system

Abstract

We provide the system. [Solution] Means of inputting information, Means for transmitting information, A means of searching the database, Methods for obtaining search results, A system that includes means for displaying search results.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventionally, operations such as checking the names of persons in charge of specific sales channels or measures, or investigating the order placement window for events required manual work or reference to a separate system, which was inefficient. In addition, every time the information of the person in charge was updated, it was necessary to manually check the consistency of the information, lacking in speed and accuracy. This not only reduced the efficiency of the work but also might lead to the use of incorrect information.

Means for Solving the Problems

[0005] This invention solves the above problems by providing a system that includes means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, and means for displaying search results. This system allows users to easily and quickly search for the names of contact persons for specific sales channels or initiatives, or event ordering contacts. GET requests are used as the means for transmitting information, and a relational database is used. Since the search results are displayed in JSON format, they can be efficiently used as structured data. This significantly improves the efficiency and accuracy of work.

[0006] "Means of inputting information" refers to devices or interfaces that allow users to input specific data into a system.

[0007] "Means of transmitting information" refers to communication protocols and mechanisms for sending user input data to a server.

[0008] "Methods for searching a database" refers to the process of searching for information within a database based on specified conditions and extracting the relevant data.

[0009] "Means for obtaining search results" refers to means for receiving the results of a database search and for further processing or displaying that data.

[0010] "Means for displaying search results" refers to devices or interfaces for visually displaying the acquired search results to the user.

[0011] A "web browser" is an application used to view web pages via the internet.

[0012] A "GET request" is a type of HTTP method used by web browsers to request data from a server, and it sends information using URL parameters.

[0013] A relational database is a type of database that organizes and manages data in a table format, and it is possible to define relationships between tables and execute complex queries.

[0014] "JSON format" is an abbreviation for JavaScript (registered trademark) Object Notation, and refers to a format that structures data in a way that makes it easy for humans to read and easy for machines to analyze. [Brief explanation of the drawing]

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

Mode for Carrying Out the Invention

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

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

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

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

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

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

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

[0023] [First Embodiment]

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

[0025] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

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

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

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

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

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

[0032] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

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

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

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

[0036] This invention relates to a system that includes means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, and means for displaying search results. The purpose of this system is to quickly and accurately obtain the names of persons in charge of specific sales channels or measures, as well as event ordering contacts.

[0037] Specific Examples of the System

[0038] This system works by having the user input information via a web browser and send it to the server. The server searches a database based on the received information and returns the search results to the terminal in JSON format. This entire process will be explained in detail.

[0039] User input

[0040] The user accesses a specific URL using a web browser and enters the required information (e.g., specific sales channels and campaign types) into the displayed form. Once the user has finished entering the information, they click the "Search" button to begin the process.

[0041] Information transmission by terminal

[0042] The terminal uses a program such as JavaScript to retrieve information entered by the user. This information is sent as parameters in a GET request to the specified server endpoint.

[0043] Server-based database search

[0044] The server receives a request sent from the terminal. The request includes the store_type (type of sales channel) and promotion_type (type of promotion) entered by the user. The server uses these parameters to connect to the relational database and search for the corresponding record.

[0045] Server retrieves and processes search results.

[0046] The server retrieves the query results and extracts matching contact names and ordering contact information. This result is converted into JSON format and made available as structured data. The server returns this JSON data to the terminal as a response.

[0047] Displaying search results by device

[0048] The terminal receives a response from the server and parses the received JSON data. Based on this data, it displays information such as the name of the person in charge and the ordering contact point so that the user can visually confirm it through their browser. This allows the user to easily obtain the latest information in real time.

[0049] Specific example

[0050] For example, if a user enters "Major Electronics Retailer" for `store_type` and "BB" for `promotion_type`, the device sends this information to the server as a GET request. The server searches the relational database and retrieves the name of the person in charge of the "BB" promotion at the "Major Electronics Retailer". The retrieved name is converted to JSON format and returned to the device. The device parses the received JSON data and displays the name of the person in charge to the user.

[0051] In this way, the system of the present invention enables users to easily and quickly obtain the names of contact persons and event ordering contacts related to specific sales channels and initiatives. This system significantly improves the efficiency and accuracy of work and prevents the use of incorrect information.

[0052] The following describes the processing flow.

[0053] Step 1:

[0054] The user opens a web browser and accesses a specific URL. The page displays a form for entering `store_type` and `promotion_type`. The user enters the data into these input fields and clicks the "Search" button.

[0055] Step 2:

[0056] The terminal receives user input. The form contents are read using a client-side scripting language such as JavaScript. For example, if "Major Electronics Retailer" is entered for `store_type` and "BB" for `promotion_type`, this information is stored in variables.

[0057] Step 3:

[0058] The data acquired by the device is sent as parameters in a GET request to the endpoint / api / retrieve_representative. Specifically, the URL will be / api / retrieve_representative?store_type=major electronics retailer&promotion_type=BB.

[0059] Step 4:

[0060] The server receives a GET request. The server extracts the request parameters store_type and promotion_type. For example, it verifies that store_type is "Major Electronics Retailer" and promotion_type is "BB".

[0061] Step 5:

[0062] The server establishes a database connection. It then uses a relational database such as SQLite to query the ptn_representatives table in the database.

[0063] Step 6:

[0064] The server generates the SQL query, sets the parameters, and executes the query. The query will look like this:

[0065] SQL

[0066] SELECT representative_name FROM ptn_representatives WHERE store_type = 'Major Electronics Retailer' AND promotion_type = 'BB'

[0067] The server searches for the relevant record.

[0068] Step 7:

[0069] The server retrieves the search results. If a matching record is found, the name of the person in charge is retrieved as a result. For example, "Taro Tanaka" might be retrieved as the person in charge's name.

[0070] Step 8:

[0071] The server converts the retrieved representative name into JSON format. For example, the result might be {"representative_name": "Taro Tanaka"}. If no matching record is found, an error message {"error": "No representative found"} is generated.

[0072] Step 9:

[0073] The server returns a JSON response to the terminal. The HTTP response specifies Content-Type as application / json and sends back a response containing JSON data.

[0074] Step 10:

[0075] The terminal receives a response from the server. It then uses technologies such as JavaScript to analyze the response data.

[0076] Step 11:

[0077] The terminal displays the analysis results on the screen. Based on the received JSON data, it visually presents the user with the name of the person in charge or an error message. For example, if the person in charge's name is "Taro Tanaka," then "Person in Charge: Taro Tanaka" will be displayed on the screen.

[0078] (Example 1)

[0079] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0080] It is crucial to quickly and accurately obtain information such as the names of contact persons and ordering channels related to sales channels and strategies within companies and other organizations, but this has been difficult with conventional methods. In particular, large organizations have required considerable effort and time to extract necessary information from a large amount of data and to process and display it appropriately. The present invention aims to solve these problems and provide a system that enables easy and efficient acquisition and display of information.

[0081] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0082] In this invention, the server includes means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, means for converting search results into structured data, means for processing search results in JSON format, and means for displaying search results. This allows a user to input information about specific sales channels or measures through a web browser, the server to search a database based on this information and return the results obtained in JSON format to the terminal, which then parses and displays the results visually.

[0083] "Means of inputting information" refers to devices or software that provide an interface for users to input the information they need.

[0084] "Means of transmitting information" refers to devices or software used to transfer information entered by a user to a server.

[0085] "Means of searching a database" refers to devices or software that find records within a database based on specified conditions.

[0086] "Means for obtaining search results" refers to devices or software that receive the results of a database search.

[0087] "Means for converting search results into structured data" refers to devices or software that convert acquired data into structured data such as JSON format.

[0088] "Means of processing search results in JSON format" refers to devices or software that process data in JSON format as structured data.

[0089] "Means for displaying search results" refers to devices or software that display search results in a way that allows users to visually confirm the information.

[0090] A "web browser" is software used to access and display websites on the internet.

[0091] A "GET request" is one of the HTTP request methods that a client sends to retrieve resources from a server.

[0092] This invention relates to a system in which information is input and transmitted, a server searches a database, retrieves the search results, and presents them to the user. The purpose of this system is to quickly and accurately obtain information such as the names of persons in charge of specific sales channels or initiatives, and the contact points for event ordering.

[0093] This system is implemented using the following procedure.

[0094] The user accesses a specific URL using a web browser and enters specific information into the displayed form. For example, the user enters "Major electronics retailer" in the `store_type` field and "BB campaign" in the `promotion_type` field. After completing the input, the user clicks the "Search" button. The system then retrieves the user's input and sends it to the server.

[0095] The server receives requests sent from the terminal. Specifically, the server receives the store_type and promotion_type information entered by the user as an HTTP GET request. The server uses JavaScript or Ajax for this process. The relational database used is a common one, such as MySQL® or PostgreSQL. The server uses these parameters to search the database. This search is performed by executing queries against specific tables within the database, and matching records are retrieved.

[0096] Next, the server converts the search results into JSON format and sends them to the terminal as structured data. This ensures data consistency and enables rapid data processing.

[0097] The terminal receives a response from the server and parses the data in JSON format. Then, based on the parsed data, it displays information that the user can visually confirm through their browser. This display is done using HTML, CSS, and JavaScript. This allows the user to obtain information such as the name of the person in charge and the contact point for ordering in real time.

[0098] As a concrete example, consider a case where a user enters "Major Electronics Retailer" for `store_type` and "BB" for `promotion_type`. This information is sent from the terminal to the server, which searches the database and retrieves the name of the person in charge corresponding to the "BB promotion" for the "Major Electronics Retailer". This retrieved person in charge name is converted to JSON format and sent back to the terminal. The terminal parses this information and displays the person in charge name to the user.

[0099] Example of a prompt:

[0100] The user entered "Major Electronics Retailer" in the `store_type` field and "BB Promotion" in the `promotion_type` field on a web form and clicked the "Search" button. This caused the device to send a GET request to the server containing this input information. The server searched the relational database and retrieved the names of the personnel responsible for "BB Promotion" at "Major Electronics Retailer" in JSON format. The device then parsed this JSON data and displayed the personnel names to the user.

[0101] This invention allows users to quickly and accurately obtain information on specific sales channels and strategies, significantly improving operational efficiency.

[0102] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0103] Step 1: Enter Information

[0104] The user accesses a specific URL using a web browser and enters information into the displayed form. For example, they might enter "Major electronics retailer" in the `store_type` field and "BB campaign" in the `promotion_type` field. Once the user has finished entering the information, they click the "Search" button.

[0105] Input: store_type and promotion_type information

[0106] Output: Information entered into the terminal

[0107] Step 2: Send Information

[0108] The device retrieves the information entered by the user and prepares to send it to the server. Specifically, it uses JavaScript to collect the information and sends it to the server's endpoint as an HTTP GET request.

[0109] Input: Information on store_type and promotion_type entered by the user.

[0110] Output: Data included in the GET request to the server

[0111] Specific operation: Use JavaScript to retrieve form data and send it to the server using Ajax.

[0112] Step 3: Request reception and database search

[0113] The server receives a GET request from the terminal and retrieves the `store_type` and `promotion_type` parameters contained within it. It then connects to the relational database and searches for data that matches these parameters.

[0114] Input: Information about store_type and promotion_type included in the GET request

[0115] Output: Search results retrieved from the database

[0116] Specific operation: The server executes a query against a relational database (e.g., MySQL) and retrieves matching records.

[0117] Step 4: Retrieve search results and convert to JSON

[0118] The server extracts the necessary information based on the search results obtained from the database and converts it into JSON format, which is structured data.

[0119] Input: Database search results

[0120] Output: Data converted to JSON format

[0121] Specific operation: Select the necessary fields from the search results and format them as a JSON string.

[0122] Step 5: Send Response

[0123] The server sends the data, converted to JSON format, to the terminal as a response.

[0124] Input: Search results converted to JSON format

[0125] Output: Response to terminal

[0126] Specific operation: The server sends JSON data back to the terminal as an HTTP response.

[0127] Step 6: Response received and data displayed

[0128] The terminal receives a response from the server and parses the received JSON data. Then, based on the parsed data, it displays the search results in the user's web browser.

[0129] Input: JSON data received from the server

[0130] Output: Search results displayed to the user

[0131] Specific operation: Use JavaScript to parse JSON data and display the results on the screen using HTML and CSS.

[0132] The above outlines the specific processing flow of this system's program. This process allows users to quickly and accurately obtain information such as the names of contact persons and ordering contacts related to specific sales channels and initiatives.

[0133] (Application Example 1)

[0134] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0135] In logistics centers, it is essential to quickly and accurately obtain necessary contact information (names and contact details for specific departments or projects). However, this information is scattered across multiple systems, resulting in time-consuming and inefficient data collection. Furthermore, there is a risk of obtaining incorrect information, which can hinder business operations. A solution to these problems is needed.

[0136] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0137] In this invention, the server includes means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, means for displaying search results, means for obtaining information related to the storage and movement of items, and means for displaying the obtained information on a user device. This allows the user to easily search for and obtain the desired contact person information, enabling rapid business processing and accurate information transmission.

[0138] "Means of inputting information" refers to an interface that allows users to input necessary information (such as department name or project name) on their device.

[0139] "Means of transmitting information" refers to a mechanism for transmitting information entered by a user to a remote server or other device.

[0140] A "means of searching a database" is a processing device that finds relevant information from stored data, such as a relational database, based on the information that has been transmitted.

[0141] "Means of obtaining search results" refers to the process of retrieving information retrieved from a database and converting it into a usable format.

[0142] "Means for displaying search results" refers to an interface that visually displays the retrieved search results to the user in an easy-to-understand manner.

[0143] "Means for acquiring information related to the handling of storage and movement of goods" refers to the function of collecting information related to goods stored in logistics centers or goods being moved.

[0144] "Means for displaying acquired information on a user device" refers to a mechanism for displaying collected information on a user's device, such as a smartphone or personal computer.

[0145] This invention is a system for quickly and accurately obtaining necessary personnel information at a logistics center. The system includes means for a user to input information, means for transmitting information, means for searching a database, means for obtaining search results, means for displaying search results, means for obtaining information related to the storage and movement of goods, and means for displaying the obtained information on a user device.

[0146] Program Processing Description

[0147] In this system, users input necessary information (such as department name and project name) using a smartphone application. The entered information is then sent to the server via a data transmission method. For example, GET requests or POST requests are used for data transmission.

[0148] The server searches the database based on the received information. This database search process uses technologies such as SQL queries. The search results are converted to JSON format and sent from the server to the user's device.

[0149] The user device parses the received JSON data and visually displays necessary information such as the person in charge's name and contact details. This parsing and display can be done using programming languages ​​such as JavaScript or Python. This allows users to obtain accurate information in real time and perform business processes efficiently.

[0150] Specific example

[0151] For example, consider a scenario where a user searches for a "warehouse management manager" at a logistics center. The user opens a smartphone application and enters "warehouse management" and "inventory management" into the search form. This input is sent to a server, which searches the corresponding database and retrieves the relevant contact information in JSON format. The retrieved information is then sent back to the user's device, displaying the contact person's name and contact details.

[0152] Example of a prompt:

[0153] Please use the following information to search for the contact person at the logistics center.

[0154] Department: Warehouse Management

[0155] Project name: Inventory Clearance

[0156] Thus, by using this system, information retrieval in logistics centers will become easier, and it is expected that operational efficiency will improve dramatically.

[0157] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0158] Step 1:

[0159] The user opens the smartphone application and enters the necessary information (e.g., department name or project name) into the search form. Input is done through text fields, and each field displays a relevant label. The user's input is sent to the device as specific strings such as "warehouse management" or "inventory management."

[0160] Step 2:

[0161] The terminal retrieves the information entered by the user and prepares it for transmission. A program such as JavaScript or Python is executed here, converting the input information into a JSON object. This JSON object is then sent to the server endpoint in the form of a GET or POST request.

[0162] Step 3:

[0163] The server analyzes the request received from the terminal and extracts the included parameters (such as department name and project name). Based on the extracted information, it executes an SQL query against the relational database to search for the relevant records. For example, it searches for information on the person in charge related to the "Inventory Management Project in the Warehouse Management Department".

[0164] Step 4:

[0165] The server retrieves the search results and converts them into JSON format. In this step, it extracts the necessary information (such as the person in charge's name and contact details) from the search result records and structures it into a JSON object. The generated JSON object is sent to the terminal as a response.

[0166] Step 5:

[0167] The terminal receives a response from the server and parses the received JSON data. Using JavaScript or Python code, it converts the JSON data into an object format and extracts the necessary information (such as the person in charge's name and contact information). This information is then displayed on the screen in a format that the user can visually confirm.

[0168] Step 6:

[0169] Users view the contact person information displayed on their device screen and take the necessary action (for example, contact the contact person). Specifically, the contact person's name and contact information are displayed in a list format, and links or buttons are provided for direct contact as needed.

[0170] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0171] This invention relates to a system that includes means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, means for displaying search results, and an emotion engine that recognizes the user's emotions. The purpose of this system is to quickly and accurately obtain the names of persons in charge of specific sales channels or measures and event ordering contacts, and to provide search results that take the user's emotions into consideration.

[0172] Specific Examples of the System

[0173] This system works by having the user input information via a web browser and send it to the server. The server searches a database based on the received information and analyzes the user's emotions using an emotion engine. The search results are returned to the terminal in JSON format and displayed after being adjusted according to the user's emotions.

[0174] User input

[0175] Users access a specific URL using a web browser and enter the required information (e.g., specific sales channels and campaign types) into the displayed form. The input fields also include a field for users to enter text comments, allowing them to express their feelings. Once the user provides this input data, they click the "Search" button to begin processing.

[0176] Information transmission by terminal

[0177] The device uses JavaScript or similar methods to retrieve data entered by the user. This data is sent as parameters in a GET request to the specified server endpoint. For example, the URL might be / api / retrieve_representative?store_type=major electronics retailer&promotion_type=BB&comment=please respond quickly.

[0178] Server-based database search

[0179] The server receives a request sent from the terminal. The request includes the store_type (type of sales channel), promotion_type (type of promotion), and comment (user comment) entered by the user. The server uses these parameters to connect to the relational database and search for the corresponding record.

[0180] Sentiment analysis and result retrieval by the server

[0181] The server uses a sentiment engine to analyze the sentiment of user comments. The sentiment engine analyzes the user's comment text to identify the degree and type of emotion. For example, it can detect emotions such as "strong request" or "dissatisfaction" from user comments. Based on this information, the server adjusts or filters the search results.

[0182] Server retrieves and processes search results.

[0183] The server retrieves the query results and extracts matching contact names and order contact information. This information is converted to JSON format, and necessary adjustments are made based on the sentiment analysis results. For example, if a user expresses dissatisfaction, the server prioritizes providing the names of contacts who are likely to provide more courteous service.

[0184] Displaying search results by device

[0185] The terminal receives a response from the server and parses the JSON data. Since the results of sentiment analysis are also included, they are presented to the user in an appropriate format. For example, if there is a comment that says "Please respond quickly," the search results will be displayed as "High priority personnel."

[0186] Specific example

[0187] For example, if a user enters "Major Electronics Retailer" as the store_type, "BB" as the promotion_type, and "Please respond quickly" as a comment, and then searches, the device sends this information to the server as a GET request. The server searches the relational database and retrieves the name of the person in charge of the "BB" promotion at the "Major Electronics Retailer". At the same time, the sentiment engine analyzes the user comment to determine that it is requesting a "quick response". Based on this, the server selects the most suitable person in charge and returns the result to the device in JSON format. The device then analyzes this result and displays the most suitable person in charge to the user.

[0188] This system allows users to quickly and accurately obtain the information they need, as well as receive appropriate responses tailored to their emotions and expectations. This leads to improved customer satisfaction and a dramatic increase in work efficiency.

[0189] The following describes the processing flow.

[0190] Step 1:

[0191] The user opens a web browser and accesses a specific URL. The page displays forms for entering `store_type` and `promotion_type`, as well as a comment section. The user enters the data into these input fields and clicks the "Search" button.

[0192] Step 2:

[0193] The terminal retrieves user input. The form contents are read using a client-side scripting language such as JavaScript. For example, if the user enters "Major electronics retailer" for `store_type`, "BB" for `promotion_type`, and "Please respond quickly" in the comments field, this information will be stored in a variable.

[0194] Step 3:

[0195] The data acquired by the device is sent as parameters to the endpoint / api / retrieve_representative_with_emotion in a GET request. Specifically, the URL will be / api / retrieve_representative_with_emotion?store_type=major electronics retailer&promotion_type=BB&comment=please respond quickly.

[0196] Step 4:

[0197] The server receives a GET request. The server extracts the values ​​of the request parameters store_type, promotion_type, and comment. For example, it verifies that store_type is "Major electronics retailer", promotion_type is "BB", and comment is "Please respond quickly".

[0198] Step 5:

[0199] The server establishes a database connection. It uses a relational database to query the ptn_representatives table in the database.

[0200] Step 6:

[0201] The server generates the query, sets the parameters, and executes the query. The query will look like this:

[0202] SQL

[0203] SELECT representative_name FROM ptn_representatives WHERE store_type = 'Major Electronics Retailer' AND promotion_type = 'BB'

[0204] The server searches for the relevant record.

[0205] Step 7:

[0206] The server retrieves the search results. If a matching record is found, the name of the person in charge is retrieved as a result. For example, "Taro Tanaka" might be retrieved as the person in charge's name.

[0207] Step 8:

[0208] The server uses an emotion engine to analyze the sentiment from user comments. The emotion engine analyzes the comment "Please respond quickly" and detects the user's strong request.

[0209] Step 9:

[0210] The server adjusts or filters search results based on the sentiment analysis results. For example, if a strong user request is detected, a high-priority contact person is selected. In this case, "Taro Tanaka" would be selected as the high-priority contact person.

[0211] Step 10:

[0212] The server converts the retrieved representative name into JSON format. For example, the result might be {"representative_name": "Taro Tanaka"}. If no matching record is found, an error message {"error": "No representative found"} is generated.

[0213] Step 11:

[0214] The server returns a JSON response to the terminal. The HTTP response specifies Content-Type as application / json and sends back a response containing JSON data.

[0215] Step 12:

[0216] The terminal receives a response from the server. It then uses technologies such as JavaScript to analyze the response data.

[0217] Step 13:

[0218] The terminal displays the analysis results on the screen. Based on the received JSON data, it visually presents the user with the name of the person in charge or an error message. For example, if the person in charge's name is "Taro Tanaka," then "Person in Charge: Taro Tanaka" will be displayed on the screen. The user's sentiment analysis results will also be displayed, so a message such as "A prompt response was expected" may also be shown.

[0219] (Example 2)

[0220] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0221] Traditional information retrieval systems often provide search results without considering user emotions or needs, which can lead to decreased user satisfaction. Furthermore, they struggle to provide appropriate information to users who require quick and accurate responses, resulting in a lack of improvement in operational efficiency.

[0222] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0223] In this invention, the server includes means for inputting information, means for transmitting information, means for searching a database, means for analyzing emotions, means for adjusting search results, means for obtaining search results, and means for displaying search results. This makes it possible to provide optimal information while taking the user's emotions into consideration, thereby improving customer satisfaction and operational efficiency.

[0224] "Means of inputting information" refers to an interface for users to input necessary information, such as a form in a web browser.

[0225] "Means of transmitting information" refers to the mechanism for sending data entered by a user to a server, which may include using a GET request, for example.

[0226] "Means of searching a database" refers to a mechanism that searches for relevant information from relational and non-relational databases based on the input data.

[0227] "Means of analyzing emotions" refers to engines or software that analyze emotions from user-inputted comments, such as generative AI models.

[0228] "Means of adjusting search results" refers to mechanisms that prioritize or filter search results based on the results of sentiment analysis.

[0229] "Means for obtaining search results" refers to a mechanism for collecting information extracted from a database and using it for subsequent processing.

[0230] "Means of displaying search results" refers to the interface used to visualize the final retrieved search results for the user, such as the display component of a web page.

[0231] The present invention is a system for quickly and accurately obtaining information requested by a user and presenting it appropriately while taking the user's emotions into consideration. This system includes means for inputting information, means for transmitting information, means for searching a database, means for analyzing emotions, means for adjusting search results, means for obtaining search results, and means for displaying search results.

[0232] User input

[0233] The user accesses a specific URL through a web browser and enters the required information into a form. This form includes fields for "Sales Channel Type," "Measure Type," and "Comments." The comments field allows the user to write their feelings or requests. For example, let's assume the user selects "Major Electronics Retailer" as the sales channel type, "BB" as the measure type, and enters the comment "Please respond quickly."

[0234] Information transmission by terminal

[0235] The device uses JavaScript to retrieve the data entered by the user and sends it as a parameter to the specified server endpoint in a GET request. A concrete example request URL would be / api / retrieve_representative?store_type=major electronics retailer&promotion_type=BB&comment=please respond quickly.

[0236] Server-based database search

[0237] The server receives a request sent from the terminal. This request contains the information entered by the user: store_type, promotion_type, and comment. The server uses these parameters to connect to a relational database (such as MySQL) and retrieve the corresponding record.

[0238] Server-based sentiment analysis

[0239] The server uses an emotion engine (e.g., IBM Watson® Tone Analyzer) to analyze the sentiment of user comments. The analysis results include emotions such as "strong request for a quick response" or "dissatisfaction." For example, a comment like "Please respond quickly" might be interpreted as a "strong request."

[0240] Server generates and sends search results.

[0241] The server converts the contact person names and order contact information retrieved from the database into JSON format and adjusts the information based on the sentiment analysis results. For example, if a user indicates a "strong request for a quick response," the server adjusts the information to provide contact person information with a higher priority. This data is ultimately returned to the terminal in JSON format.

[0242] Displaying search results by device

[0243] The terminal parses the JSON data received from the server and displays the search results to the user in an appropriate format. For example, if there is a comment that says "Please respond quickly," the result will be displayed as "High priority person in charge."

[0244] Specific example

[0245] For example, if a user enters "Major electronics retailer" as the store_type, "BB" as the promotion_type, and "Please respond quickly" as a comment, the device sends this information to the server as a GET request. The server searches the relational database and retrieves the name of the person in charge of the "BB" promotion at the "Major electronics retailer". At the same time, the sentiment engine analyzes the user's comment to determine that it requests a "quick response". Based on this, the server selects the most suitable person in charge and returns it to the device as a result in JSON format. The device then analyzes this result and displays the most suitable person in charge to the user.

[0246] Example of a prompt

[0247] Send the following information as a GET request to the URL:

[0248] store_type: Major consumer electronics retailer

[0249] promotion_type: BB

[0250] Comment: Please respond promptly.

[0251] Search the database for the relevant person in charge and analyze the comments using a sentiment engine. Then, return the search results in JSON format.

[0252] This system allows users to quickly and accurately obtain the information they need and receive appropriate responses that meet their emotions and expectations. This leads to improved customer satisfaction and increased operational efficiency.

[0253] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0254] Step 1:

[0255] The user accesses a specific URL using a web browser and enters the required information into the displayed form. Specifically, they fill in the fields for "Sales Channel Type," "Measure Type," and "Comments." Once they have finished entering the information, they click the "Search" button.

[0256] Input: Information entered by the user in the form (e.g., store_type, promotion_type, comment)

[0257] Output: User input data acquired by the terminal

[0258] Step 2:

[0259] The device uses JavaScript to retrieve data entered by the user into a form. This retrieved data is then sent as parameters to a GET request to the specified server endpoint.

[0260] Input: User input data

[0261] Output: Data in GET request format sent to the server

[0262] Specific actions:

[0263] The device retrieves the user's form input data using JavaScript.

[0264] Generate a GET request URL (e.g., / api / retrieve_representative?store_type=major electronics retailer&promotion_type=BB&comment=please respond quickly).

[0265] Send data to the server.

[0266] Step 3:

[0267] The server receives a GET request sent from the terminal. It extracts and parses the parameters store_type, promotion_type, and comment included in the request.

[0268] Input: GET request data from the terminal

[0269] Output: Extracted parameters (store_type, promotion_type, comment)

[0270] Specific actions:

[0271] The server receives a GET request.

[0272] Extract parameters from the request (e.g., store_type = large home appliance retailer, promotion_type = BB, comment = Please provide prompt response).

[0273] Step 4:

[0274] The server uses the extracted parameters to connect to a relational database (e.g., MySQL) and search for corresponding records.

[0275] Input: Extracted parameters

[0276] Output: Search results from the database

[0277] Specific operations:

[0278] Generate a database query based on the extracted parameters.

[0279] Execute the database query and search for corresponding records.

[0280] Obtain the search results.

[0281] Step 5:

[0282] The server uses a sentiment engine (e.g., IBM Watson Tone Analyzer) to analyze the user's comment. Analyze the comment text to identify the degree and type of sentiment.

[0283] Input: User's comment text

[0284] Output: Results of sentiment analysis (e.g., strong desire, dissatisfaction, etc.)

[0285] Specific operations:

[0286] Send the user's comment text to the sentiment engine.

[0287] The emotion engine analyzes the text to identify the type and degree of emotion.

[0288] Obtain the emotion analysis results.

[0289] Step 6:

[0290] The server converts the search results retrieved from the database into JSON format and makes adjustments based on the sentiment analysis results. The adjusted results are then sent to the terminal.

[0291] Input: Database search results, sentiment analysis results

[0292] Output: Search results in adjusted JSON format

[0293] Specific actions:

[0294] Convert the search results retrieved from the database into JSON format.

[0295] The search results are adjusted based on sentiment analysis results (e.g., prioritizing the provision of information on high-priority contacts).

[0296] The adjusted results will be sent to the device.

[0297] Step 7:

[0298] The terminal parses the JSON data received from the server and displays the search results to the user in an appropriate format.

[0299] Input: JSON data received from the server

[0300] Output: Search results displayed to the user

[0301] Specific actions:

[0302] The system parses the JSON data received from the server.

[0303] Pass the results to the UI components to visualize them for the user.

[0304] Display the search results (e.g., display as "personnel who can be expected to respond quickly").

[0305] (Application Example 2)

[0306] Next, Application Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart device 14 is referred to as the "terminal".

[0307] In the conventional system, even when the user inputs information, it is not possible to provide search results according to the user's emotions and expectations, so there is a problem that the user satisfaction decreases. Also, when a quick and accurate response is required, there is a problem that it is difficult to select an appropriate person in a system that does not consider emotions.

[0308] The specific processing by the specific 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 a means for inputting information, a means for transmitting information, a means for searching a database, a means for obtaining search results, a means for displaying search results, and an emotion analysis engine for analyzing the user's emotions. Thereby, it becomes possible to adjust the search results based on the user's emotions.

[0309] The "means for inputting information" is an interface for the user to input necessary information to the system, and examples include a web browser and a smartphone application.

[0310] The "means for transmitting information" is a communication means for transmitting the information input by the user to the server, and specifically uses an HTTP request such as a GET request.

[0311] The "means for searching a database" is a function for searching relevant data from the database based on the information received on the server side.

[0312] "Means for obtaining search results" refers to the function that allows the server to receive the results of a database search and process those results as appropriate.

[0313] "Means of displaying search results" refers to the interface used to display the retrieved search results to the user, such as the screen of a web browser or a smartphone application.

[0314] A "sentiment analysis engine" is a software component that analyzes emotions from user input text and identifies the degree and type of emotion.

[0315] "Means of adjusting search results based on user sentiment" refers to a function that appropriately filters or prioritizes search results based on sentiment information obtained by a sentiment analysis engine.

[0316] This invention relates to a system including means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, means for displaying search results, and an emotion analysis engine for analyzing the user's emotions. This system allows users to quickly and accurately obtain the information they need and receive appropriate responses that match their emotions and expectations.

[0317] Specific examples

[0318] User input

[0319] Users access a specific screen using a smartphone application and enter the required information into the displayed form. The input fields also include a field for users to enter text comments, allowing them to express their feelings. Once the user provides this input data, they tap the "Search" button to begin processing.

[0320] Information transmission by terminal

[0321] The device uses JavaScript or similar methods to retrieve data entered by the user. This data is sent as parameters in an HTTP GET request to the specified server endpoint. For example, the URL might be / api / retrieve_representative?store_type=large retail store&promotion_type=promotion Type A&comment=urgent action required.

[0322] Server-based database search

[0323] The server receives a request sent from the terminal. The request includes the store_type (type of sales channel), promotion_type (type of promotion), and comment (user comment) entered by the user. The server uses these parameters to connect to the relational database and search for the corresponding record.

[0324] Sentiment analysis and result retrieval by the server

[0325] The server uses a sentiment analysis engine to analyze the emotions expressed in user comments. The sentiment analysis engine analyzes the user's comment text to identify the degree and type of emotion. For example, it can detect emotions such as "strong demand" or "dissatisfaction" from user comments. Based on this information, the server adjusts or filters the search results.

[0326] Server retrieves and processes search results.

[0327] The server retrieves the query results and extracts matching contact names and order contact information. This information is converted to JSON format, and necessary adjustments are made based on the sentiment analysis results. For example, if a user expresses dissatisfaction, the server prioritizes providing the names of contacts who are likely to provide more courteous service.

[0328] Displaying search results by device

[0329] The terminal receives a response from the server and parses the JSON data. Since the results of sentiment analysis are also included, they are presented to the user in an appropriate format. For example, if there is a comment that says "urgent action required," the search results will be displayed as "high priority personnel."

[0330] Specific examples

[0331] For example, if a user enters "Large Retail Store" as the store_type, "Promotion Type A" as the promotion_type, and "I need immediate action" as the comment, the device sends this information to the server as a GET request. The server searches the relational database and retrieves the name of the person in charge of the "Promotion Type A" initiative for the "Large Retail Store". At the same time, the sentiment analysis engine analyzes the user's comment as requesting "immediate action". Based on this, the server selects the most suitable person in charge and returns it to the device as a result in JSON format. The device then analyzes this result and displays the most suitable person in charge to the user.

[0332] Example of a prompt

[0333] User comment: "We need an immediate response."

[0334] Analysis result: Due to the high emotional score, the priority will be set to "High".

[0335] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0336] Step 1:

[0337] The user opens the smartphone application, accesses a specific screen, and enters the required information into the provided form. The input fields include "Sales Channel Type," "Measure Type," and a "Comment Field." Once the user enters this data and taps the "Search" button, the device is ready to proceed to the next step.

[0338] Step 2:

[0339] The terminal retrieves the data entered by the user and sends it to the server as parameters in an HTTP GET request. Specifically, it uses a script such as JavaScript to collect the input data and sends it to the server endpoint in URL format. For example, if you enter "Large-scale retail store" for store_type, "Promotion Type A" for promotion_type, and "Immediate action required" for comment, the following URL will be generated: / api / retrieve_representative?store_type=Large-scale retail store&promotion_type=Promotion Type A&comment=Immediate action required

[0340] Step 3:

[0341] The server parses the request received from the terminal and extracts the request parameters. These extracted parameters include store_type, promotion_type, and comment. Based on these parameters, the server connects to the relational database and searches for the relevant records. This search process extracts contact persons and ordering contact information that have a high degree of accuracy.

[0342] Step 4:

[0343] The server activates a sentiment analysis engine to analyze user comments and calculates a sentiment score from the comment text. The sentiment analysis engine (for example, a natural language processing library such as TextBlob) analyzes the user's text and identifies the degree of emotion, such as positive, negative, or neutral. For example, a comment like "I need immediate action" would receive a high positive sentiment score as a strong request.

[0344] Step 5:

[0345] The server combines database search results with sentiment analysis results and adjusts search results based on the user's emotions. Specifically, if the sentiment score is high, it prioritizes selecting the names of personnel who can be expected to respond more quickly, and filters or prioritizes the results accordingly. These results are converted into JSON format.

[0346] Step 6:

[0347] The terminal receives the search results in JSON format returned from the server and parses them. The parsed search results are then presented to the user in an appropriate format. For example, if a result is tagged with "Priority: High," a message such as "This person is available to handle your request with high priority" will be displayed on the screen. Based on this, the user can receive a prompt response.

[0348] Through the above processing flow, the system can provide optimal search results that meet the user's emotions and expectations, enabling a quick and appropriate response.

[0349] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0350] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0351] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0352] [Second Embodiment]

[0353] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0354] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0355] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0356] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0357] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0358] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0359] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0360] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0361] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0362] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0363] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0364] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0365] This invention relates to a system that includes means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, and means for displaying search results. The purpose of this system is to quickly and accurately obtain the names of persons in charge of specific sales channels or measures, as well as event ordering contacts.

[0366] Specific Examples of the System

[0367] This system works by having the user input information via a web browser and send it to the server. The server searches a database based on the received information and returns the search results to the terminal in JSON format. This entire process will be explained in detail.

[0368] User input

[0369] The user accesses a specific URL using a web browser and enters the required information (e.g., specific sales channels and campaign types) into the displayed form. Once the user has finished entering the information, they click the "Search" button to begin the process.

[0370] Information transmission by terminal

[0371] The terminal uses a program such as JavaScript to retrieve information entered by the user. This information is sent as parameters in a GET request to the specified server endpoint.

[0372] Server-based database search

[0373] The server receives a request sent from the terminal. The request includes the store_type (type of sales channel) and promotion_type (type of promotion) entered by the user. The server uses these parameters to connect to the relational database and search for the corresponding record.

[0374] Server retrieves and processes search results.

[0375] The server retrieves the query results and extracts matching contact names and ordering contact information. This result is converted into JSON format and made available as structured data. The server returns this JSON data to the terminal as a response.

[0376] Displaying search results by device

[0377] The terminal receives a response from the server and parses the received JSON data. Based on this data, it displays information such as the name of the person in charge and the ordering contact point so that the user can visually confirm it through their browser. This allows the user to easily obtain the latest information in real time.

[0378] Specific example

[0379] For example, if a user enters "Major Electronics Retailer" for `store_type` and "BB" for `promotion_type`, the device sends this information to the server as a GET request. The server searches the relational database and retrieves the name of the person in charge of the "BB" promotion at the "Major Electronics Retailer". The retrieved name is converted to JSON format and returned to the device. The device parses the received JSON data and displays the name of the person in charge to the user.

[0380] In this way, the system of the present invention enables users to easily and quickly obtain the names of contact persons and event ordering contacts related to specific sales channels and initiatives. This system significantly improves the efficiency and accuracy of work and prevents the use of incorrect information.

[0381] The following describes the processing flow.

[0382] Step 1:

[0383] The user opens a web browser and accesses a specific URL. The page displays a form for entering `store_type` and `promotion_type`. The user enters the data into these input fields and clicks the "Search" button.

[0384] Step 2:

[0385] The terminal receives user input. The form contents are read using a client-side scripting language such as JavaScript. For example, if "Major Electronics Retailer" is entered for `store_type` and "BB" for `promotion_type`, this information is stored in variables.

[0386] Step 3:

[0387] The data acquired by the device is sent as parameters in a GET request to the endpoint / api / retrieve_representative. Specifically, the URL will be / api / retrieve_representative?store_type=major electronics retailer&promotion_type=BB.

[0388] Step 4:

[0389] The server receives a GET request. The server extracts the request parameters store_type and promotion_type. For example, it verifies that store_type is "Major Electronics Retailer" and promotion_type is "BB".

[0390] Step 5:

[0391] The server establishes a database connection. It then uses a relational database such as SQLite to query the ptn_representatives table in the database.

[0392] Step 6:

[0393] The server generates the SQL query, sets the parameters, and executes the query. The query will look like this:

[0394] SQL

[0395] SELECT representative_name FROM ptn_representatives WHERE store_type = 'Major Electronics Retailer' AND promotion_type = 'BB'

[0396] The server searches for the relevant record.

[0397] Step 7:

[0398] The server retrieves the search results. If a matching record is found, the name of the person in charge is retrieved as a result. For example, "Taro Tanaka" might be retrieved as the person in charge's name.

[0399] Step 8:

[0400] The server converts the retrieved representative name into JSON format. For example, the result might be {"representative_name": "Taro Tanaka"}. If no matching record is found, an error message {"error": "No representative found"} is generated.

[0401] Step 9:

[0402] The server returns a JSON response to the terminal. The HTTP response specifies Content-Type as application / json and sends back a response containing JSON data.

[0403] Step 10:

[0404] The terminal receives a response from the server. It then uses technologies such as JavaScript to analyze the response data.

[0405] Step 11:

[0406] The terminal displays the analysis results on the screen. Based on the received JSON data, it visually presents the user with the name of the person in charge or an error message. For example, if the person in charge's name is "Taro Tanaka," then "Person in Charge: Taro Tanaka" will be displayed on the screen.

[0407] (Example 1)

[0408] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0409] It is crucial to quickly and accurately obtain information such as the names of contact persons and ordering channels related to sales channels and strategies within companies and other organizations, but this has been difficult with conventional methods. In particular, large organizations have required considerable effort and time to extract necessary information from a large amount of data and to process and display it appropriately. The present invention aims to solve these problems and provide a system that enables easy and efficient acquisition and display of information.

[0410] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0411] In this invention, the server includes means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, means for converting search results into structured data, means for processing search results in JSON format, and means for displaying search results. This allows a user to input information about specific sales channels or measures through a web browser, the server to search a database based on this information and return the results obtained in JSON format to the terminal, which then parses and displays the results visually.

[0412] "Means of inputting information" refers to devices or software that provide an interface for users to input the information they need.

[0413] "Means of transmitting information" refers to devices or software used to transfer information entered by a user to a server.

[0414] "Means of searching a database" refers to devices or software that find records within a database based on specified conditions.

[0415] "Means for obtaining search results" refers to devices or software that receive the results of a database search.

[0416] "Means for converting search results into structured data" refers to devices or software that convert acquired data into structured data such as JSON format.

[0417] "Means of processing search results in JSON format" refers to devices or software that process data in JSON format as structured data.

[0418] "Means for displaying search results" refers to devices or software that display search results in a way that allows users to visually confirm the information.

[0419] A "web browser" is software used to access and display websites on the internet.

[0420] A "GET request" is one of the HTTP request methods that a client sends to retrieve resources from a server.

[0421] This invention relates to a system in which information is input and transmitted, a server searches a database, retrieves the search results, and presents them to the user. The purpose of this system is to quickly and accurately obtain information such as the names of persons in charge of specific sales channels or initiatives, and the contact points for event ordering.

[0422] This system is implemented using the following procedure.

[0423] The user accesses a specific URL using a web browser and enters specific information into the displayed form. For example, the user enters "Major electronics retailer" in the `store_type` field and "BB campaign" in the `promotion_type` field. After completing the input, the user clicks the "Search" button. The system then retrieves the user's input and sends it to the server.

[0424] The server receives requests sent from the terminal. Specifically, the server receives the store_type and promotion_type information entered by the user as an HTTP GET request. The server uses JavaScript or Ajax for this process. The relational database used is a common one, such as MySQL or PostgreSQL. The server uses these parameters to search the database. This search is performed by executing queries against specific tables within the database, and matching records are retrieved.

[0425] Next, the server converts the search results into JSON format and sends them to the terminal as structured data. This ensures data consistency and enables rapid data processing.

[0426] The terminal receives a response from the server and parses the data in JSON format. Then, based on the parsed data, it displays information that the user can visually confirm through their browser. This display is done using HTML, CSS, and JavaScript. This allows the user to obtain information such as the name of the person in charge and the contact point for ordering in real time.

[0427] As a concrete example, consider a case where a user enters "Major Electronics Retailer" for `store_type` and "BB" for `promotion_type`. This information is sent from the terminal to the server, which searches the database and retrieves the name of the person in charge corresponding to the "BB promotion" for the "Major Electronics Retailer". This retrieved person in charge name is converted to JSON format and sent back to the terminal. The terminal parses this information and displays the person in charge name to the user.

[0428] Example of a prompt:

[0429] The user entered "Major Electronics Retailer" in the `store_type` field and "BB Promotion" in the `promotion_type` field on a web form and clicked the "Search" button. This caused the device to send a GET request to the server containing this input information. The server searched the relational database and retrieved the names of the personnel responsible for "BB Promotion" at "Major Electronics Retailer" in JSON format. The device then parsed this JSON data and displayed the personnel names to the user.

[0430] This invention allows users to quickly and accurately obtain information on specific sales channels and strategies, significantly improving operational efficiency.

[0431] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0432] Step 1: Enter Information

[0433] The user accesses a specific URL using a web browser and enters information into the displayed form. For example, they might enter "Major electronics retailer" in the `store_type` field and "BB campaign" in the `promotion_type` field. Once the user has finished entering the information, they click the "Search" button.

[0434] Input: store_type and promotion_type information

[0435] Output: Information entered into the terminal

[0436] Step 2: Send Information

[0437] The device retrieves the information entered by the user and prepares to send it to the server. Specifically, it uses JavaScript to collect the information and sends it to the server's endpoint as an HTTP GET request.

[0438] Input: Information on store_type and promotion_type entered by the user.

[0439] Output: Data included in the GET request to the server

[0440] Specific operation: Use JavaScript to retrieve form data and send it to the server using Ajax.

[0441] Step 3: Request reception and database search

[0442] The server receives a GET request from the terminal and retrieves the `store_type` and `promotion_type` parameters contained within it. It then connects to the relational database and searches for data that matches these parameters.

[0443] Input: Information about store_type and promotion_type included in the GET request

[0444] Output: Search results retrieved from the database

[0445] Specific operation: The server executes a query against a relational database (e.g., MySQL) and retrieves matching records.

[0446] Step 4: Retrieve search results and convert to JSON

[0447] The server extracts the necessary information based on the search results obtained from the database and converts it into JSON format, which is structured data.

[0448] Input: Database search results

[0449] Output: Data converted to JSON format

[0450] Specific operation: Select the necessary fields from the search results and format them as a JSON string.

[0451] Step 5: Send Response

[0452] The server sends the data, converted to JSON format, to the terminal as a response.

[0453] Input: Search results converted to JSON format

[0454] Output: Response to terminal

[0455] Specific operation: The server sends JSON data back to the terminal as an HTTP response.

[0456] Step 6: Response received and data displayed

[0457] The terminal receives a response from the server and parses the received JSON data. Then, based on the parsed data, it displays the search results in the user's web browser.

[0458] Input: JSON data received from the server

[0459] Output: Search results displayed to the user

[0460] Specific operation: Use JavaScript to parse JSON data and display the results on the screen using HTML and CSS.

[0461] The above outlines the specific processing flow of this system's program. This process allows users to quickly and accurately obtain information such as the names of contact persons and ordering contacts related to specific sales channels and initiatives.

[0462] (Application Example 1)

[0463] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0464] In logistics centers, it is essential to quickly and accurately obtain necessary contact information (names and contact details for specific departments or projects). However, this information is scattered across multiple systems, resulting in time-consuming and inefficient data collection. Furthermore, there is a risk of obtaining incorrect information, which can hinder business operations. A solution to these problems is needed.

[0465] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0466] In this invention, the server includes means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, means for displaying search results, means for obtaining information related to the storage and movement of items, and means for displaying the obtained information on a user device. This allows the user to easily search for and obtain the desired contact person information, enabling rapid business processing and accurate information transmission.

[0467] "Means of inputting information" refers to an interface that allows users to input necessary information (such as department name or project name) on their device.

[0468] "Means of transmitting information" refers to a mechanism for transmitting information entered by a user to a remote server or other device.

[0469] A "means of searching a database" is a processing device that finds relevant information from stored data, such as a relational database, based on the information that has been transmitted.

[0470] "Means of obtaining search results" refers to the process of retrieving information retrieved from a database and converting it into a usable format.

[0471] "Means for displaying search results" refers to an interface that visually displays the retrieved search results to the user in an easy-to-understand manner.

[0472] "Means for acquiring information related to the handling of storage and movement of goods" refers to the function of collecting information related to goods stored in logistics centers or goods being moved.

[0473] "Means for displaying acquired information on a user device" refers to a mechanism for displaying collected information on a user's device, such as a smartphone or personal computer.

[0474] This invention is a system for quickly and accurately obtaining necessary personnel information at a logistics center. The system includes means for a user to input information, means for transmitting information, means for searching a database, means for obtaining search results, means for displaying search results, means for obtaining information related to the storage and movement of goods, and means for displaying the obtained information on a user device.

[0475] Program Processing Description

[0476] In this system, users input necessary information (such as department name and project name) using a smartphone application. The entered information is then sent to the server via a data transmission method. For example, GET requests or POST requests are used for data transmission.

[0477] The server searches the database based on the received information. This database search process uses technologies such as SQL queries. The search results are converted to JSON format and sent from the server to the user's device.

[0478] The user device parses the received JSON data and visually displays necessary information such as the person in charge's name and contact details. This parsing and display can be done using programming languages ​​such as JavaScript or Python. This allows users to obtain accurate information in real time and perform business processes efficiently.

[0479] Specific example

[0480] For example, consider a scenario where a user searches for a "warehouse management manager" at a logistics center. The user opens a smartphone application and enters "warehouse management" and "inventory management" into the search form. This input is sent to a server, which searches the corresponding database and retrieves the relevant contact information in JSON format. The retrieved information is then sent back to the user's device, displaying the contact person's name and contact details.

[0481] Example of a prompt:

[0482] Please use the following information to search for the contact person at the logistics center.

[0483] Department: Warehouse Management

[0484] Project name: Inventory Clearance

[0485] Thus, by using this system, information retrieval in logistics centers will become easier, and it is expected that operational efficiency will improve dramatically.

[0486] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0487] Step 1:

[0488] The user opens the smartphone application and enters the necessary information (e.g., department name or project name) into the search form. Input is done through text fields, and each field displays a relevant label. The user's input is sent to the device as specific strings such as "warehouse management" or "inventory management."

[0489] Step 2:

[0490] The terminal retrieves the information entered by the user and prepares it for transmission. A program such as JavaScript or Python is executed here, converting the input information into a JSON object. This JSON object is then sent to the server endpoint in the form of a GET or POST request.

[0491] Step 3:

[0492] The server analyzes the request received from the terminal and extracts the included parameters (such as department name and project name). Based on the extracted information, it executes an SQL query against the relational database to search for the relevant records. For example, it searches for information on the person in charge related to the "Inventory Management Project in the Warehouse Management Department".

[0493] Step 4:

[0494] The server retrieves the search results and converts them into JSON format. In this step, it extracts the necessary information (such as the person in charge's name and contact details) from the search result records and structures it into a JSON object. The generated JSON object is sent to the terminal as a response.

[0495] Step 5:

[0496] The terminal receives a response from the server and parses the received JSON data. Using JavaScript or Python code, it converts the JSON data into an object format and extracts the necessary information (such as the person in charge's name and contact information). This information is then displayed on the screen in a format that the user can visually confirm.

[0497] Step 6:

[0498] Users view the contact person information displayed on their device screen and take the necessary action (for example, contact the contact person). Specifically, the contact person's name and contact information are displayed in a list format, and links or buttons are provided for direct contact as needed.

[0499] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0500] This invention relates to a system that includes means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, means for displaying search results, and an emotion engine that recognizes the user's emotions. The purpose of this system is to quickly and accurately obtain the names of persons in charge of specific sales channels or measures and event ordering contacts, and to provide search results that take the user's emotions into consideration.

[0501] Specific Examples of the System

[0502] This system works by having the user input information via a web browser and send it to the server. The server searches a database based on the received information and analyzes the user's emotions using an emotion engine. The search results are returned to the terminal in JSON format and displayed after being adjusted according to the user's emotions.

[0503] User input

[0504] Users access a specific URL using a web browser and enter the required information (e.g., specific sales channels and campaign types) into the displayed form. The input fields also include a field for users to enter text comments, allowing them to express their feelings. Once the user provides this input data, they click the "Search" button to begin processing.

[0505] Information transmission by terminal

[0506] The device uses JavaScript or similar methods to retrieve data entered by the user. This data is sent as parameters in a GET request to the specified server endpoint. For example, the URL might be / api / retrieve_representative?store_type=major electronics retailer&promotion_type=BB&comment=please respond quickly.

[0507] Server-based database search

[0508] The server receives a request sent from the terminal. The request includes the store_type (type of sales channel), promotion_type (type of promotion), and comment (user comment) entered by the user. The server uses these parameters to connect to the relational database and search for the corresponding record.

[0509] Sentiment analysis and result retrieval by the server

[0510] The server uses a sentiment engine to analyze the sentiment of user comments. The sentiment engine analyzes the user's comment text to identify the degree and type of emotion. For example, it can detect emotions such as "strong request" or "dissatisfaction" from user comments. Based on this information, the server adjusts or filters the search results.

[0511] Server retrieves and processes search results.

[0512] The server retrieves the query results and extracts matching contact names and order contact information. This information is converted to JSON format, and necessary adjustments are made based on the sentiment analysis results. For example, if a user expresses dissatisfaction, the server prioritizes providing the names of contacts who are likely to provide more courteous service.

[0513] Displaying search results by device

[0514] The terminal receives a response from the server and parses the JSON data. Since the results of sentiment analysis are also included, they are presented to the user in an appropriate format. For example, if there is a comment that says "Please respond quickly," the search results will be displayed as "High priority personnel."

[0515] Specific example

[0516] For example, if a user enters "Major Electronics Retailer" as the store_type, "BB" as the promotion_type, and "Please respond quickly" as a comment, and then searches, the device sends this information to the server as a GET request. The server searches the relational database and retrieves the name of the person in charge of the "BB" promotion at the "Major Electronics Retailer". At the same time, the sentiment engine analyzes the user comment to determine that it is requesting a "quick response". Based on this, the server selects the most suitable person in charge and returns the result to the device in JSON format. The device then analyzes this result and displays the most suitable person in charge to the user.

[0517] This system allows users to quickly and accurately obtain the information they need, as well as receive appropriate responses tailored to their emotions and expectations. This leads to improved customer satisfaction and a dramatic increase in work efficiency.

[0518] The following describes the processing flow.

[0519] Step 1:

[0520] The user opens a web browser and accesses a specific URL. The page displays forms for entering `store_type` and `promotion_type`, as well as a comment section. The user enters the data into these input fields and clicks the "Search" button.

[0521] Step 2:

[0522] The terminal retrieves user input. The form contents are read using a client-side scripting language such as JavaScript. For example, if the user enters "Major electronics retailer" for `store_type`, "BB" for `promotion_type`, and "Please respond quickly" in the comments field, this information will be stored in a variable.

[0523] Step 3:

[0524] The data acquired by the device is sent as parameters to the endpoint / api / retrieve_representative_with_emotion in a GET request. Specifically, the URL will be / api / retrieve_representative_with_emotion?store_type=major electronics retailer&promotion_type=BB&comment=please respond quickly.

[0525] Step 4:

[0526] The server receives a GET request. The server extracts the values ​​of the request parameters store_type, promotion_type, and comment. For example, it verifies that store_type is "Major electronics retailer", promotion_type is "BB", and comment is "Please respond quickly".

[0527] Step 5:

[0528] The server establishes a database connection. It uses a relational database to query the ptn_representatives table in the database.

[0529] Step 6:

[0530] The server generates the query, sets the parameters, and executes the query. The query will look like this:

[0531] SQL

[0532] SELECT representative_name FROM ptn_representatives WHERE store_type = 'Major Electronics Retailer' AND promotion_type = 'BB'

[0533] The server searches for the relevant record.

[0534] Step 7:

[0535] The server retrieves the search results. If a matching record is found, the name of the person in charge is retrieved as a result. For example, "Taro Tanaka" might be retrieved as the person in charge's name.

[0536] Step 8:

[0537] The server uses an emotion engine to analyze the sentiment from user comments. The emotion engine analyzes the comment "Please respond quickly" and detects the user's strong request.

[0538] Step 9:

[0539] The server adjusts or filters search results based on the sentiment analysis results. For example, if a strong user request is detected, a high-priority contact person is selected. In this case, "Taro Tanaka" would be selected as the high-priority contact person.

[0540] Step 10:

[0541] The server converts the retrieved representative name into JSON format. For example, the result might be {"representative_name": "Taro Tanaka"}. If no matching record is found, an error message {"error": "No representative found"} is generated.

[0542] Step 11:

[0543] The server returns a JSON response to the terminal. The HTTP response specifies Content-Type as application / json and sends back a response containing JSON data.

[0544] Step 12:

[0545] The terminal receives a response from the server. It then uses technologies such as JavaScript to analyze the response data.

[0546] Step 13:

[0547] The terminal displays the analysis results on the screen. Based on the received JSON data, it visually presents the user with the name of the person in charge or an error message. For example, if the person in charge's name is "Taro Tanaka," then "Person in Charge: Taro Tanaka" will be displayed on the screen. The user's sentiment analysis results will also be displayed, so a message such as "A prompt response was expected" may also be shown.

[0548] (Example 2)

[0549] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0550] Traditional information retrieval systems often provide search results without considering user emotions or needs, which can lead to decreased user satisfaction. Furthermore, they struggle to provide appropriate information to users who require quick and accurate responses, resulting in a lack of improvement in operational efficiency.

[0551] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0552] In this invention, the server includes means for inputting information, means for transmitting information, means for searching a database, means for analyzing emotions, means for adjusting search results, means for obtaining search results, and means for displaying search results. This makes it possible to provide optimal information while taking the user's emotions into consideration, thereby improving customer satisfaction and operational efficiency.

[0553] "Means of inputting information" refers to an interface for users to input necessary information, such as a form in a web browser.

[0554] "Means of transmitting information" refers to the mechanism for sending data entered by a user to a server, which may include using a GET request, for example.

[0555] "Means of searching a database" refers to a mechanism that searches for relevant information from relational and non-relational databases based on the input data.

[0556] "Means of analyzing emotions" refers to engines or software that analyze emotions from user-inputted comments, such as generative AI models.

[0557] "Means of adjusting search results" refers to mechanisms that prioritize or filter search results based on the results of sentiment analysis.

[0558] "Means for obtaining search results" refers to a mechanism for collecting information extracted from a database and using it for subsequent processing.

[0559] "Means of displaying search results" refers to the interface used to visualize the final retrieved search results for the user, such as the display component of a web page.

[0560] The present invention is a system for quickly and accurately obtaining information requested by a user and presenting it appropriately while taking the user's emotions into consideration. This system includes means for inputting information, means for transmitting information, means for searching a database, means for analyzing emotions, means for adjusting search results, means for obtaining search results, and means for displaying search results.

[0561] User input

[0562] The user accesses a specific URL through a web browser and enters the required information into a form. This form includes fields for "Sales Channel Type," "Measure Type," and "Comments." The comments field allows the user to write their feelings or requests. For example, let's assume the user selects "Major Electronics Retailer" as the sales channel type, "BB" as the measure type, and enters the comment "Please respond quickly."

[0563] Information transmission by terminal

[0564] The device uses JavaScript to retrieve the data entered by the user and sends it as a parameter to the specified server endpoint in a GET request. A concrete example request URL would be / api / retrieve_representative?store_type=major electronics retailer&promotion_type=BB&comment=please respond quickly.

[0565] Server-based database search

[0566] The server receives a request sent from the terminal. This request contains the information entered by the user: store_type, promotion_type, and comment. The server uses these parameters to connect to a relational database (such as MySQL) and retrieve the corresponding record.

[0567] Server-based sentiment analysis

[0568] The server uses an emotion engine (e.g., IBM Watson Tone Analyzer) to analyze the sentiment of a user's comment text. The analysis results include emotions such as "strong request for a quick response" or "dissatisfaction." For example, a comment like "Please respond quickly" might be interpreted as a "strong request."

[0569] Server generates and sends search results.

[0570] The server converts the contact person names and order contact information retrieved from the database into JSON format and adjusts the information based on the sentiment analysis results. For example, if a user indicates a "strong request for a quick response," the server adjusts the information to provide contact person information with a higher priority. This data is ultimately returned to the terminal in JSON format.

[0571] Displaying search results by device

[0572] The terminal parses the JSON data received from the server and displays the search results to the user in an appropriate format. For example, if there is a comment that says "Please respond quickly," the result will be displayed as "High priority person in charge."

[0573] Specific example

[0574] For example, if a user enters "Major electronics retailer" as the store_type, "BB" as the promotion_type, and "Please respond quickly" as a comment, the device sends this information to the server as a GET request. The server searches the relational database and retrieves the name of the person in charge of the "BB" promotion at the "Major electronics retailer". At the same time, the sentiment engine analyzes the user's comment to determine that it requests a "quick response". Based on this, the server selects the most suitable person in charge and returns it to the device as a result in JSON format. The device then analyzes this result and displays the most suitable person in charge to the user.

[0575] Example of a prompt

[0576] Send the following information as a GET request to the URL:

[0577] store_type: Major consumer electronics retailer

[0578] promotion_type: BB

[0579] Comment: Please respond promptly.

[0580] Search the database for the relevant person in charge and analyze the comments using a sentiment engine. Then, return the search results in JSON format.

[0581] This system allows users to quickly and accurately obtain the information they need and receive appropriate responses that meet their emotions and expectations. This leads to improved customer satisfaction and increased operational efficiency.

[0582] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0583] Step 1:

[0584] The user accesses a specific URL using a web browser and enters the required information into the displayed form. Specifically, they fill in the fields for "Sales Channel Type," "Measure Type," and "Comments." Once they have finished entering the information, they click the "Search" button.

[0585] Input: Information entered by the user in the form (e.g., store_type, promotion_type, comment)

[0586] Output: User input data acquired by the terminal

[0587] Step 2:

[0588] The device uses JavaScript to retrieve data entered by the user into a form. This retrieved data is then sent as parameters to a GET request to the specified server endpoint.

[0589] Input: User input data

[0590] Output: Data in GET request format sent to the server

[0591] Specific actions:

[0592] The device retrieves the user's form input data using JavaScript.

[0593] Generate a GET request URL (e.g., / api / retrieve_representative?store_type=major electronics retailer&promotion_type=BB&comment=please respond quickly).

[0594] Send data to the server.

[0595] Step 3:

[0596] The server receives a GET request sent from the terminal. It extracts and parses the parameters store_type, promotion_type, and comment included in the request.

[0597] Input: GET request data from the terminal

[0598] Output: Extracted parameters (store_type, promotion_type, comment)

[0599] Specific actions:

[0600] The server receives a GET request.

[0601] Extract parameters from the request (e.g., store_type=Major electronics retailer, promotion_type=BB, comment=Please respond quickly).

[0602] Step 4:

[0603] The server uses the extracted parameters to connect to a relational database (e.g., MySQL) and search for the relevant records.

[0604] Input: Extracted parameters

[0605] Output: Search results from the database

[0606] Specific actions:

[0607] Generate a database query based on the extracted parameters.

[0608] Execute a database query to find the relevant record.

[0609] Retrieve search results.

[0610] Step 5:

[0611] The server uses a sentiment engine (e.g., IBM Watson Tone Analyzer) to analyze user comments. It analyzes the comment text to identify the degree and type of sentiment.

[0612] Input: User's comment text

[0613] Output: Results of sentiment analysis (e.g., strong demands, dissatisfaction, etc.)

[0614] Specific actions:

[0615] Send user comment text to the sentiment engine.

[0616] The emotion engine analyzes the text to identify the type and degree of emotion.

[0617] Obtain the emotion analysis results.

[0618] Step 6:

[0619] The server converts the search results retrieved from the database into JSON format and makes adjustments based on the sentiment analysis results. The adjusted results are then sent to the terminal.

[0620] Input: Database search results, sentiment analysis results

[0621] Output: Search results in adjusted JSON format

[0622] Specific actions:

[0623] Convert the search results retrieved from the database into JSON format.

[0624] The search results are adjusted based on sentiment analysis results (e.g., prioritizing the provision of information on high-priority contacts).

[0625] The adjusted results will be sent to the device.

[0626] Step 7:

[0627] The terminal parses the JSON data received from the server and displays the search results to the user in an appropriate format.

[0628] Input: JSON data received from the server

[0629] Output: Search results displayed to the user

[0630] Specific actions:

[0631] The system parses the JSON data received from the server.

[0632] The results are passed to a UI component for visualization to the user.

[0633] Display the search results (e.g., display as "Responsible person who can be expected to respond quickly").

[0634] (Application Example 2)

[0635] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0636] Traditional systems suffered from a lack of user satisfaction because they could not provide search results that reflected the user's emotions or expectations, even after they entered information. Furthermore, in situations requiring quick and accurate responses, systems that did not consider emotions made it difficult to select the appropriate person to handle the situation.

[0637] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, means for displaying search results, and an emotion analysis engine for analyzing the user's emotions. This makes it possible to adjust the search results based on the user's emotions.

[0638] "Means of inputting information" refers to the interface through which users input necessary information into a system, such as web browsers and smartphone applications.

[0639] "Means of transmitting information" refers to communication methods used to send information entered by a user to a server, specifically using HTTP requests such as GET requests.

[0640] "Methods for searching a database" refers to functions that allow the server to retrieve relevant data from a database based on the information it receives.

[0641] "Means for obtaining search results" refers to the function that allows the server to receive the results of a database search and process those results as appropriate.

[0642] "Means of displaying search results" refers to the interface used to display the retrieved search results to the user, such as the screen of a web browser or a smartphone application.

[0643] A "sentiment analysis engine" is a software component that analyzes emotions from user input text and identifies the degree and type of emotion.

[0644] "Means of adjusting search results based on user sentiment" refers to a function that appropriately filters or prioritizes search results based on sentiment information obtained by a sentiment analysis engine.

[0645] This invention relates to a system including means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, means for displaying search results, and an emotion analysis engine for analyzing the user's emotions. This system allows users to quickly and accurately obtain the information they need and receive appropriate responses that match their emotions and expectations.

[0646] Specific examples

[0647] User input

[0648] Users access a specific screen using a smartphone application and enter the required information into the displayed form. The input fields also include a field for users to enter text comments, allowing them to express their feelings. Once the user provides this input data, they tap the "Search" button to begin processing.

[0649] Information transmission by terminal

[0650] The device uses JavaScript or similar methods to retrieve data entered by the user. This data is sent as parameters in an HTTP GET request to the specified server endpoint. For example, the URL might be / api / retrieve_representative?store_type=large retail store&promotion_type=promotion Type A&comment=urgent action required.

[0651] Server-based database search

[0652] The server receives a request sent from the terminal. The request includes the store_type (type of sales channel), promotion_type (type of promotion), and comment (user comment) entered by the user. The server uses these parameters to connect to the relational database and search for the corresponding record.

[0653] Sentiment analysis and result retrieval by the server

[0654] The server uses a sentiment analysis engine to analyze the emotions expressed in user comments. The sentiment analysis engine analyzes the user's comment text to identify the degree and type of emotion. For example, it can detect emotions such as "strong demand" or "dissatisfaction" from user comments. Based on this information, the server adjusts or filters the search results.

[0655] Server retrieves and processes search results.

[0656] The server retrieves the query results and extracts matching contact names and order contact information. This information is converted to JSON format, and necessary adjustments are made based on the sentiment analysis results. For example, if a user expresses dissatisfaction, the server prioritizes providing the names of contacts who are likely to provide more courteous service.

[0657] Displaying search results by device

[0658] The terminal receives a response from the server and parses the JSON data. Since the results of sentiment analysis are also included, they are presented to the user in an appropriate format. For example, if there is a comment that says "urgent action required," the search results will be displayed as "high priority personnel."

[0659] Specific examples

[0660] For example, if a user enters "Large Retail Store" as the store_type, "Promotion Type A" as the promotion_type, and "I need immediate action" as the comment, the device sends this information to the server as a GET request. The server searches the relational database and retrieves the name of the person in charge of the "Promotion Type A" initiative for the "Large Retail Store". At the same time, the sentiment analysis engine analyzes the user's comment as requesting "immediate action". Based on this, the server selects the most suitable person in charge and returns it to the device as a result in JSON format. The device then analyzes this result and displays the most suitable person in charge to the user.

[0661] Example of a prompt

[0662] User comment: "We need an immediate response."

[0663] Analysis result: Due to the high emotional score, the priority will be set to "High".

[0664] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0665] Step 1:

[0666] The user opens the smartphone application, accesses a specific screen, and enters the required information into the provided form. The input fields include "Sales Channel Type," "Measure Type," and a "Comment Field." Once the user enters this data and taps the "Search" button, the device is ready to proceed to the next step.

[0667] Step 2:

[0668] The terminal retrieves the data entered by the user and sends it to the server as parameters in an HTTP GET request. Specifically, it uses a script such as JavaScript to collect the input data and sends it to the server endpoint in URL format. For example, if you enter "Large-scale retail store" for store_type, "Promotion Type A" for promotion_type, and "Immediate action required" for comment, the following URL will be generated: / api / retrieve_representative?store_type=Large-scale retail store&promotion_type=Promotion Type A&comment=Immediate action required

[0669] Step 3:

[0670] The server parses the request received from the terminal and extracts the request parameters. These extracted parameters include store_type, promotion_type, and comment. Based on these parameters, the server connects to the relational database and searches for the relevant records. This search process extracts contact persons and ordering contact information that have a high degree of accuracy.

[0671] Step 4:

[0672] The server activates a sentiment analysis engine to analyze user comments and calculates a sentiment score from the comment text. The sentiment analysis engine (for example, a natural language processing library such as TextBlob) analyzes the user's text and identifies the degree of emotion, such as positive, negative, or neutral. For example, a comment like "I need immediate action" would receive a high positive sentiment score as a strong request.

[0673] Step 5:

[0674] The server combines database search results with sentiment analysis results and adjusts search results based on the user's emotions. Specifically, if the sentiment score is high, it prioritizes selecting the names of personnel who can be expected to respond more quickly, and filters or prioritizes the results accordingly. These results are converted into JSON format.

[0675] Step 6:

[0676] The terminal receives the search results in JSON format returned from the server and parses them. The parsed search results are then presented to the user in an appropriate format. For example, if a result is tagged with "Priority: High," a message such as "This person is available to handle your request with high priority" will be displayed on the screen. Based on this, the user can receive a prompt response.

[0677] Through the above processing flow, the system can provide optimal search results that meet the user's emotions and expectations, enabling a quick and appropriate response.

[0678] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0679] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0680] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0681] [Third Embodiment]

[0682] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0683] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0684] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0685] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0686] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0687] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0688] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0689] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0690] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0691] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0692] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0693] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0694] This invention relates to a system that includes means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, and means for displaying search results. The purpose of this system is to quickly and accurately obtain the names of persons in charge of specific sales channels or measures, as well as event ordering contacts.

[0695] Specific Examples of the System

[0696] This system works by having the user input information via a web browser and send it to the server. The server searches a database based on the received information and returns the search results to the terminal in JSON format. This entire process will be explained in detail.

[0697] User input

[0698] The user accesses a specific URL using a web browser and enters the required information (e.g., specific sales channels and campaign types) into the displayed form. Once the user has finished entering the information, they click the "Search" button to begin the process.

[0699] Information transmission by terminal

[0700] The terminal uses a program such as JavaScript to retrieve information entered by the user. This information is sent as parameters in a GET request to the specified server endpoint.

[0701] Server-based database search

[0702] The server receives a request sent from the terminal. The request includes the store_type (type of sales channel) and promotion_type (type of promotion) entered by the user. The server uses these parameters to connect to the relational database and search for the corresponding record.

[0703] Server retrieves and processes search results.

[0704] The server retrieves the query results and extracts matching contact names and ordering contact information. This result is converted into JSON format and made available as structured data. The server returns this JSON data to the terminal as a response.

[0705] Displaying search results by device

[0706] The terminal receives a response from the server and parses the received JSON data. Based on this data, it displays information such as the name of the person in charge and the ordering contact point so that the user can visually confirm it through their browser. This allows the user to easily obtain the latest information in real time.

[0707] Specific example

[0708] For example, if a user enters "Major Electronics Retailer" for `store_type` and "BB" for `promotion_type`, the device sends this information to the server as a GET request. The server searches the relational database and retrieves the name of the person in charge of the "BB" promotion at the "Major Electronics Retailer". The retrieved name is converted to JSON format and returned to the device. The device parses the received JSON data and displays the name of the person in charge to the user.

[0709] In this way, the system of the present invention enables users to easily and quickly obtain the names of contact persons and event ordering contacts related to specific sales channels and initiatives. This system significantly improves the efficiency and accuracy of work and prevents the use of incorrect information.

[0710] The following describes the processing flow.

[0711] Step 1:

[0712] The user opens a web browser and accesses a specific URL. The page displays a form for entering `store_type` and `promotion_type`. The user enters the data into these input fields and clicks the "Search" button.

[0713] Step 2:

[0714] The terminal receives user input. The form contents are read using a client-side scripting language such as JavaScript. For example, if "Major Electronics Retailer" is entered for `store_type` and "BB" for `promotion_type`, this information is stored in variables.

[0715] Step 3:

[0716] The data acquired by the device is sent as parameters in a GET request to the endpoint / api / retrieve_representative. Specifically, the URL will be / api / retrieve_representative?store_type=major electronics retailer&promotion_type=BB.

[0717] Step 4:

[0718] The server receives a GET request. The server extracts the request parameters store_type and promotion_type. For example, it verifies that store_type is "Major Electronics Retailer" and promotion_type is "BB".

[0719] Step 5:

[0720] The server establishes a database connection. It then uses a relational database such as SQLite to query the ptn_representatives table in the database.

[0721] Step 6:

[0722] The server generates the SQL query, sets the parameters, and executes the query. The query will look like this:

[0723] SQL

[0724] SELECT representative_name FROM ptn_representatives WHERE store_type = 'Major Electronics Retailer' AND promotion_type = 'BB'

[0725] The server searches for the relevant record.

[0726] Step 7:

[0727] The server retrieves the search results. If a matching record is found, the name of the person in charge is retrieved as a result. For example, "Taro Tanaka" might be retrieved as the person in charge's name.

[0728] Step 8:

[0729] The server converts the retrieved representative name into JSON format. For example, the result might be {"representative_name": "Taro Tanaka"}. If no matching record is found, an error message {"error": "No representative found"} is generated.

[0730] Step 9:

[0731] The server returns a JSON response to the terminal. The HTTP response specifies Content-Type as application / json and sends back a response containing JSON data.

[0732] Step 10:

[0733] The terminal receives a response from the server. It then uses technologies such as JavaScript to analyze the response data.

[0734] Step 11:

[0735] The terminal displays the analysis results on the screen. Based on the received JSON data, it visually presents the user with the name of the person in charge or an error message. For example, if the person in charge's name is "Taro Tanaka," then "Person in Charge: Taro Tanaka" will be displayed on the screen.

[0736] (Example 1)

[0737] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0738] It is crucial to quickly and accurately obtain information such as the names of contact persons and ordering channels related to sales channels and strategies within companies and other organizations, but this has been difficult with conventional methods. In particular, large organizations have required considerable effort and time to extract necessary information from a large amount of data and to process and display it appropriately. The present invention aims to solve these problems and provide a system that enables easy and efficient acquisition and display of information.

[0739] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0740] In this invention, the server includes means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, means for converting search results into structured data, means for processing search results in JSON format, and means for displaying search results. This allows a user to input information about specific sales channels or measures through a web browser, the server to search a database based on this information and return the results obtained in JSON format to the terminal, which then parses and displays the results visually.

[0741] "Means of inputting information" refers to devices or software that provide an interface for users to input the information they need.

[0742] "Means of transmitting information" refers to devices or software used to transfer information entered by a user to a server.

[0743] "Means of searching a database" refers to devices or software that find records within a database based on specified conditions.

[0744] "Means for obtaining search results" refers to devices or software that receive the results of a database search.

[0745] "Means for converting search results into structured data" refers to devices or software that convert acquired data into structured data such as JSON format.

[0746] "Means of processing search results in JSON format" refers to devices or software that process data in JSON format as structured data.

[0747] "Means for displaying search results" refers to devices or software that display search results in a way that allows users to visually confirm the information.

[0748] A "web browser" is software used to access and display websites on the internet.

[0749] A "GET request" is one of the HTTP request methods that a client sends to retrieve resources from a server.

[0750] This invention relates to a system in which information is input and transmitted, a server searches a database, retrieves the search results, and presents them to the user. The purpose of this system is to quickly and accurately obtain information such as the names of persons in charge of specific sales channels or initiatives, and the contact points for event ordering.

[0751] This system is implemented using the following procedure.

[0752] The user accesses a specific URL using a web browser and enters specific information into the displayed form. For example, the user enters "Major electronics retailer" in the `store_type` field and "BB campaign" in the `promotion_type` field. After completing the input, the user clicks the "Search" button. The system then retrieves the user's input and sends it to the server.

[0753] The server receives requests sent from the terminal. Specifically, the server receives the store_type and promotion_type information entered by the user as an HTTP GET request. The server uses JavaScript or Ajax for this process. The relational database used is a common one, such as MySQL or PostgreSQL. The server uses these parameters to search the database. This search is performed by executing queries against specific tables within the database, and matching records are retrieved.

[0754] Next, the server converts the search results into JSON format and sends them to the terminal as structured data. This ensures data consistency and enables rapid data processing.

[0755] The terminal receives a response from the server and parses the data in JSON format. Then, based on the parsed data, it displays information that the user can visually confirm through their browser. This display is done using HTML, CSS, and JavaScript. This allows the user to obtain information such as the name of the person in charge and the contact point for ordering in real time.

[0756] As a concrete example, consider a case where a user enters "Major Electronics Retailer" for `store_type` and "BB" for `promotion_type`. This information is sent from the terminal to the server, which searches the database and retrieves the name of the person in charge corresponding to the "BB promotion" for the "Major Electronics Retailer". This retrieved person in charge name is converted to JSON format and sent back to the terminal. The terminal parses this information and displays the person in charge name to the user.

[0757] Example of a prompt:

[0758] The user entered "Major Electronics Retailer" in the `store_type` field and "BB Promotion" in the `promotion_type` field on a web form and clicked the "Search" button. This caused the device to send a GET request to the server containing this input information. The server searched the relational database and retrieved the names of the personnel responsible for "BB Promotion" at "Major Electronics Retailer" in JSON format. The device then parsed this JSON data and displayed the personnel names to the user.

[0759] This invention allows users to quickly and accurately obtain information on specific sales channels and strategies, significantly improving operational efficiency.

[0760] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0761] Step 1: Enter Information

[0762] The user accesses a specific URL using a web browser and enters information into the displayed form. For example, they might enter "Major electronics retailer" in the `store_type` field and "BB campaign" in the `promotion_type` field. Once the user has finished entering the information, they click the "Search" button.

[0763] Input: store_type and promotion_type information

[0764] Output: Information entered into the terminal

[0765] Step 2: Send Information

[0766] The device retrieves the information entered by the user and prepares to send it to the server. Specifically, it uses JavaScript to collect the information and sends it to the server's endpoint as an HTTP GET request.

[0767] Input: Information on store_type and promotion_type entered by the user.

[0768] Output: Data included in the GET request to the server

[0769] Specific operation: Use JavaScript to retrieve form data and send it to the server using Ajax.

[0770] Step 3: Request reception and database search

[0771] The server receives a GET request from the terminal and retrieves the `store_type` and `promotion_type` parameters contained within it. It then connects to the relational database and searches for data that matches these parameters.

[0772] Input: Information about store_type and promotion_type included in the GET request

[0773] Output: Search results retrieved from the database

[0774] Specific operation: The server executes a query against a relational database (e.g., MySQL) and retrieves matching records.

[0775] Step 4: Retrieve search results and convert to JSON

[0776] The server extracts the necessary information based on the search results obtained from the database and converts it into JSON format, which is structured data.

[0777] Input: Database search results

[0778] Output: Data converted to JSON format

[0779] Specific operation: Select the necessary fields from the search results and format them as a JSON string.

[0780] Step 5: Send Response

[0781] The server sends the data, converted to JSON format, to the terminal as a response.

[0782] Input: Search results converted to JSON format

[0783] Output: Response to terminal

[0784] Specific operation: The server sends JSON data back to the terminal as an HTTP response.

[0785] Step 6: Response received and data displayed

[0786] The terminal receives a response from the server and parses the received JSON data. Then, based on the parsed data, it displays the search results in the user's web browser.

[0787] Input: JSON data received from the server

[0788] Output: Search results displayed to the user

[0789] Specific operation: Use JavaScript to parse JSON data and display the results on the screen using HTML and CSS.

[0790] The above outlines the specific processing flow of this system's program. This process allows users to quickly and accurately obtain information such as the names of contact persons and ordering contacts related to specific sales channels and initiatives.

[0791] (Application Example 1)

[0792] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0793] In logistics centers, it is essential to quickly and accurately obtain necessary contact information (names and contact details for specific departments or projects). However, this information is scattered across multiple systems, resulting in time-consuming and inefficient data collection. Furthermore, there is a risk of obtaining incorrect information, which can hinder business operations. A solution to these problems is needed.

[0794] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0795] In this invention, the server includes means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, means for displaying search results, means for obtaining information related to the storage and movement of items, and means for displaying the obtained information on a user device. This allows the user to easily search for and obtain the desired contact person information, enabling rapid business processing and accurate information transmission.

[0796] "Means of inputting information" refers to an interface that allows users to input necessary information (such as department name or project name) on their device.

[0797] "Means of transmitting information" refers to a mechanism for transmitting information entered by a user to a remote server or other device.

[0798] A "means of searching a database" is a processing device that finds relevant information from stored data, such as a relational database, based on the information that has been transmitted.

[0799] "Means of obtaining search results" refers to the process of retrieving information retrieved from a database and converting it into a usable format.

[0800] "Means for displaying search results" refers to an interface that visually displays the retrieved search results to the user in an easy-to-understand manner.

[0801] "Means for acquiring information related to the handling of storage and movement of goods" refers to the function of collecting information related to goods stored in logistics centers or goods being moved.

[0802] "Means for displaying acquired information on a user device" refers to a mechanism for displaying collected information on a user's device, such as a smartphone or personal computer.

[0803] This invention is a system for quickly and accurately obtaining necessary personnel information at a logistics center. The system includes means for a user to input information, means for transmitting information, means for searching a database, means for obtaining search results, means for displaying search results, means for obtaining information related to the storage and movement of goods, and means for displaying the obtained information on a user device.

[0804] Program Processing Description

[0805] In this system, users input necessary information (such as department name and project name) using a smartphone application. The entered information is then sent to the server via a data transmission method. For example, GET requests or POST requests are used for data transmission.

[0806] The server searches the database based on the received information. This database search process uses technologies such as SQL queries. The search results are converted to JSON format and sent from the server to the user's device.

[0807] The user device parses the received JSON data and visually displays necessary information such as the person in charge's name and contact details. This parsing and display can be done using programming languages ​​such as JavaScript or Python. This allows users to obtain accurate information in real time and perform business processes efficiently.

[0808] Specific example

[0809] For example, consider a scenario where a user searches for a "warehouse management manager" at a logistics center. The user opens a smartphone application and enters "warehouse management" and "inventory management" into the search form. This input is sent to a server, which searches the corresponding database and retrieves the relevant contact information in JSON format. The retrieved information is then sent back to the user's device, displaying the contact person's name and contact details.

[0810] Example of a prompt:

[0811] Please use the following information to search for the contact person at the logistics center.

[0812] Department: Warehouse Management

[0813] Project name: Inventory Clearance

[0814] Thus, by using this system, information retrieval in logistics centers will become easier, and it is expected that operational efficiency will improve dramatically.

[0815] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0816] Step 1:

[0817] The user opens the smartphone application and enters the necessary information (e.g., department name or project name) into the search form. Input is done through text fields, and each field displays a relevant label. The user's input is sent to the device as specific strings such as "warehouse management" or "inventory management."

[0818] Step 2:

[0819] The terminal retrieves the information entered by the user and prepares it for transmission. A program such as JavaScript or Python is executed here, converting the input information into a JSON object. This JSON object is then sent to the server endpoint in the form of a GET or POST request.

[0820] Step 3:

[0821] The server analyzes the request received from the terminal and extracts the included parameters (such as department name and project name). Based on the extracted information, it executes an SQL query against the relational database to search for the relevant records. For example, it searches for information on the person in charge related to the "Inventory Management Project in the Warehouse Management Department".

[0822] Step 4:

[0823] The server retrieves the search results and converts them into JSON format. In this step, it extracts the necessary information (such as the person in charge's name and contact details) from the search result records and structures it into a JSON object. The generated JSON object is sent to the terminal as a response.

[0824] Step 5:

[0825] The terminal receives a response from the server and parses the received JSON data. Using JavaScript or Python code, it converts the JSON data into an object format and extracts the necessary information (such as the person in charge's name and contact information). This information is then displayed on the screen in a format that the user can visually confirm.

[0826] Step 6:

[0827] Users view the contact person information displayed on their device screen and take the necessary action (for example, contact the contact person). Specifically, the contact person's name and contact information are displayed in a list format, and links or buttons are provided for direct contact as needed.

[0828] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0829] This invention relates to a system that includes means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, means for displaying search results, and an emotion engine that recognizes the user's emotions. The purpose of this system is to quickly and accurately obtain the names of persons in charge of specific sales channels or measures and event ordering contacts, and to provide search results that take the user's emotions into consideration.

[0830] Specific Examples of the System

[0831] This system works by having the user input information via a web browser and send it to the server. The server searches a database based on the received information and analyzes the user's emotions using an emotion engine. The search results are returned to the terminal in JSON format and displayed after being adjusted according to the user's emotions.

[0832] User input

[0833] Users access a specific URL using a web browser and enter the required information (e.g., specific sales channels and campaign types) into the displayed form. The input fields also include a field for users to enter text comments, allowing them to express their feelings. Once the user provides this input data, they click the "Search" button to begin processing.

[0834] Information transmission by terminal

[0835] The device uses JavaScript or similar methods to retrieve data entered by the user. This data is sent as parameters in a GET request to the specified server endpoint. For example, the URL might be / api / retrieve_representative?store_type=major electronics retailer&promotion_type=BB&comment=please respond quickly.

[0836] Server-based database search

[0837] The server receives a request sent from the terminal. The request includes the store_type (type of sales channel), promotion_type (type of promotion), and comment (user comment) entered by the user. The server uses these parameters to connect to the relational database and search for the corresponding record.

[0838] Sentiment analysis and result retrieval by the server

[0839] The server uses a sentiment engine to analyze the sentiment of user comments. The sentiment engine analyzes the user's comment text to identify the degree and type of emotion. For example, it can detect emotions such as "strong request" or "dissatisfaction" from user comments. Based on this information, the server adjusts or filters the search results.

[0840] Server retrieves and processes search results.

[0841] The server retrieves the query results and extracts matching contact names and order contact information. This information is converted to JSON format, and necessary adjustments are made based on the sentiment analysis results. For example, if a user expresses dissatisfaction, the server prioritizes providing the names of contacts who are likely to provide more courteous service.

[0842] Displaying search results by device

[0843] The terminal receives a response from the server and parses the JSON data. Since the results of sentiment analysis are also included, they are presented to the user in an appropriate format. For example, if there is a comment that says "Please respond quickly," the search results will be displayed as "High priority personnel."

[0844] Specific example

[0845] For example, if a user enters "Major Electronics Retailer" as the store_type, "BB" as the promotion_type, and "Please respond quickly" as a comment, and then searches, the device sends this information to the server as a GET request. The server searches the relational database and retrieves the name of the person in charge of the "BB" promotion at the "Major Electronics Retailer". At the same time, the sentiment engine analyzes the user comment to determine that it is requesting a "quick response". Based on this, the server selects the most suitable person in charge and returns the result to the device in JSON format. The device then analyzes this result and displays the most suitable person in charge to the user.

[0846] This system allows users to quickly and accurately obtain the information they need, as well as receive appropriate responses tailored to their emotions and expectations. This leads to improved customer satisfaction and a dramatic increase in work efficiency.

[0847] The following describes the processing flow.

[0848] Step 1:

[0849] The user opens a web browser and accesses a specific URL. The page displays forms for entering `store_type` and `promotion_type`, as well as a comment section. The user enters the data into these input fields and clicks the "Search" button.

[0850] Step 2:

[0851] The terminal retrieves user input. The form contents are read using a client-side scripting language such as JavaScript. For example, if the user enters "Major electronics retailer" for `store_type`, "BB" for `promotion_type`, and "Please respond quickly" in the comments field, this information will be stored in a variable.

[0852] Step 3:

[0853] The data acquired by the device is sent as parameters to the endpoint / api / retrieve_representative_with_emotion in a GET request. Specifically, the URL will be / api / retrieve_representative_with_emotion?store_type=major electronics retailer&promotion_type=BB&comment=please respond quickly.

[0854] Step 4:

[0855] The server receives a GET request. The server extracts the values ​​of the request parameters store_type, promotion_type, and comment. For example, it verifies that store_type is "Major electronics retailer", promotion_type is "BB", and comment is "Please respond quickly".

[0856] Step 5:

[0857] The server establishes a database connection. It uses a relational database to query the ptn_representatives table in the database.

[0858] Step 6:

[0859] The server generates the query, sets the parameters, and executes the query. The query will look like this:

[0860] SQL

[0861] SELECT representative_name FROM ptn_representatives WHERE store_type = 'Major Electronics Retailer' AND promotion_type = 'BB'

[0862] The server searches for the relevant record.

[0863] Step 7:

[0864] The server retrieves the search results. If a matching record is found, the name of the person in charge is retrieved as a result. For example, "Taro Tanaka" might be retrieved as the person in charge's name.

[0865] Step 8:

[0866] The server uses an emotion engine to analyze the sentiment from user comments. The emotion engine analyzes the comment "Please respond quickly" and detects the user's strong request.

[0867] Step 9:

[0868] The server adjusts or filters search results based on the sentiment analysis results. For example, if a strong user request is detected, a high-priority contact person is selected. In this case, "Taro Tanaka" would be selected as the high-priority contact person.

[0869] Step 10:

[0870] The server converts the retrieved representative name into JSON format. For example, the result might be {"representative_name": "Taro Tanaka"}. If no matching record is found, an error message {"error": "No representative found"} is generated.

[0871] Step 11:

[0872] The server returns a JSON response to the terminal. The HTTP response specifies Content-Type as application / json and sends back a response containing JSON data.

[0873] Step 12:

[0874] The terminal receives a response from the server. It then uses technologies such as JavaScript to analyze the response data.

[0875] Step 13:

[0876] The terminal displays the analysis results on the screen. Based on the received JSON data, it visually presents the user with the name of the person in charge or an error message. For example, if the person in charge's name is "Taro Tanaka," then "Person in Charge: Taro Tanaka" will be displayed on the screen. The user's sentiment analysis results will also be displayed, so a message such as "A prompt response was expected" may also be shown.

[0877] (Example 2)

[0878] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0879] Traditional information retrieval systems often provide search results without considering user emotions or needs, which can lead to decreased user satisfaction. Furthermore, they struggle to provide appropriate information to users who require quick and accurate responses, resulting in a lack of improvement in operational efficiency.

[0880] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0881] In this invention, the server includes means for inputting information, means for transmitting information, means for searching a database, means for analyzing emotions, means for adjusting search results, means for obtaining search results, and means for displaying search results. This makes it possible to provide optimal information while taking the user's emotions into consideration, thereby improving customer satisfaction and operational efficiency.

[0882] "Means of inputting information" refers to an interface for users to input necessary information, such as a form in a web browser.

[0883] "Means of transmitting information" refers to the mechanism for sending data entered by a user to a server, which may include using a GET request, for example.

[0884] "Means of searching a database" refers to a mechanism that searches for relevant information from relational and non-relational databases based on the input data.

[0885] "Means of analyzing emotions" refers to engines or software that analyze emotions from user-inputted comments, such as generative AI models.

[0886] "Means of adjusting search results" refers to mechanisms that prioritize or filter search results based on the results of sentiment analysis.

[0887] "Means for obtaining search results" refers to a mechanism for collecting information extracted from a database and using it for subsequent processing.

[0888] "Means of displaying search results" refers to the interface used to visualize the final retrieved search results for the user, such as the display component of a web page.

[0889] The present invention is a system for quickly and accurately obtaining information requested by a user and presenting it appropriately while taking the user's emotions into consideration. This system includes means for inputting information, means for transmitting information, means for searching a database, means for analyzing emotions, means for adjusting search results, means for obtaining search results, and means for displaying search results.

[0890] User input

[0891] The user accesses a specific URL through a web browser and enters the required information into a form. This form includes fields for "Sales Channel Type," "Measure Type," and "Comments." The comments field allows the user to write their feelings or requests. For example, let's assume the user selects "Major Electronics Retailer" as the sales channel type, "BB" as the measure type, and enters the comment "Please respond quickly."

[0892] Information transmission by terminal

[0893] The device uses JavaScript to retrieve the data entered by the user and sends it as a parameter to the specified server endpoint in a GET request. A concrete example request URL would be / api / retrieve_representative?store_type=major electronics retailer&promotion_type=BB&comment=please respond quickly.

[0894] Server-based database search

[0895] The server receives a request sent from the terminal. This request contains the information entered by the user: store_type, promotion_type, and comment. The server uses these parameters to connect to a relational database (such as MySQL) and retrieve the corresponding record.

[0896] Server-based sentiment analysis

[0897] The server uses an emotion engine (e.g., IBM Watson Tone Analyzer) to analyze the sentiment of a user's comment text. The analysis results include emotions such as "strong request for a quick response" or "dissatisfaction." For example, a comment like "Please respond quickly" might be interpreted as a "strong request."

[0898] Server generates and sends search results.

[0899] The server converts the contact person names and order contact information retrieved from the database into JSON format and adjusts the information based on the sentiment analysis results. For example, if a user indicates a "strong request for a quick response," the server adjusts the information to provide contact person information with a higher priority. This data is ultimately returned to the terminal in JSON format.

[0900] Displaying search results by device

[0901] The terminal parses the JSON data received from the server and displays the search results to the user in an appropriate format. For example, if there is a comment that says "Please respond quickly," the result will be displayed as "High priority person in charge."

[0902] Specific example

[0903] For example, if a user enters "Major electronics retailer" as the store_type, "BB" as the promotion_type, and "Please respond quickly" as a comment, the device sends this information to the server as a GET request. The server searches the relational database and retrieves the name of the person in charge of the "BB" promotion at the "Major electronics retailer". At the same time, the sentiment engine analyzes the user's comment to determine that it requests a "quick response". Based on this, the server selects the most suitable person in charge and returns it to the device as a result in JSON format. The device then analyzes this result and displays the most suitable person in charge to the user.

[0904] Example of a prompt

[0905] Send the following information as a GET request to the URL:

[0906] store_type: Major consumer electronics retailer

[0907] promotion_type: BB

[0908] Comment: Please respond promptly.

[0909] Search the database for the relevant person in charge and analyze the comments using a sentiment engine. Then, return the search results in JSON format.

[0910] This system allows users to quickly and accurately obtain the information they need and receive appropriate responses that meet their emotions and expectations. This leads to improved customer satisfaction and increased operational efficiency.

[0911] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0912] Step 1:

[0913] The user accesses a specific URL using a web browser and enters the required information into the displayed form. Specifically, they fill in the fields for "Sales Channel Type," "Measure Type," and "Comments." Once they have finished entering the information, they click the "Search" button.

[0914] Input: Information entered by the user in the form (e.g., store_type, promotion_type, comment)

[0915] Output: User input data acquired by the terminal

[0916] Step 2:

[0917] The device uses JavaScript to retrieve data entered by the user into a form. This retrieved data is then sent as parameters to a GET request to the specified server endpoint.

[0918] Input: User input data

[0919] Output: Data in GET request format sent to the server

[0920] Specific actions:

[0921] The device retrieves the user's form input data using JavaScript.

[0922] Generate a GET request URL (e.g., / api / retrieve_representative?store_type=major electronics retailer&promotion_type=BB&comment=please respond quickly).

[0923] Send data to the server.

[0924] Step 3:

[0925] The server receives a GET request sent from the terminal. It extracts and parses the parameters store_type, promotion_type, and comment included in the request.

[0926] Input: GET request data from the terminal

[0927] Output: Extracted parameters (store_type, promotion_type, comment)

[0928] Specific actions:

[0929] The server receives a GET request.

[0930] Extract parameters from the request (e.g., store_type=Major electronics retailer, promotion_type=BB, comment=Please respond quickly).

[0931] Step 4:

[0932] The server uses the extracted parameters to connect to a relational database (e.g., MySQL) and search for the relevant records.

[0933] Input: Extracted parameters

[0934] Output: Search results from the database

[0935] Specific actions:

[0936] Generate a database query based on the extracted parameters.

[0937] Execute a database query to find the relevant record.

[0938] Retrieve search results.

[0939] Step 5:

[0940] The server uses a sentiment engine (e.g., IBM Watson Tone Analyzer) to analyze user comments. It analyzes the comment text to identify the degree and type of sentiment.

[0941] Input: User's comment text

[0942] Output: Results of sentiment analysis (e.g., strong demands, dissatisfaction, etc.)

[0943] Specific actions:

[0944] Send user comment text to the sentiment engine.

[0945] The emotion engine analyzes the text to identify the type and degree of emotion.

[0946] Obtain the emotion analysis results.

[0947] Step 6:

[0948] The server converts the search results retrieved from the database into JSON format and makes adjustments based on the sentiment analysis results. The adjusted results are then sent to the terminal.

[0949] Input: Database search results, sentiment analysis results

[0950] Output: Search results in adjusted JSON format

[0951] Specific actions:

[0952] Convert the search results retrieved from the database into JSON format.

[0953] The search results are adjusted based on sentiment analysis results (e.g., prioritizing the provision of information on high-priority contacts).

[0954] The adjusted results will be sent to the device.

[0955] Step 7:

[0956] The terminal parses the JSON data received from the server and displays the search results to the user in an appropriate format.

[0957] Input: JSON data received from the server

[0958] Output: Search results displayed to the user

[0959] Specific actions:

[0960] The system parses the JSON data received from the server.

[0961] The results are passed to a UI component for visualization to the user.

[0962] Display the search results (e.g., display as "Responsible person who can be expected to respond quickly").

[0963] (Application Example 2)

[0964] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0965] Traditional systems suffered from a lack of user satisfaction because they could not provide search results that reflected the user's emotions or expectations, even after they entered information. Furthermore, in situations requiring quick and accurate responses, systems that did not consider emotions made it difficult to select the appropriate person to handle the situation.

[0966] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, means for displaying search results, and an emotion analysis engine for analyzing the user's emotions. This makes it possible to adjust the search results based on the user's emotions.

[0967] "Means of inputting information" refers to the interface through which users input necessary information into a system, such as web browsers and smartphone applications.

[0968] "Means of transmitting information" refers to communication methods used to send information entered by a user to a server, specifically using HTTP requests such as GET requests.

[0969] "Methods for searching a database" refers to functions that allow the server to retrieve relevant data from a database based on the information it receives.

[0970] "Means for obtaining search results" refers to the function that allows the server to receive the results of a database search and process those results as appropriate.

[0971] "Means of displaying search results" refers to the interface used to display the retrieved search results to the user, such as the screen of a web browser or a smartphone application.

[0972] A "sentiment analysis engine" is a software component that analyzes emotions from user input text and identifies the degree and type of emotion.

[0973] "Means of adjusting search results based on user sentiment" refers to a function that appropriately filters or prioritizes search results based on sentiment information obtained by a sentiment analysis engine.

[0974] This invention relates to a system including means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, means for displaying search results, and an emotion analysis engine for analyzing the user's emotions. This system allows users to quickly and accurately obtain the information they need and receive appropriate responses that match their emotions and expectations.

[0975] Specific examples

[0976] User input

[0977] Users access a specific screen using a smartphone application and enter the required information into the displayed form. The input fields also include a field for users to enter text comments, allowing them to express their feelings. Once the user provides this input data, they tap the "Search" button to begin processing.

[0978] Information transmission by terminal

[0979] The device uses JavaScript or similar methods to retrieve data entered by the user. This data is sent as parameters in an HTTP GET request to the specified server endpoint. For example, the URL might be / api / retrieve_representative?store_type=large retail store&promotion_type=promotion Type A&comment=urgent action required.

[0980] Server-based database search

[0981] The server receives a request sent from the terminal. The request includes the store_type (type of sales channel), promotion_type (type of promotion), and comment (user comment) entered by the user. The server uses these parameters to connect to the relational database and search for the corresponding record.

[0982] Sentiment analysis and result retrieval by the server

[0983] The server uses a sentiment analysis engine to analyze the emotions expressed in user comments. The sentiment analysis engine analyzes the user's comment text to identify the degree and type of emotion. For example, it can detect emotions such as "strong demand" or "dissatisfaction" from user comments. Based on this information, the server adjusts or filters the search results.

[0984] Server retrieves and processes search results.

[0985] The server retrieves the query results and extracts matching contact names and order contact information. This information is converted to JSON format, and necessary adjustments are made based on the sentiment analysis results. For example, if a user expresses dissatisfaction, the server prioritizes providing the names of contacts who are likely to provide more courteous service.

[0986] Displaying search results by device

[0987] The terminal receives a response from the server and parses the JSON data. Since the results of sentiment analysis are also included, they are presented to the user in an appropriate format. For example, if there is a comment that says "urgent action required," the search results will be displayed as "high priority personnel."

[0988] Specific examples

[0989] For example, if a user enters "Large Retail Store" as the store_type, "Promotion Type A" as the promotion_type, and "I need immediate action" as the comment, the device sends this information to the server as a GET request. The server searches the relational database and retrieves the name of the person in charge of the "Promotion Type A" initiative for the "Large Retail Store". At the same time, the sentiment analysis engine analyzes the user's comment as requesting "immediate action". Based on this, the server selects the most suitable person in charge and returns it to the device as a result in JSON format. The device then analyzes this result and displays the most suitable person in charge to the user.

[0990] Example of a prompt

[0991] User comment: "We need an immediate response."

[0992] Analysis result: Due to the high emotional score, the priority will be set to "High".

[0993] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0994] Step 1:

[0995] The user opens the smartphone application, accesses a specific screen, and enters the required information into the provided form. The input fields include "Sales Channel Type," "Measure Type," and a "Comment Field." Once the user enters this data and taps the "Search" button, the device is ready to proceed to the next step.

[0996] Step 2:

[0997] The terminal retrieves the data entered by the user and sends it to the server as parameters in an HTTP GET request. Specifically, it uses a script such as JavaScript to collect the input data and sends it to the server endpoint in URL format. For example, if you enter "Large-scale retail store" for store_type, "Promotion Type A" for promotion_type, and "Immediate action required" for comment, the following URL will be generated: / api / retrieve_representative?store_type=Large-scale retail store&promotion_type=Promotion Type A&comment=Immediate action required

[0998] Step 3:

[0999] The server parses the request received from the terminal and extracts the request parameters. These extracted parameters include store_type, promotion_type, and comment. Based on these parameters, the server connects to the relational database and searches for the relevant records. This search process extracts contact persons and ordering contact information that have a high degree of accuracy.

[1000] Step 4:

[1001] The server activates a sentiment analysis engine to analyze user comments and calculates a sentiment score from the comment text. The sentiment analysis engine (for example, a natural language processing library such as TextBlob) analyzes the user's text and identifies the degree of emotion, such as positive, negative, or neutral. For example, a comment like "I need immediate action" would receive a high positive sentiment score as a strong request.

[1002] Step 5:

[1003] The server combines database search results with sentiment analysis results and adjusts search results based on the user's emotions. Specifically, if the sentiment score is high, it prioritizes selecting the names of personnel who can be expected to respond more quickly, and filters or prioritizes the results accordingly. These results are converted into JSON format.

[1004] Step 6:

[1005] The terminal receives the search results in JSON format returned from the server and parses them. The parsed search results are then presented to the user in an appropriate format. For example, if a result is tagged with "Priority: High," a message such as "This person is available to handle your request with high priority" will be displayed on the screen. Based on this, the user can receive a prompt response.

[1006] Through the above processing flow, the system can provide optimal search results that meet the user's emotions and expectations, enabling a quick and appropriate response.

[1007] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1008] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1009] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1010] [Fourth Embodiment]

[1011] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1012] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1013] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1014] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1015] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1016] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1017] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1018] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1019] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1020] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1021] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1022] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1023] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1024] This invention relates to a system that includes means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, and means for displaying search results. The purpose of this system is to quickly and accurately obtain the names of persons in charge of specific sales channels or measures, as well as event ordering contacts.

[1025] Specific Examples of the System

[1026] This system works by having the user input information via a web browser and send it to the server. The server searches a database based on the received information and returns the search results to the terminal in JSON format. This entire process will be explained in detail.

[1027] User input

[1028] The user accesses a specific URL using a web browser and enters the required information (e.g., specific sales channels and campaign types) into the displayed form. Once the user has finished entering the information, they click the "Search" button to begin the process.

[1029] Information transmission by terminal

[1030] The terminal uses a program such as JavaScript to retrieve information entered by the user. This information is sent as parameters in a GET request to the specified server endpoint.

[1031] Server-based database search

[1032] The server receives a request sent from the terminal. The request includes the store_type (type of sales channel) and promotion_type (type of promotion) entered by the user. The server uses these parameters to connect to the relational database and search for the corresponding record.

[1033] Server retrieves and processes search results.

[1034] The server retrieves the query results and extracts matching contact names and ordering contact information. This result is converted into JSON format and made available as structured data. The server returns this JSON data to the terminal as a response.

[1035] Displaying search results by device

[1036] The terminal receives a response from the server and parses the received JSON data. Based on this data, it displays information such as the name of the person in charge and the ordering contact point so that the user can visually confirm it through their browser. This allows the user to easily obtain the latest information in real time.

[1037] Specific example

[1038] For example, if a user enters "Major Electronics Retailer" for `store_type` and "BB" for `promotion_type`, the device sends this information to the server as a GET request. The server searches the relational database and retrieves the name of the person in charge of the "BB" promotion at the "Major Electronics Retailer". The retrieved name is converted to JSON format and returned to the device. The device parses the received JSON data and displays the name of the person in charge to the user.

[1039] In this way, the system of the present invention enables users to easily and quickly obtain the names of contact persons and event ordering contacts related to specific sales channels and initiatives. This system significantly improves the efficiency and accuracy of work and prevents the use of incorrect information.

[1040] The following describes the processing flow.

[1041] Step 1:

[1042] The user opens a web browser and accesses a specific URL. The page displays a form for entering `store_type` and `promotion_type`. The user enters the data into these input fields and clicks the "Search" button.

[1043] Step 2:

[1044] The terminal receives user input. The form contents are read using a client-side scripting language such as JavaScript. For example, if "Major Electronics Retailer" is entered for `store_type` and "BB" for `promotion_type`, this information is stored in variables.

[1045] Step 3:

[1046] The data acquired by the device is sent as parameters in a GET request to the endpoint / api / retrieve_representative. Specifically, the URL will be / api / retrieve_representative?store_type=major electronics retailer&promotion_type=BB.

[1047] Step 4:

[1048] The server receives a GET request. The server extracts the request parameters store_type and promotion_type. For example, it verifies that store_type is "Major Electronics Retailer" and promotion_type is "BB".

[1049] Step 5:

[1050] The server establishes a database connection. It then uses a relational database such as SQLite to query the ptn_representatives table in the database.

[1051] Step 6:

[1052] The server generates the SQL query, sets the parameters, and executes the query. The query will look like this:

[1053] SQL

[1054] SELECT representative_name FROM ptn_representatives WHERE store_type = 'Major Electronics Retailer' AND promotion_type = 'BB'

[1055] The server searches for the relevant record.

[1056] Step 7:

[1057] The server retrieves the search results. If a matching record is found, the name of the person in charge is retrieved as a result. For example, "Taro Tanaka" might be retrieved as the person in charge's name.

[1058] Step 8:

[1059] The server converts the retrieved representative name into JSON format. For example, the result might be {"representative_name": "Taro Tanaka"}. If no matching record is found, an error message {"error": "No representative found"} is generated.

[1060] Step 9:

[1061] The server returns a JSON response to the terminal. The HTTP response specifies Content-Type as application / json and sends back a response containing JSON data.

[1062] Step 10:

[1063] The terminal receives a response from the server. It then uses technologies such as JavaScript to analyze the response data.

[1064] Step 11:

[1065] The terminal displays the analysis results on the screen. Based on the received JSON data, it visually presents the user with the name of the person in charge or an error message. For example, if the person in charge's name is "Taro Tanaka," then "Person in Charge: Taro Tanaka" will be displayed on the screen.

[1066] (Example 1)

[1067] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1068] It is crucial to quickly and accurately obtain information such as the names of contact persons and ordering channels related to sales channels and strategies within companies and other organizations, but this has been difficult with conventional methods. In particular, large organizations have required considerable effort and time to extract necessary information from a large amount of data and to process and display it appropriately. The present invention aims to solve these problems and provide a system that enables easy and efficient acquisition and display of information.

[1069] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1070] In this invention, the server includes means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, means for converting search results into structured data, means for processing search results in JSON format, and means for displaying search results. This allows a user to input information about specific sales channels or measures through a web browser, the server to search a database based on this information and return the results obtained in JSON format to the terminal, which then parses and displays the results visually.

[1071] "Means of inputting information" refers to devices or software that provide an interface for users to input the information they need.

[1072] "Means of transmitting information" refers to devices or software used to transfer information entered by a user to a server.

[1073] "Means of searching a database" refers to devices or software that find records within a database based on specified conditions.

[1074] "Means for obtaining search results" refers to devices or software that receive the results of a database search.

[1075] "Means for converting search results into structured data" refers to devices or software that convert acquired data into structured data such as JSON format.

[1076] "Means of processing search results in JSON format" refers to devices or software that process data in JSON format as structured data.

[1077] "Means for displaying search results" refers to devices or software that display search results in a way that allows users to visually confirm the information.

[1078] A "web browser" is software used to access and display websites on the internet.

[1079] A "GET request" is one of the HTTP request methods that a client sends to retrieve resources from a server.

[1080] This invention relates to a system in which information is input and transmitted, a server searches a database, retrieves the search results, and presents them to the user. The purpose of this system is to quickly and accurately obtain information such as the names of persons in charge of specific sales channels or initiatives, and the contact points for event ordering.

[1081] This system is implemented using the following procedure.

[1082] The user accesses a specific URL using a web browser and enters specific information into the displayed form. For example, the user enters "Major electronics retailer" in the `store_type` field and "BB campaign" in the `promotion_type` field. After completing the input, the user clicks the "Search" button. The system then retrieves the user's input and sends it to the server.

[1083] The server receives requests sent from the terminal. Specifically, the server receives the store_type and promotion_type information entered by the user as an HTTP GET request. The server uses JavaScript or Ajax for this process. The relational database used is a common one, such as MySQL or PostgreSQL. The server uses these parameters to search the database. This search is performed by executing queries against specific tables within the database, and matching records are retrieved.

[1084] Next, the server converts the search results into JSON format and sends them to the terminal as structured data. This ensures data consistency and enables rapid data processing.

[1085] The terminal receives a response from the server and parses the data in JSON format. Then, based on the parsed data, it displays information that the user can visually confirm through their browser. This display is done using HTML, CSS, and JavaScript. This allows the user to obtain information such as the name of the person in charge and the contact point for ordering in real time.

[1086] As a concrete example, consider a case where a user enters "Major Electronics Retailer" for `store_type` and "BB" for `promotion_type`. This information is sent from the terminal to the server, which searches the database and retrieves the name of the person in charge corresponding to the "BB promotion" for the "Major Electronics Retailer". This retrieved person in charge name is converted to JSON format and sent back to the terminal. The terminal parses this information and displays the person in charge name to the user.

[1087] Example of a prompt:

[1088] The user entered "Major Electronics Retailer" in the `store_type` field and "BB Promotion" in the `promotion_type` field on a web form and clicked the "Search" button. This caused the device to send a GET request to the server containing this input information. The server searched the relational database and retrieved the names of the personnel responsible for "BB Promotion" at "Major Electronics Retailer" in JSON format. The device then parsed this JSON data and displayed the personnel names to the user.

[1089] This invention allows users to quickly and accurately obtain information on specific sales channels and strategies, significantly improving operational efficiency.

[1090] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1091] Step 1: Enter Information

[1092] The user accesses a specific URL using a web browser and enters information into the displayed form. For example, they might enter "Major electronics retailer" in the `store_type` field and "BB campaign" in the `promotion_type` field. Once the user has finished entering the information, they click the "Search" button.

[1093] Input: store_type and promotion_type information

[1094] Output: Information entered into the terminal

[1095] Step 2: Send Information

[1096] The device retrieves the information entered by the user and prepares to send it to the server. Specifically, it uses JavaScript to collect the information and sends it to the server's endpoint as an HTTP GET request.

[1097] Input: Information on store_type and promotion_type entered by the user.

[1098] Output: Data included in the GET request to the server

[1099] Specific operation: Use JavaScript to retrieve form data and send it to the server using Ajax.

[1100] Step 3: Request reception and database search

[1101] The server receives a GET request from the terminal and retrieves the `store_type` and `promotion_type` parameters contained within it. It then connects to the relational database and searches for data that matches these parameters.

[1102] Input: Information about store_type and promotion_type included in the GET request

[1103] Output: Search results retrieved from the database

[1104] Specific operation: The server executes a query against a relational database (e.g., MySQL) and retrieves matching records.

[1105] Step 4: Retrieve search results and convert to JSON

[1106] The server extracts the necessary information based on the search results obtained from the database and converts it into JSON format, which is structured data.

[1107] Input: Database search results

[1108] Output: Data converted to JSON format

[1109] Specific operation: Select the necessary fields from the search results and format them as a JSON string.

[1110] Step 5: Send Response

[1111] The server sends the data, converted to JSON format, to the terminal as a response.

[1112] Input: Search results converted to JSON format

[1113] Output: Response to terminal

[1114] Specific operation: The server sends JSON data back to the terminal as an HTTP response.

[1115] Step 6: Response received and data displayed

[1116] The terminal receives a response from the server and parses the received JSON data. Then, based on the parsed data, it displays the search results in the user's web browser.

[1117] Input: JSON data received from the server

[1118] Output: Search results displayed to the user

[1119] Specific operation: Use JavaScript to parse JSON data and display the results on the screen using HTML and CSS.

[1120] The above outlines the specific processing flow of this system's program. This process allows users to quickly and accurately obtain information such as the names of contact persons and ordering contacts related to specific sales channels and initiatives.

[1121] (Application Example 1)

[1122] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1123] In logistics centers, it is essential to quickly and accurately obtain necessary contact information (names and contact details for specific departments or projects). However, this information is scattered across multiple systems, resulting in time-consuming and inefficient data collection. Furthermore, there is a risk of obtaining incorrect information, which can hinder business operations. A solution to these problems is needed.

[1124] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1125] In this invention, the server includes means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, means for displaying search results, means for obtaining information related to the storage and movement of items, and means for displaying the obtained information on a user device. This allows the user to easily search for and obtain the desired contact person information, enabling rapid business processing and accurate information transmission.

[1126] "Means of inputting information" refers to an interface that allows users to input necessary information (such as department name or project name) on their device.

[1127] "Means of transmitting information" refers to a mechanism for transmitting information entered by a user to a remote server or other device.

[1128] A "means of searching a database" is a processing device that finds relevant information from stored data, such as a relational database, based on the information that has been transmitted.

[1129] "Means of obtaining search results" refers to the process of retrieving information retrieved from a database and converting it into a usable format.

[1130] "Means for displaying search results" refers to an interface that visually displays the retrieved search results to the user in an easy-to-understand manner.

[1131] "Means for acquiring information related to the handling of storage and movement of goods" refers to the function of collecting information related to goods stored in logistics centers or goods being moved.

[1132] "Means for displaying acquired information on a user device" refers to a mechanism for displaying collected information on a user's device, such as a smartphone or personal computer.

[1133] This invention is a system for quickly and accurately obtaining necessary personnel information at a logistics center. The system includes means for a user to input information, means for transmitting information, means for searching a database, means for obtaining search results, means for displaying search results, means for obtaining information related to the storage and movement of goods, and means for displaying the obtained information on a user device.

[1134] Program Processing Description

[1135] In this system, users input necessary information (such as department name and project name) using a smartphone application. The entered information is then sent to the server via a data transmission method. For example, GET requests or POST requests are used for data transmission.

[1136] The server searches the database based on the received information. This database search process uses technologies such as SQL queries. The search results are converted to JSON format and sent from the server to the user's device.

[1137] The user device parses the received JSON data and visually displays necessary information such as the person in charge's name and contact details. This parsing and display can be done using programming languages ​​such as JavaScript or Python. This allows users to obtain accurate information in real time and perform business processes efficiently.

[1138] Specific example

[1139] For example, consider a scenario where a user searches for a "warehouse management manager" at a logistics center. The user opens a smartphone application and enters "warehouse management" and "inventory management" into the search form. This input is sent to a server, which searches the corresponding database and retrieves the relevant contact information in JSON format. The retrieved information is then sent back to the user's device, displaying the contact person's name and contact details.

[1140] Example of a prompt:

[1141] Please use the following information to search for the contact person at the logistics center.

[1142] Department: Warehouse Management

[1143] Project name: Inventory Clearance

[1144] Thus, by using this system, information retrieval in logistics centers will become easier, and it is expected that operational efficiency will improve dramatically.

[1145] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1146] Step 1:

[1147] The user opens the smartphone application and enters the necessary information (e.g., department name or project name) into the search form. Input is done through text fields, and each field displays a relevant label. The user's input is sent to the device as specific strings such as "warehouse management" or "inventory management."

[1148] Step 2:

[1149] The terminal retrieves the information entered by the user and prepares it for transmission. A program such as JavaScript or Python is executed here, converting the input information into a JSON object. This JSON object is then sent to the server endpoint in the form of a GET or POST request.

[1150] Step 3:

[1151] The server analyzes the request received from the terminal and extracts the included parameters (such as department name and project name). Based on the extracted information, it executes an SQL query against the relational database to search for the relevant records. For example, it searches for information on the person in charge related to the "Inventory Management Project in the Warehouse Management Department".

[1152] Step 4:

[1153] The server retrieves the search results and converts them into JSON format. In this step, it extracts the necessary information (such as the person in charge's name and contact details) from the search result records and structures it into a JSON object. The generated JSON object is sent to the terminal as a response.

[1154] Step 5:

[1155] The terminal receives a response from the server and parses the received JSON data. Using JavaScript or Python code, it converts the JSON data into an object format and extracts the necessary information (such as the person in charge's name and contact information). This information is then displayed on the screen in a format that the user can visually confirm.

[1156] Step 6:

[1157] Users view the contact person information displayed on their device screen and take the necessary action (for example, contact the contact person). Specifically, the contact person's name and contact information are displayed in a list format, and links or buttons are provided for direct contact as needed.

[1158] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1159] This invention relates to a system that includes means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, means for displaying search results, and an emotion engine that recognizes the user's emotions. The purpose of this system is to quickly and accurately obtain the names of persons in charge of specific sales channels or measures and event ordering contacts, and to provide search results that take the user's emotions into consideration.

[1160] Specific Examples of the System

[1161] This system works by having the user input information via a web browser and send it to the server. The server searches a database based on the received information and analyzes the user's emotions using an emotion engine. The search results are returned to the terminal in JSON format and displayed after being adjusted according to the user's emotions.

[1162] User input

[1163] Users access a specific URL using a web browser and enter the required information (e.g., specific sales channels and campaign types) into the displayed form. The input fields also include a field for users to enter text comments, allowing them to express their feelings. Once the user provides this input data, they click the "Search" button to begin processing.

[1164] Information transmission by terminal

[1165] The device uses JavaScript or similar methods to retrieve data entered by the user. This data is sent as parameters in a GET request to the specified server endpoint. For example, the URL might be / api / retrieve_representative?store_type=major electronics retailer&promotion_type=BB&comment=please respond quickly.

[1166] Server-based database search

[1167] The server receives a request sent from the terminal. The request includes the store_type (type of sales channel), promotion_type (type of promotion), and comment (user comment) entered by the user. The server uses these parameters to connect to the relational database and search for the corresponding record.

[1168] Sentiment analysis and result retrieval by the server

[1169] The server uses a sentiment engine to analyze the sentiment of user comments. The sentiment engine analyzes the user's comment text to identify the degree and type of emotion. For example, it can detect emotions such as "strong request" or "dissatisfaction" from user comments. Based on this information, the server adjusts or filters the search results.

[1170] Server retrieves and processes search results.

[1171] The server retrieves the query results and extracts matching contact names and order contact information. This information is converted to JSON format, and necessary adjustments are made based on the sentiment analysis results. For example, if a user expresses dissatisfaction, the server prioritizes providing the names of contacts who are likely to provide more courteous service.

[1172] Displaying search results by device

[1173] The terminal receives a response from the server and parses the JSON data. Since the results of sentiment analysis are also included, they are presented to the user in an appropriate format. For example, if there is a comment that says "Please respond quickly," the search results will be displayed as "High priority personnel."

[1174] Specific example

[1175] For example, if a user enters "Major Electronics Retailer" as the store_type, "BB" as the promotion_type, and "Please respond quickly" as a comment, and then searches, the device sends this information to the server as a GET request. The server searches the relational database and retrieves the name of the person in charge of the "BB" promotion at the "Major Electronics Retailer". At the same time, the sentiment engine analyzes the user comment to determine that it is requesting a "quick response". Based on this, the server selects the most suitable person in charge and returns the result to the device in JSON format. The device then analyzes this result and displays the most suitable person in charge to the user.

[1176] This system allows users to quickly and accurately obtain the information they need, as well as receive appropriate responses tailored to their emotions and expectations. This leads to improved customer satisfaction and a dramatic increase in work efficiency.

[1177] The following describes the processing flow.

[1178] Step 1:

[1179] The user opens a web browser and accesses a specific URL. The page displays forms for entering `store_type` and `promotion_type`, as well as a comment section. The user enters the data into these input fields and clicks the "Search" button.

[1180] Step 2:

[1181] The terminal retrieves user input. The form contents are read using a client-side scripting language such as JavaScript. For example, if the user enters "Major electronics retailer" for `store_type`, "BB" for `promotion_type`, and "Please respond quickly" in the comments field, this information will be stored in a variable.

[1182] Step 3:

[1183] The data acquired by the device is sent as parameters to the endpoint / api / retrieve_representative_with_emotion in a GET request. Specifically, the URL will be / api / retrieve_representative_with_emotion?store_type=major electronics retailer&promotion_type=BB&comment=please respond quickly.

[1184] Step 4:

[1185] The server receives a GET request. The server extracts the values ​​of the request parameters store_type, promotion_type, and comment. For example, it verifies that store_type is "Major electronics retailer", promotion_type is "BB", and comment is "Please respond quickly".

[1186] Step 5:

[1187] The server establishes a database connection. It uses a relational database to query the ptn_representatives table in the database.

[1188] Step 6:

[1189] The server generates the query, sets the parameters, and executes the query. The query will look like this:

[1190] SQL

[1191] SELECT representative_name FROM ptn_representatives WHERE store_type = 'Major Electronics Retailer' AND promotion_type = 'BB'

[1192] The server searches for the relevant record.

[1193] Step 7:

[1194] The server retrieves the search results. If a matching record is found, the name of the person in charge is retrieved as a result. For example, "Taro Tanaka" might be retrieved as the person in charge's name.

[1195] Step 8:

[1196] The server uses an emotion engine to analyze the sentiment from user comments. The emotion engine analyzes the comment "Please respond quickly" and detects the user's strong request.

[1197] Step 9:

[1198] The server adjusts or filters search results based on the sentiment analysis results. For example, if a strong user request is detected, a high-priority contact person is selected. In this case, "Taro Tanaka" would be selected as the high-priority contact person.

[1199] Step 10:

[1200] The server converts the retrieved representative name into JSON format. For example, the result might be {"representative_name": "Taro Tanaka"}. If no matching record is found, an error message {"error": "No representative found"} is generated.

[1201] Step 11:

[1202] The server returns a JSON response to the terminal. The HTTP response specifies Content-Type as application / json and sends back a response containing JSON data.

[1203] Step 12:

[1204] The terminal receives a response from the server. It then uses technologies such as JavaScript to analyze the response data.

[1205] Step 13:

[1206] The terminal displays the analysis results on the screen. Based on the received JSON data, it visually presents the user with the name of the person in charge or an error message. For example, if the person in charge's name is "Taro Tanaka," then "Person in Charge: Taro Tanaka" will be displayed on the screen. The user's sentiment analysis results will also be displayed, so a message such as "A prompt response was expected" may also be shown.

[1207] (Example 2)

[1208] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1209] Traditional information retrieval systems often provide search results without considering user emotions or needs, which can lead to decreased user satisfaction. Furthermore, they struggle to provide appropriate information to users who require quick and accurate responses, resulting in a lack of improvement in operational efficiency.

[1210] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1211] In this invention, the server includes means for inputting information, means for transmitting information, means for searching a database, means for analyzing emotions, means for adjusting search results, means for obtaining search results, and means for displaying search results. This makes it possible to provide optimal information while taking the user's emotions into consideration, thereby improving customer satisfaction and operational efficiency.

[1212] "Means of inputting information" refers to an interface for users to input necessary information, such as a form in a web browser.

[1213] "Means of transmitting information" refers to the mechanism for sending data entered by a user to a server, which may include using a GET request, for example.

[1214] "Means of searching a database" refers to a mechanism that searches for relevant information from relational and non-relational databases based on the input data.

[1215] "Means of analyzing emotions" refers to engines or software that analyze emotions from user-inputted comments, such as generative AI models.

[1216] "Means of adjusting search results" refers to mechanisms that prioritize or filter search results based on the results of sentiment analysis.

[1217] "Means for obtaining search results" refers to a mechanism for collecting information extracted from a database and using it for subsequent processing.

[1218] "Means of displaying search results" refers to the interface used to visualize the final retrieved search results for the user, such as the display component of a web page.

[1219] The present invention is a system for quickly and accurately obtaining information requested by a user and presenting it appropriately while taking the user's emotions into consideration. This system includes means for inputting information, means for transmitting information, means for searching a database, means for analyzing emotions, means for adjusting search results, means for obtaining search results, and means for displaying search results.

[1220] User input

[1221] The user accesses a specific URL through a web browser and enters the required information into a form. This form includes fields for "Sales Channel Type," "Measure Type," and "Comments." The comments field allows the user to write their feelings or requests. For example, let's assume the user selects "Major Electronics Retailer" as the sales channel type, "BB" as the measure type, and enters the comment "Please respond quickly."

[1222] Information transmission by terminal

[1223] The device uses JavaScript to retrieve the data entered by the user and sends it as a parameter to the specified server endpoint in a GET request. A concrete example request URL would be / api / retrieve_representative?store_type=major electronics retailer&promotion_type=BB&comment=please respond quickly.

[1224] Server-based database search

[1225] The server receives a request sent from the terminal. This request contains the information entered by the user: store_type, promotion_type, and comment. The server uses these parameters to connect to a relational database (such as MySQL) and retrieve the corresponding record.

[1226] Server-based sentiment analysis

[1227] The server uses an emotion engine (e.g., IBM Watson Tone Analyzer) to analyze the sentiment of a user's comment text. The analysis results include emotions such as "strong request for a quick response" or "dissatisfaction." For example, a comment like "Please respond quickly" might be interpreted as a "strong request."

[1228] Server generates and sends search results.

[1229] The server converts the contact person names and order contact information retrieved from the database into JSON format and adjusts the information based on the sentiment analysis results. For example, if a user indicates a "strong request for a quick response," the server adjusts the information to provide contact person information with a higher priority. This data is ultimately returned to the terminal in JSON format.

[1230] Displaying search results by device

[1231] The terminal parses the JSON data received from the server and displays the search results to the user in an appropriate format. For example, if there is a comment that says "Please respond quickly," the result will be displayed as "High priority person in charge."

[1232] Specific example

[1233] For example, if a user enters "Major electronics retailer" as the store_type, "BB" as the promotion_type, and "Please respond quickly" as a comment, the device sends this information to the server as a GET request. The server searches the relational database and retrieves the name of the person in charge of the "BB" promotion at the "Major electronics retailer". At the same time, the sentiment engine analyzes the user's comment to determine that it requests a "quick response". Based on this, the server selects the most suitable person in charge and returns it to the device as a result in JSON format. The device then analyzes this result and displays the most suitable person in charge to the user.

[1234] Example of a prompt

[1235] Send the following information as a GET request to the URL:

[1236] store_type: Major consumer electronics retailer

[1237] promotion_type: BB

[1238] Comment: Please respond promptly.

[1239] Search the database for the relevant person in charge and analyze the comments using a sentiment engine. Then, return the search results in JSON format.

[1240] This system allows users to quickly and accurately obtain the information they need and receive appropriate responses that meet their emotions and expectations. This leads to improved customer satisfaction and increased operational efficiency.

[1241] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1242] Step 1:

[1243] The user accesses a specific URL using a web browser and enters the required information into the displayed form. Specifically, they fill in the fields for "Sales Channel Type," "Measure Type," and "Comments." Once they have finished entering the information, they click the "Search" button.

[1244] Input: Information entered by the user in the form (e.g., store_type, promotion_type, comment)

[1245] Output: User input data acquired by the terminal

[1246] Step 2:

[1247] The device uses JavaScript to retrieve data entered by the user into a form. This retrieved data is then sent as parameters to a GET request to the specified server endpoint.

[1248] Input: User input data

[1249] Output: Data in GET request format sent to the server

[1250] Specific actions:

[1251] The device retrieves the user's form input data using JavaScript.

[1252] Generate a GET request URL (e.g., / api / retrieve_representative?store_type=major electronics retailer&promotion_type=BB&comment=please respond quickly).

[1253] Send data to the server.

[1254] Step 3:

[1255] The server receives a GET request sent from the terminal. It extracts and parses the parameters store_type, promotion_type, and comment included in the request.

[1256] Input: GET request data from the terminal

[1257] Output: Extracted parameters (store_type, promotion_type, comment)

[1258] Specific actions:

[1259] The server receives a GET request.

[1260] Extract parameters from the request (e.g., store_type=Major electronics retailer, promotion_type=BB, comment=Please respond quickly).

[1261] Step 4:

[1262] The server uses the extracted parameters to connect to a relational database (e.g., MySQL) and search for the relevant records.

[1263] Input: Extracted parameters

[1264] Output: Search results from the database

[1265] Specific actions:

[1266] Generate a database query based on the extracted parameters.

[1267] Execute a database query to find the relevant record.

[1268] Retrieve search results.

[1269] Step 5:

[1270] The server uses a sentiment engine (e.g., IBM Watson Tone Analyzer) to analyze user comments. It analyzes the comment text to identify the degree and type of sentiment.

[1271] Input: User's comment text

[1272] Output: Results of sentiment analysis (e.g., strong demands, dissatisfaction, etc.)

[1273] Specific actions:

[1274] Send user comment text to the sentiment engine.

[1275] The emotion engine analyzes the text to identify the type and degree of emotion.

[1276] Obtain the emotion analysis results.

[1277] Step 6:

[1278] The server converts the search results retrieved from the database into JSON format and makes adjustments based on the sentiment analysis results. The adjusted results are then sent to the terminal.

[1279] Input: Database search results, sentiment analysis results

[1280] Output: Search results in adjusted JSON format

[1281] Specific actions:

[1282] Convert the search results retrieved from the database into JSON format.

[1283] The search results are adjusted based on sentiment analysis results (e.g., prioritizing the provision of information on high-priority contacts).

[1284] The adjusted results will be sent to the device.

[1285] Step 7:

[1286] The terminal parses the JSON data received from the server and displays the search results to the user in an appropriate format.

[1287] Input: JSON data received from the server

[1288] Output: Search results displayed to the user

[1289] Specific actions:

[1290] The system parses the JSON data received from the server.

[1291] The results are passed to a UI component for visualization to the user.

[1292] Display the search results (e.g., display as "Responsible person who can be expected to respond quickly").

[1293] (Application Example 2)

[1294] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1295] Traditional systems suffered from a lack of user satisfaction because they could not provide search results that reflected the user's emotions or expectations, even after they entered information. Furthermore, in situations requiring quick and accurate responses, systems that did not consider emotions made it difficult to select the appropriate person to handle the situation.

[1296] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, means for displaying search results, and an emotion analysis engine for analyzing the user's emotions. This makes it possible to adjust the search results based on the user's emotions.

[1297] "Means of inputting information" refers to the interface through which users input necessary information into a system, such as web browsers and smartphone applications.

[1298] "Means of transmitting information" refers to communication methods used to send information entered by a user to a server, specifically using HTTP requests such as GET requests.

[1299] "Methods for searching a database" refers to functions that allow the server to retrieve relevant data from a database based on the information it receives.

[1300] "Means for obtaining search results" refers to the function that allows the server to receive the results of a database search and process those results as appropriate.

[1301] "Means of displaying search results" refers to the interface used to display the retrieved search results to the user, such as the screen of a web browser or a smartphone application.

[1302] A "sentiment analysis engine" is a software component that analyzes emotions from user input text and identifies the degree and type of emotion.

[1303] "Means of adjusting search results based on user sentiment" refers to a function that appropriately filters or prioritizes search results based on sentiment information obtained by a sentiment analysis engine.

[1304] This invention relates to a system including means for inputting information, means for transmitting information, means for searching a database, means for obtaining search results, means for displaying search results, and an emotion analysis engine for analyzing the user's emotions. This system allows users to quickly and accurately obtain the information they need and receive appropriate responses that match their emotions and expectations.

[1305] Specific examples

[1306] User input

[1307] Users access a specific screen using a smartphone application and enter the required information into the displayed form. The input fields also include a field for users to enter text comments, allowing them to express their feelings. Once the user provides this input data, they tap the "Search" button to begin processing.

[1308] Information transmission by terminal

[1309] The device uses JavaScript or similar methods to retrieve data entered by the user. This data is sent as parameters in an HTTP GET request to the specified server endpoint. For example, the URL might be / api / retrieve_representative?store_type=large retail store&promotion_type=promotion Type A&comment=urgent action required.

[1310] Server-based database search

[1311] The server receives a request sent from the terminal. The request includes the store_type (type of sales channel), promotion_type (type of promotion), and comment (user comment) entered by the user. The server uses these parameters to connect to the relational database and search for the corresponding record.

[1312] Sentiment analysis and result retrieval by the server

[1313] The server uses a sentiment analysis engine to analyze the emotions expressed in user comments. The sentiment analysis engine analyzes the user's comment text to identify the degree and type of emotion. For example, it can detect emotions such as "strong demand" or "dissatisfaction" from user comments. Based on this information, the server adjusts or filters the search results.

[1314] Server retrieves and processes search results.

[1315] The server retrieves the query results and extracts matching contact names and order contact information. This information is converted to JSON format, and necessary adjustments are made based on the sentiment analysis results. For example, if a user expresses dissatisfaction, the server prioritizes providing the names of contacts who are likely to provide more courteous service.

[1316] Displaying search results by device

[1317] The terminal receives a response from the server and parses the JSON data. Since the results of sentiment analysis are also included, they are presented to the user in an appropriate format. For example, if there is a comment that says "urgent action required," the search results will be displayed as "high priority personnel."

[1318] Specific examples

[1319] For example, if a user enters "Large Retail Store" as the store_type, "Promotion Type A" as the promotion_type, and "I need immediate action" as the comment, the device sends this information to the server as a GET request. The server searches the relational database and retrieves the name of the person in charge of the "Promotion Type A" initiative for the "Large Retail Store". At the same time, the sentiment analysis engine analyzes the user's comment as requesting "immediate action". Based on this, the server selects the most suitable person in charge and returns it to the device as a result in JSON format. The device then analyzes this result and displays the most suitable person in charge to the user.

[1320] Example of a prompt

[1321] User comment: "We need an immediate response."

[1322] Analysis result: Due to the high emotional score, the priority will be set to "High".

[1323] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1324] Step 1:

[1325] The user opens the smartphone application, accesses a specific screen, and enters the required information into the provided form. The input fields include "Sales Channel Type," "Measure Type," and a "Comment Field." Once the user enters this data and taps the "Search" button, the device is ready to proceed to the next step.

[1326] Step 2:

[1327] The terminal retrieves the data entered by the user and sends it to the server as parameters in an HTTP GET request. Specifically, it uses a script such as JavaScript to collect the input data and sends it to the server endpoint in URL format. For example, if you enter "Large-scale retail store" for store_type, "Promotion Type A" for promotion_type, and "Immediate action required" for comment, the following URL will be generated: / api / retrieve_representative?store_type=Large-scale retail store&promotion_type=Promotion Type A&comment=Immediate action required

[1328] Step 3:

[1329] The server parses the request received from the terminal and extracts the request parameters. These extracted parameters include store_type, promotion_type, and comment. Based on these parameters, the server connects to the relational database and searches for the relevant records. This search process extracts contact persons and ordering contact information that have a high degree of accuracy.

[1330] Step 4:

[1331] The server activates a sentiment analysis engine to analyze user comments and calculates a sentiment score from the comment text. The sentiment analysis engine (for example, a natural language processing library such as TextBlob) analyzes the user's text and identifies the degree of emotion, such as positive, negative, or neutral. For example, a comment like "I need immediate action" would receive a high positive sentiment score as a strong request.

[1332] Step 5:

[1333] The server combines database search results with sentiment analysis results and adjusts search results based on the user's emotions. Specifically, if the sentiment score is high, it prioritizes selecting the names of personnel who can be expected to respond more quickly, and filters or prioritizes the results accordingly. These results are converted into JSON format.

[1334] Step 6:

[1335] The terminal receives the search results in JSON format returned from the server and parses them. The parsed search results are then presented to the user in an appropriate format. For example, if a result is tagged with "Priority: High," a message such as "This person is available to handle your request with high priority" will be displayed on the screen. Based on this, the user can receive a prompt response.

[1336] Through the above processing flow, the system can provide optimal search results that meet the user's emotions and expectations, enabling a quick and appropriate response.

[1337] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1338] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1339] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1340] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1341] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1342] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1343] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1344] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1345] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1346] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1347] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1348] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1349] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1350] 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.

[1351] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1352] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1353] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1354] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1355] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1356] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1357] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[1358] The following is further disclosed regarding the embodiments described above.

[1359] (Claim 1)

[1360] Means of inputting information,

[1361] Means for transmitting information,

[1362] A means of searching the database,

[1363] Methods for obtaining search results,

[1364] A system that includes means for displaying search results.

[1365] (Claim 2)

[1366] The system according to claim 1, characterized in that the means for inputting information is a web browser.

[1367] (Claim 3)

[1368] The system according to claim 1, characterized in that the means for transmitting information uses a GET request.

[1369] (Claim 4)

[1370] The system according to claim 1, characterized in that the database is a relational database.

[1371] (Claim 5)

[1372] The system according to claim 1, characterized in that the search results are displayed in JSON format.

[1373] "Example 1"

[1374] (Claim 1)

[1375] Means of inputting information,

[1376] Means for transmitting information,

[1377] A means of searching the database,

[1378] Methods for obtaining search results,

[1379] Means of displaying search results,

[1380] A method for converting search results into structured data,

[1381] A system that includes a means for processing search results in JSON format.

[1382] (Claim 2)

[1383] The system according to claim 1, characterized in that the means for inputting information is a web browser.

[1384] (Claim 3)

[1385] The system according to claim 1, characterized in that the means for transmitting information uses a GET request.

[1386] "Application Example 1"

[1387] (Claim 1)

[1388] Means of inputting information,

[1389] Means for transmitting information,

[1390] A means of searching the database,

[1391] Methods for obtaining search results,

[1392] Means of displaying search results,

[1393] Means for obtaining information related to the processing of storage and movement of goods,

[1394] A means for displaying the acquired information on the user's device,

[1395] A system that includes this.

[1396] (Claim 2)

[1397] The system according to claim 1, characterized in that the means for inputting information is a web browser or application software.

[1398] (Claim 3)

[1399] The system according to claim 1, characterized in that the means for transmitting information is a GET request or a POST request.

[1400] "Example 2 of combining an emotion engine"

[1401] (Claim 1)

[1402] Means of inputting information,

[1403] Means for transmitting information,

[1404] A means of searching the database,

[1405] A means of analyzing emotions,

[1406] Means to adjust search results,

[1407] Methods for obtaining search results,

[1408] Means of displaying search results,

[1409] A system that includes this.

[1410] (Claim 2)

[1411] The system according to claim 1, characterized in that the means for inputting information is a web browser.

[1412] (Claim 3)

[1413] The system according to claim 1, characterized in that the means for transmitting information uses a GET request.

[1414] (Claim 4)

[1415] The system according to claim 1, characterized in that the means for analyzing emotions is a generative AI model.

[1416] (Claim 5)

[1417] The system according to claim 4, characterized in that the means for adjusting the search results are performed based on a prompt statement.

[1418] "Application example 2 of combining emotional engines"

[1419] (Claim 1)

[1420] Means of inputting information,

[1421] Means for transmitting information,

[1422] A means of searching the database,

[1423] Methods for obtaining search results,

[1424] Means of displaying search results,

[1425] A system including an emotion analysis engine that analyzes the emotions of users,

[1426] A system that includes means to adjust search results based on the user's emotions.

[1427] (Claim 2)

[1428] The system according to claim 1, characterized in that the means for inputting information is a web browser or a smartphone application.

[1429] (Claim 3)

[1430] The system according to claim 1, characterized in that the means for transmitting information uses a GET request. [Explanation of symbols]

[1431] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means of inputting information, Means for transmitting information, A means of searching the database, Methods for obtaining search results, A system that includes means for displaying search results.

2. The system according to claim 1, characterized in that the means for inputting information is a web browser.

3. The system according to claim 1, characterized in that the means for transmitting information uses a GET request.

4. The system according to claim 1, characterized in that the database is a relational database.

5. The system according to claim 1, characterized in that the search results are displayed in JSON format.

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