order information including order_id, customer_id, and items with item_id and quantity. Make sure all required fields are filled and quantities are valid."

[1902] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1903] Step 1:

[1904] Input: The user inputs the order information on the smartphone device.

[1905] Specific operation: The user enters the order_id, customer_id, item_id and quantity of each item into the input fields of the smartphone app. This forms the order information.

[1906] Step 2:

[1907] Input: The user presses the submit button.

[1908] Specific operation: The entered order information is constructed in JSON format within the smartphone device.

[1909] Step 3:

[1910] Input: The smartphone device sends the constructed order information in JSON format to the server endpoint via a POST request.

[1911] Specific operation: The smartphone device sends a POST request to the specified endpoint of the server via the network. This request contains order information in JSON format.

[1912] Step 4:

[1913] Input: The server receives a POST request.

[1914] What happens: The server endpoint captures the request and extracts the JSON data from the request body.

[1915] Step 5:

[1916] Input: The server parses the received order information.

[1917] Specific operation: The server parses the extracted JSON data and obtains it as a dictionary-style object. Specifically, it separates information such as order_id, customer_id, and items.

[1918] Step 6:

[1919] Input: The server checks for missing required fields based on the analysis results.

[1920] Specific operation: The server checks whether the order_id, customer_id, and items exist in the order information it retrieves. If any required items are missing, it will proceed to the next step.

[1921] Step 7:

[1922] Input: The server checks each item for missing information.

[1923] Specific operation: The server checks whether the item_id and quantity are present for each element in the items list. If any information is missing, it proceeds to the next step.

[1924] Step 8:

[1925] Input: The server checks the quantity for validity.

[1926] Specific operation: The server checks whether the quantity of each item is greater than or equal to 0. If an invalid quantity is detected, it proceeds to the next step.

[1927] Step 9:

[1928] Input: The server determines whether there are any errors.

[1929] Specific operation: Determine whether there are any defects based on the past check results. If there are any defects, generate an error message. If there are no defects, generate an order acceptance message.

[1930] Step 10:

[1931] Input: The server sends the message back to the user.

[1932] Specific operation: The server generates a message (error or acceptance) in JSON format according to the judgment result and returns it to the smartphone device as a response.

[1933] Step 11:

[1934] Input: The device receives a response from the server.

[1935] Specific operation: The smartphone device receives the response from the server and analyzes the content.

[1936] Step 12:

[1937] Input: The device determines the next action based on the analysis results.

[1938] Specific operation: Based on the response from the server, if the order is normal, an order acceptance message is displayed; if there is an error, an error message is displayed on the screen to prompt the user to correct the error.

[1939] Example prompt sentence:

[1940] "Please input the order information including order_id, customer_id, and items with item_id and quantity. Make sure all required fields are filled and quantities are valid."

[1941] 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.

[1942] The following describes in detail the mode for carrying out the present invention. This system combines an emotion engine with an automatic response system for inquiries about incomplete order contents, receives order information according to a specific procedure, automatically detects and responds to any incompleteness, and recognizes the user's emotions and provides feedback.

[1943] Server Operation

[1944] 1. The server sets up a dedicated endpoint to receive POST requests from users, which contain order information in JSON format.

[1945] 2. The server parses the JSON-formatted order information from the request body, obtaining the entire order information as a dictionary-format object.

[1946] 3. The server checks whether all required fields (order_id, customer_id, items) are present in the parsed order information. If these fields are missing, the server generates and returns an error message.

[1947] 4. The server then checks for missing information for each item in the order information, specifically checking whether each item has an item_id and quantity.

[1948] 5. The server checks whether the quantity of each item in the order information is a valid value (usually 0 or greater), thereby detecting whether an invalid value for quantity has been entered.

[1949] 6. If any errors are detected in any of the above steps, the server generates an error message and returns it to the user. If no errors are detected, the server generates a success message indicating that the order is successful and returns it to the user.

[1950] 7. The server recognizes the user's emotions using the emotion engine, and provides appropriate feedback to the user based on the inspection result (success or error) of the order information and the emotion data.

[1951] Device behavior

[1952] 1. A user enters a new order at a terminal and sends it to the system.

[1953] 2. The terminal constructs the order information in the appropriate format (JSON format) and sends a POST request to the server's dedicated endpoint.

[1954] 3. The device receives the response from the server and decides the next action based on it. For example, if an error message is returned, it displays the items that need to be corrected to the user. It also displays feedback based on the emotion engine.

[1955] User Actions

[1956] 1. The user uses the interface on the terminal to enter order information, including the order_id, customer_id, item_id and quantity for each item.

[1957] 2. The user checks the entered order information and presses the submit button. This action sends the order information to the server.

[1958] 3. The user receives a response from the server. If the order is correct, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message.

[1959] 4. Users also receive feedback from the emotion engine. For example, when a flaw is detected, the emotion engine recognizes the user's stress or confusion and provides gentle feedback and support accordingly.

[1960] Specific examples

[1961] Normal order case

[1962] The user enters the following order information on the terminal and submits it:

[1963] json

[1964] {

[1965] "order_id": "ORD12345",

[1966] "customer_id": "CUST54321",

[1967] "items": [

[1968] {"item_id": "ITEM001", "quantity": 2},

[1969] {"item_id": "ITEM002", "quantity": 5}

[1970] ]

[1971] }

[1972] The server receives this and performs checks at each step. If all checks pass, it returns a message to the user indicating that the order is correct. The emotion engine also recognizes the user's satisfaction and provides positive feedback to that effect.

[1973] Cases of defective orders

[1974] The user enters the following order information on the terminal and submits it:

[1975] json

[1976] {

[1977] "order_id": "ORD12345",

[1978] "items": [

[1979] {"item_id": "ITEM001"},

[1980] {"item_id": "ITEM002", "quantity": -1}

[1981] ]

[1982] }

[1983] The server receives this and detects that a required field is missing (no customer_id) and the quantity is incorrect (quantity is -1), which causes the server to return the following error message to the user:

[1984] json

[1985] {

[1986] "status": "error",

[1987] "message": "Required fields are missing"

[1988] }

[1989] or

[1990] json

[1991] {

[1992] "status": "error",

[1993] "message": "Invalid quantity: {'item_id': 'ITEM002', 'quantity': -1}"

[1994] }

[1995] Additionally, the emotion engine recognizes when a user is confused or stressed and offers corresponding supportive or encouraging messages:

[1996] json

[1997] {

[1998] "status": "error",

[1999] "message": "Invalid quantity: {'item_id': 'ITEM002', 'quantity': -1}",

[2000] "emotion_feedback": "We're sorry you encountered an issue. Please enter the required information and try again."

[2001] }

[2002] This system automatically detects errors in order details and responds quickly, thereby improving operational efficiency and customer satisfaction. In addition, the introduction of an emotion engine improves the user experience and helps build good relationships with customers.

[2003] The processing flow will be explained below.

[2004] Step 1:

[2005] The server receives a POST request to a dedicated endpoint and receives the order information sent by the user from the terminal as JSON format data.

[2006] Step 2:

[2007] The server parses the received request body and converts the JSON data into a dictionary-style object. Through this parsing, the entire order information is obtained as data.

[2008] Step 3:

[2009] The server checks whether all required items (order_id, customer_id, and items) are present in the order information. If these items are missing, the server generates and returns an error message.

[2010] Step 4:

[2011] The server checks whether the item_id and quantity are present for each item in items. If they are missing, the server generates and returns a detailed error message.

[2012] Step 5:

[2013] The server checks whether the quantity value for each item in items is greater than 0, i.e., whether it is an invalid quantity. If an invalid quantity is detected, the server generates and returns an error message indicating this.

[2014] Step 6:

[2015] The server generates an error or success message based on the result of detecting the order information and returns it to the user. If there are no errors, it generates a success message indicating that the order is normal.

[2016] Step 7:

[2017] The server uses an emotion engine to recognize the user's emotions in real time, and provides appropriate feedback to the user based on the inspection result (success or error) of the order information and the emotion data.

[2018] Step 8:

[2019] The device receives the response from the server and decides the next action based on it. For example, if an error message is returned, it will display the items that need to be corrected to the user and also display feedback from the emotion engine.

[2020] Step 9:

[2021] The user receives the response message returned from the server, and if an error message is included, corrects the order information according to the instructions. If there are no errors, the user confirms that the order has been accepted.

[2022] Step 10:

[2023] If necessary, the user can resubmit the revised order information to the server for rechecking, and receive feedback from the emotion engine again.

[2024] Example 2

[2025] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2026] Conventional order processing systems have had the problem of requiring a lot of time and effort to detect errors in order information. Furthermore, when a user submits an order with errors, the system provides little feedback, which hinders the user experience. In particular, the lack of appropriate feedback and support for orders with errors was a factor that led to a decline in user satisfaction.

[2027] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for receiving order information, a means for analyzing required items from the received order information, a means for detecting whether required items are missing from the order information, a means for detecting whether information on each item is missing from the order information, a means for detecting inappropriate quantities in the order information, a means for generating an order acceptance message if there are no deficiencies, a means for detecting an emotional state, and a means for generating feedback based on the emotional state. This makes it possible to quickly and automatically detect deficiencies in the order content and provide appropriate feedback that also takes the user's emotions into consideration.

[2028] "Order Information" means data entered by a user when placing an order, including an identifier, customer identifier, item list, and other related information.

[2029] "Required items" are particularly important elements of the order information, and include an identifier, a customer identifier, and an item list.

[2030] An "identifier" is information that uniquely identifies a particular order, and typically refers to an order number or ID.

[2031] "Customer identifier" refers to information that uniquely identifies the customer who placed the order, such as customer ID or account information.

[2032] An "item list" is data that lists information about each item included in an order.

[2033] An "item identifier" is information that uniquely identifies each item in an item list, and typically refers to the product ID.

[2034] "Quantity" is information indicating the number of items ordered, and is usually expressed as an integer value.

[2035] "Emotional state" refers to the type and intensity of emotions a user experiences when placing an order and receiving feedback about it.

[2036] "Feedback" refers to response messages that return information to the user about the status or deficiencies of an order, including additional support messages based on emotional state.

[2037] "Analysis" refers to the process of deciphering received data and extracting necessary information.

[2038] "Detection" refers to the process of finding items or deficiencies that meet specific conditions.

[2039] "Generation" refers to the process of creating new data or messages.

[2040] "Reception" refers to the process of taking in data from outside.

[2041] The following describes in detail the mode for carrying out the present invention. This system combines an emotion engine with an automatic response system for inquiries about order defects. It receives order information according to a specific procedure, automatically detects and responds to any defects, and recognizes the user's emotions and provides feedback. The system consists of three main elements: a server, a terminal, and a user.

[2042] Server Operation

[2043] 1. The server sets up a dedicated endpoint to receive POST requests from users, which contain order information in JSON format.

[2044] 2. The server parses the JSON-formatted order information from the request body, extracting the entire order information as a dictionary-format object.

[2045] 3. The server checks whether all required items (identifier, customer identifier, item list) are present in the parsed order information. If these items are missing, the server generates and returns an error message.

[2046] 4. The server then checks for missing information for each item in the order information, specifically checking whether each item has an item identifier and quantity.

[2047] 5. The server checks whether the quantity of each item in the order information is a valid value (usually 0 or greater), thereby detecting whether an invalid value for quantity has been entered.

[2048] 6. If any errors are detected in any of the above steps, the server generates an error message and returns it to the user. If no errors are detected, the server generates a success message indicating that the order is successful and returns it to the user.

[2049] 7. The server recognizes the user's emotions using the emotion engine, and provides appropriate feedback to the user based on the inspection result (success or error) of the order information and the emotion data.

[2050] Device behavior

[2051] 1. A user enters a new order at a terminal and sends it to the system.

[2052] 2. The terminal constructs the order information in the appropriate format (JSON format) and sends a POST request to the server's dedicated endpoint.

[2053] 3. The device receives the response from the server and decides the next action based on it. For example, if an error message is returned, it displays the items that need to be corrected to the user. It also displays feedback based on the emotion engine.

[2054] User Actions

[2055] 1. The user uses the interface on the terminal to enter order information, including the identifier, customer identifier, item identifier and quantity for each item.

[2056] 2. The user checks the entered order information and presses the submit button. This action sends the order information to the server.

[2057] 3. The user receives a response from the server. If the order is successful, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message.

[2058] 4. Users also receive feedback from the emotion engine. For example, when a flaw is detected, the emotion engine recognizes the user's stress or confusion and provides gentle feedback and support accordingly.

[2059] Specific examples

[2060] Normal order case

[2061] A user enters the following order information on the terminal and submits it:

[2062] Prompt statement:

[2063] Order ID: ORD12345

[2064] Customer ID: CUST54321

[2065] item:

[2066] Item ID: ITEM001, Quantity: 2

[2067] Item ID: ITEM002, Quantity: 5

[2068] The server receives this and performs checks at each step. If all checks pass, it returns a message to the user indicating that the order is correct. The emotion engine also recognizes the user's satisfaction and provides positive feedback to that effect.

[2069] Cases of defective orders

[2070] A user enters the following order information on the terminal and submits it:

[2071] Prompt statement:

[2072] Order ID: ORD12345

[2073] item:

[2074] Item ID: ITEM001

[2075] Item ID: ITEM002, Quantity: -1

[2076] The server receives this and detects that a required field is missing (no customer ID) and the quantity is incorrect (quantity is -1), which causes the server to return the following error message to the user:

[2077] "Required items are missing"

[2078] or

[2079] "Invalid quantity: Item ID: ITEM002, Quantity: -1"

[2080] Additionally, the emotion engine recognizes when a user is confused or stressed and offers corresponding supportive or encouraging messages:

[2081] "Sorry for the problem. Please enter the required information and try again."

[2082] This system automatically detects errors in order details and responds quickly, thereby improving operational efficiency and customer satisfaction. In addition, the introduction of an emotion engine improves the user experience and helps build good relationships with customers.

[2083] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2084] Server Operation

[2085] Step 1:

[2086] The server has a dedicated endpoint that receives POST requests from users, which contain order information in JSON format. The input is JSON data as a POST request, and the output is a parseable JSON object.

[2087] Step 2:

[2088] The server parses the JSON order information from the request body. This parses the entire order information as a dictionary object. The input is the received JSON data, and the output is a dictionary object.

[2089] Step 3:

[2090] The server checks whether all required items (identifier, customer identifier, item list) are present in the parsed order information. If these items are missing, the server generates and returns an error message. The input is a dictionary object, and the output is a Boolean value of the check result and an error message.

[2091] Step 4:

[2092] The server checks whether the item identifier and quantity are present for each item in the order information. If they are missing, the server generates an error message for that item. The input is a dictionary object, and the output is a Boolean result of the check and an error message.

[2093] Step 5:

[2094] The server checks whether the quantity of each item in the order information is a valid value (usually 0 or greater). If the quantity is invalid, the server generates an error message. The input is a dictionary object, and the output is a Boolean value of the check result and an error message.

[2095] Step 6:

[2096] If any errors are detected at any of the above steps, the server generates an error message and returns it to the user. If no errors are found, it generates a success message stating that the order is normal and returns it to the user. The input is the check result at each step, and the output is an error message or a success message.

[2097] Step 7:

[2098] The server uses an emotion engine to recognize the user's emotion. Based on the inspection result (success or error) of the order information and the emotion data, it provides appropriate feedback to the user. The input is the inspection result and user interaction data, and the output is a feedback message based on the emotion.

[2099] Device behavior

[2100] Step 1:

[2101] A user enters a new order on a terminal and sends it to the system. The input is the data the user entered into the interface, and the output is the constructed order information in JSON format.

[2102] Step 2:

[2103] The terminal constructs the order information in the appropriate format (JSON format) and sends a POST request to a dedicated endpoint on the server. The input is the data entered by the user, and the output is the JSON data sent to the server.

[2104] Step 3:

[2105] The device receives the response from the server and determines the next action based on that. For example, if an error message is returned, it displays the items that need to be corrected to the user. It also displays feedback from the emotion engine. The input is the response message from the server, and the output is the feedback message displayed to the user.

[2106] User Actions

[2107] Step 1:

[2108] The user uses the interface on the terminal to enter order information, including an identifier, a customer identifier, an item identifier and a quantity for each item. The input is the data entered by the user into the interface, and the output is confirmation of the input fields displayed on the terminal.

[2109] Step 2:

[2110] The user confirms the entered order information and presses the send button. This action sends the order information to the server. The input is the confirmed order information, and the output is a trigger for sending to the server.

[2111] Step 3:

[2112] The user receives a response from the server. If the order is normal, the user confirms that the order has been accepted. If there are any errors, the user makes the necessary corrections based on the error message. The input is the response message from the server, and the output is the action to correct or confirm the order.

[2113] Step 4:

[2114] The user also receives feedback from the emotion engine. For example, when a flaw is detected, the emotion engine recognizes the user's stress or confusion and provides gentle feedback and support accordingly. The input is the feedback message from the emotion engine, and the output is the user's next action (correction or resubmission).

[2115] (Application example 2)

[2116] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2117] While conventional order management systems can detect errors in order information, they have the problem of not being able to properly manage the user's feelings and provide feedback. As a result, when users feel stressed or confused, they are unable to respond quickly and appropriately, which can lead to a poor user experience. Furthermore, there is a demand for smartphone applications that allow users to easily enter appropriate order information and receive immediate feedback.

[2118] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving order information, means for analyzing required items from the received order information, means for detecting whether required items in the order information are missing, means for detecting whether information on each item in the order information is missing, means for detecting inappropriate quantities in the order information, means for generating an order acceptance message if there are no defects, means for recognizing the user's emotions, and means for providing feedback based on the user's emotions. This makes it possible to quickly detect defects in the order content and provide appropriate feedback based on the user's emotions.

[2119] "Order information" refers to detailed order information entered by a user when purchasing a product or service.

[2120] "Required items" are important data items that are indispensable within the order information, and examples include order_id, customer_id, and items.

[2121] "Quantity" is a numerical value that indicates the number of each item in the order information.

[2122] An "emotion engine" is a system that recognizes and analyzes emotions from the text, voice, facial expressions, etc. entered by the user.

[2123] "Feedback" refers to the reply or response that a system provides to a user, particularly one that is appropriate in response to the user's emotions.

[2124] A "server" is a computer system that receives requests from clients and returns responses to those requests.

[2125] An "order acceptance message" is a message sent to a user when the order information is normal, informing the user that the order has been accepted.

[2126] An "incomplete" is when required data or information is missing or incorrect in the order information.

[2127] "Means for analysis" refers to systems or software that have the function of breaking down and analyzing the received data and extracting the necessary information.

[2128] "Means of detection" are systems or software that have the functionality to find missing information or inappropriate values.

[2129] A "means for providing feedback" is a system or software that has the functionality to generate and provide an appropriate reply or response based on the user's emotions and the status of the order information.

[2130] The following is a detailed description of an embodiment of the present invention. This system combines an automatic response system for inquiries about incomplete order contents with an emotion engine, and the server, terminal, and user each play their role according to a specific procedure.

[2131] The server sets up a dedicated endpoint and receives POST requests from users. This request contains order information in JSON format. The server parses the JSON-formatted order information from the request body and obtains it as a dictionary-format object. Next, it checks whether all required fields (order_id, customer_id, items) are present in the order information, and if any are missing, it generates and returns an error message. It also checks the item_id and quantity for each item to ensure that the quantity is an appropriate value (0 or greater). This detects whether an invalid value for the quantity has been entered. If there are no errors, it generates a success message stating that the order is normal and returns it to the user.

[2132] The server then uses an emotion engine to recognize the user's emotions. It is recommended to use an external service (e.g., Hume AI) for this emotion recognition. The emotion engine analyzes the user's input text to detect emotions such as stress or confusion. To provide feedback based on the detected emotion, the server generates an appropriate support message along with a success or error message.

[2133] The terminal helps the user enter a new order and submit it to the system. The order is constructed in the appropriate format (JSON) and a POST request is sent to a dedicated endpoint on the server. When a response is received from the server, it determines the next action to take. If an error message is returned, it displays the items that need to be corrected to the user, as well as feedback from the emotion engine.

[2134] The user inputs order information using the interface on the terminal, confirms it, and then submits it. The submitted data is checked by the server, and if the order is correct, the user receives a confirmation message, or if there is a problem, an error message and emotional feedback.

[2135] As a concrete example, consider the case of a successful order. Consider the case where a user enters the following order information on a terminal and submits it:

[2136] {

[2137] "order_id": "ORD12345",

[2138] "customer_id": "CUST54321",

[2139] "items": [

[2140] {"item_id": "ITEM001", "quantity": 2},

[2141] {"item_id": "ITEM002", "quantity": 5}

[2142] ]

[2143] }

[2144] The server receives this and checks each step. If all checks pass, it returns a message to the user indicating that the order is correct. The emotion engine also recognizes the user's satisfaction and provides positive feedback.

[2145] Also, consider the following example of an incomplete order:

[2146] {

[2147] "order_id": "ORD12345",

[2148] "items": [

[2149] {"item_id": "ITEM001"},

[2150] {"item_id": "ITEM002", "quantity": -1}

[2151] ]

[2152] }

[2153] The server receives this and detects the lack of required fields (no customer_id) and the inappropriate quantity (quantity is -1). Along with the error message, the server's emotion engine recognizes the user's confusion and stress and provides a corresponding support message.

[2154] Examples of prompts for a generative AI model might include:

[2155] Detect the order information entered by the user and display an error message for any incomplete items. Also, use a sentiment engine to analyze the user's sentiment and display appropriate feedback. The order information is as follows:

[2156] {

[2157] "order_id": "ORD67890",

[2158] "customer_id": "CUST12345",

[2159] "items": [

[2160] {"item_id": "ITEM123", "quantity": 1}

[2161] ],

[2162] "user_message": "I'm having trouble placing my order."

[2163] }

[2164] This system automatically detects errors in order details and responds quickly, improving operational efficiency and customer satisfaction. In addition, the introduction of an emotion engine improves the user experience and helps build good relationships with customers.

[2165] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2166] Step 1:

[2167] The user enters order information on the terminal. Specifically, the user uses a dedicated interface to enter the order_id, customer_id, and item_id and quantity of each item, and then presses the submit button. This creates the order information in JSON format.

[2168] Input: order_id, customer_id, item_id, quantity

[2169] Output: Order information in JSON format

[2170] Step 2:

[2171] The terminal sends the constructed JSON-formatted order information to the server. Specifically, the terminal sends a POST request to a dedicated endpoint on the server, with the order information included in the request body.

[2172] Input: Order information in JSON format

[2173] Output: POST request

[2174] Step 3:

[2175] The server receives the POST request sent from the terminal. Specifically, it receives the request at a dedicated endpoint, extracts the order information from the request body, and parses it into a dictionary-style object.

[2176] Input: POST request

[2177] Output: Order information in dictionary format

[2178] Step 4:

[2179] The server checks whether all required fields (order_id, customer_id, items) are present in the received order information. If any fields are missing, it generates and returns an error message.

[2180] Input: Order information in dictionary format

[2181] Output: Error message or proceed to next step

[2182] Step 5:

[2183] The server checks whether each item in the order information has an item_id and quantity. If the information is insufficient, it generates and returns an error message. It also checks whether the quantity is valid and returns an error message if it is inappropriate.

[2184] Input: Order information in dictionary format

[2185] Output: Error message or proceed to next step

[2186] Step 6:

[2187] If all checks are passed, the server generates a success message indicating that the order contents are correct and returns it to the user.

[2188] Input: Order information in dictionary format

[2189] Output: Success message

[2190] Step 7:

[2191] The server uses an emotion engine to recognize the user's emotions. Specifically, it sends message data from the user to an emotion recognition library (e.g., Hume AI) to obtain emotion data.

[2192] Input: User's message data

[2193] Output: Emotion data

[2194] Step 8:

[2195] The server generates appropriate feedback based on the emotion data. For example, it generates a supportive message if the user is confused, or positive feedback if the user is satisfied. This feedback is polite and sensitive to the user's emotions.

[2196] Input: Emotion data

[2197] Output: Feedback message

[2198] Step 9:

[2199] The user receives a response from the server on their terminal, and if the response is a success message, they know that their order has been accepted, or if there are any issues, they see an error message and emotion-based feedback.

[2200] Input: Response message from the server

[2201] Output: Messages to be displayed (success message, error message, feedback message)

[2202] This series of steps realizes a system that can automatically detect incomplete order information and provide feedback that is sensitive to the user's emotions.

[2203] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2204] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2205] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2206] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2207] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2208] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2209] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2210] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2211] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2212] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2213] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2214] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2215] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2216] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2217] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2218] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2219] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2220] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2221] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2222] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2223] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2224] The following is further disclosed regarding the above embodiment.

[2225] (Claim 1)

[2226] means for receiving order information;

[2227] A means for parsing required fields from the received order information;

[2228] a means for detecting missing required items of order information;

[2229] A means for detecting missing information for each item of the order information;

[2230] means for detecting improper quantities in the order information;

[2231] means for generating an order acceptance message if there are no deficiencies;

[2232] A system including:

[2233] (Claim 2)

[2234] 2. The system according to claim 1, wherein required items of order information include order_id, customer_id, and items.

[2235] (Claim 3)

[2236] 2. The system of claim 1, wherein each item in the order information includes an item_id and a quantity.

[2237] "Example 1"

[2238] (Claim 1)

[2239] means for receiving order information;

[2240] A means of parsing received order information in JSON format;

[2241] a means for detecting missing required items of order information;

[2242] A means for detecting missing information for each item of the order information;

[2243] means for detecting improper quantities in the order information;

[2244] means for generating an order acceptance message if there are no deficiencies;

[2245] If there is a problem, a means to generate and return an appropriate error message;

[2246] A system including:

[2247] (Claim 2)

[2248] 2. The system according to claim 1, wherein required items of order information include order_id, customer_id, and items.

[2249] (Claim 3)

[2250] 2. The system of claim 1, wherein each item in the order information includes an item_id and a quantity.

[2251] "Application Example 1"

[2252] (Claim 1)

[2253] means for receiving order information;

[2254] A means for parsing required fields from the received order information;

[2255] a means for detecting missing required items of order information;

[2256] A means for detecting missing information for each item of the order information;

[2257] means for detecting improper quantities in the order information;

[2258] means for generating an order acceptance message if there are no deficiencies;

[2259] A means for inputting order information and sending a POST request to the endpoint by a smartphone device;

[2260] means for receiving a response from the server and determining a next course of action based thereon;

[2261] Display an error message and prompt the user to correct the problem.

[2262] A system including:

[2263] (Claim 2)

[2264] 2. The system according to claim 1, wherein required items of order information include order_id, customer_id, and items.

[2265] (Claim 3)

[2266] 2. The system of claim 1, wherein each item in the order information includes an item_id and a quantity.

[2267] "Example 2: Combining Emotion Engines"

[2268] (Claim 1)

[2269] means for receiving order information;

[2270] A means for parsing required fields from the received order information;

[2271] a means for detecting missing required items of order information;

[2272] A means for detecting missing information for each item of the order information;

[2273] means for detecting improper quantities in the order information;

[2274] means for generating an order acceptance message if there are no deficiencies;

[2275] a means for detecting an emotional state;

[2276] means for generating feedback based on the emotional state;

[2277] A system including:

[2278] (Claim 2)

[2279] 2. The system of claim 1, wherein required items of order information include an identifier, a customer identifier, and an item list.

[2280] (Claim 3)

[2281] 10. The system of claim 1, wherein each item of order information includes an item identifier and a quantity.

[2282] "Application example 2 when combining emotion engines"

[2283] New invention details

[2284] Considering the content of the new invention, it is a system that not only detects errors in order information but also recognizes the user's emotions and provides feedback based on those emotions. This system detects the user's emotions such as stress or confusion and responds adaptively. It is also assumed that it will be installed on a smartphone application.

[2285] (Claim 1)

[2286] means for receiving order information;

[2287] A means for parsing required fields from the received order information;

[2288] a means for detecting missing required items of order information;

[2289] A means for detecting missing information for each item of the order information;

[2290] means for detecting improper quantities in the order information;

[2291] means for generating an order acceptance message if there are no deficiencies;

[2292] a means of recognizing a user's emotions;

[2293] a means of providing feedback based on user sentiment;

[2294] A system including:

[2295] (Claim 2)

[2296] 2. The system of claim 1, wherein required items of order information include order_id, customer_id, and items.

[2297] (Claim 3)

[2298] 2. The system of claim 1, wherein each item in the order information includes an item_id and a quantity. [Explanation of symbols]

[2299] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:>...

Claims

1. means for receiving order information; A means for parsing required items from the received order information; a means for detecting missing required items of order information; A means for detecting missing information for each item of the order information; means for detecting improper quantities in the order information; means for generating an order acceptance message if there are no deficiencies; A system including:

2. 2. The system according to claim 1, wherein required items of order information include order_id, customer_id, and items.

3. 2. The system of claim 1, wherein each item in the order information includes an item_id and a quantity.

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