system

Abstract

Provide a system. A means for a user to input work history information and desired conditions; means for receiving the input information and storing it in a database; a means for presenting questions to a user regarding job duties and work environment and receiving answers; a means for storing the received responses in a database; A means for analyzing user information and responses and generating optimal job information; A means for providing the generated job information to a user; A means for providing candidate information to companies that post job information; A system including:

Description

[Technical Field]

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

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

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

[0004] In traditional job-hunting processes, it is difficult for job seekers to efficiently find job information that matches their skill set and desired conditions. It is also difficult for companies to quickly find suitable candidates. This places a significant burden of time and effort on both job seekers and companies. There is a need for a system that can solve these issues and match job seekers and companies efficiently and accurately. [Means for solving the problem]

[0005] The present invention solves the above problem by providing a system that includes a means for a user to input work history information and desired conditions, a means for receiving the input information and saving it in a database, a means for presenting questions to the user regarding job content and work environment and receiving answers, a means for saving the received answers in a database, a means for analyzing the user's information and answers and generating optimal job information, a means for providing the generated job information to the user, and a means for providing candidate information to companies that submit job information.

[0006] Furthermore, by including a means for using machine learning algorithms to analyze user information and responses and a means for calculating the degree of matching of job information, the system achieves more accurate matching, allowing job seekers to find suitable job information in a short time and companies to efficiently find suitable candidates.

[0007] "User" refers to a person who uses the job change matching system to input work history information and desired conditions.

[0008] "Work history information" refers to data that includes a user's past work history, skill sets, and other related information.

[0009] "Desired conditions" refer to conditions such as the user's desired work environment, work location, salary, and working style.

[0010] "Database" refers to the storage device within the system that stores and manages users' work history information, desired conditions, responses, and job information.

[0011] A "question" refers to an inquiry presented to a user to collect information about job content and work environment related to job change.

[0012] An "answer" refers to information entered by a user in response to a posed question.

[0013] "Generation" refers to the process of analyzing the user's information and responses and creating a specific job posting based thereon.

[0014] "Machine learning algorithm" refers to a computer program used to analyze data such as user information and responses, and job listings.

[0015] "Matching degree" refers to an index that quantifies the compatibility of the user's information and answers with the job information.

[0016] "Job information" refers to data that includes information such as the job description offered by a company, the required skill set, and working conditions.

[0017] "Company" refers to an organization or group that posts job information and uses a job-matching system to find suitable candidates.

[0018] A "candidate" refers to a user who is deemed suitable based on job information provided by a company. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7]FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0021] First, the terms used in the following description will be explained.

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] This invention relates to a system that provides optimal job information to job seekers. Users input their work history and desired conditions, and a server receives and analyzes them to generate and provide optimal job information.

[0041] System configuration

[0042] This system includes a terminal used by the user, a database, and a server. Users use their terminal to access the system and input and receive information. The server receives the information and stores and analyzes it in the database.

[0043] Explanation of program processing

[0044] Registration Phase

[0045] User: The user enters their work history information and desired conditions into the terminal, including name, address, past work history, skill set (e.g., Java (registered trademark), Python), and desired work environment (e.g., remote work allowed).

[0046] Terminal: The terminal receives the input information, converts it into a specific data format (such as JSON), and sends it to the server.

[0047] Server: The server analyzes the received data and stores it in a database. Once the data is stored, it sends a confirmation response to the device.

[0048] Question Phase

[0049] Server: The server presents the user with predefined questions, such as "Do you value teamwork?" or "Do you prefer a company that allows remote work?"

[0050] Terminal: The terminal displays these questions in a user interface and waits for user input.

[0051] User: The user answers each question using a terminal. For example, the user answers "Yes" to the question "Do you value teamwork?"

[0052] Terminal: The terminal collects the user's answers, converts them into the specified data format, and sends them to the server.

[0053] Server: The server analyzes the received response and stores it in a database.

[0054] Matching Phase

[0055] Server: The server runs a matching algorithm based on the user's work history and answers, which allows the server to compare the user's information with job listings in its database and select the most suitable job listing.

[0056] Server: Generates a list containing selected job information and sends it to the terminal.

[0057] Terminal: The terminal displays the job listings on a user interface.

[0058] User: The user reviews the displayed job information and selects the job that interests them.

[0059] Proposal Phase

[0060] Server: The server generates an alert to the company providing the user's profile information, such as "Candidate A has been added to your job seeker list. His skill set and desired conditions match your job posting."

[0061] Company: The company receives the candidate information provided by the server and schedules interviews and next steps.

[0062] Specific examples

[0063] Example of the registration phase

[0064] User: Taro Yamada accesses the system and enters his name, address, past work experience (e.g., 5 years of Java development experience), skill set (e.g., Java, Python), and desired work environment (e.g., remote work acceptable).

[0065] Terminal: The terminal converts this information into JSON format and sends it to the server.

[0066] Server: After receiving the data and verifying its validity, the server stores it in a database and returns a processing completion response to the terminal.

[0067] Specific example of the question phase

[0068] Server: The server sends the question "Do you value teamwork?" in JSON format to the terminal.

[0069] Terminal: The terminal presents the received question to the user.

[0070] User: Yamada answers "Yes" and sends the answer to the server via his terminal.

[0071] Server: The server receives the answer and stores it in a database.

[0072] A concrete example of the matching phase

[0073] Server: Based on Yamada's profile and answers, the server uses a matching algorithm to analyze the job listings in the database and select the most suitable job listing.

[0074] Server: Generates a list containing suitable job information (e.g., "Company B - Java Engineer (remote work available)") and sends it to the device.

[0075] Terminal: The terminal displays this list to Yamada.

[0076] User: Yamada checks the displayed job information and selects the information that interests him.

[0077] Specific example of the proposal phase

[0078] Server: The server generates and sends an alert to Company B containing Taro Yamada's profile information.

[0079] Company: The company's HR will review the profile information received and schedule an interview.

[0080] In this way, a system can be constructed that realizes efficient and highly accurate job-change matching for both users and companies.

[0081] The processing flow will be explained below.

[0082] Step 1:

[0083] Users enter their work history information and desired conditions into a terminal, specifically, their name, address, past work history, skill set, and desired work environment.

[0084] Step 2:

[0085] The terminal receives the input information and converts it into a specified format such as JSON.

[0086] Step 3:

[0087] The terminal sends the converted data to the server via an HTTP POST request.

[0088] Step 4:

[0089] The server parses the received data and validates it, checking that all required fields are present, that the format is correct, etc.

[0090] Step 5:

[0091] The server saves the data that has been successfully validated in the database, and once the saving is complete, it sends the processing result to the terminal as a response.

[0092] Step 6:

[0093] The server sends a list of questions to the user in JSON format to present questions about their job duties and work environment to the terminal.

[0094] Step 7:

[0095] The terminal displays the received question list on the user interface.

[0096] Step 8:

[0097] The user inputs an answer to the displayed question, for example, "Do you value teamwork?", and answers "Yes."

[0098] Step 9:

[0099] The terminal collects the answers entered by the user, converts them back into JSON format, and sends them to the server.

[0100] Step 10:

[0101] The server analyzes the received responses and stores them in a database, adding them to the user's profile.

[0102] Step 11:

[0103] The server runs a matching algorithm based on the user's work history and responses, calculating the degree of match between the job listings in the database and the user's information.

[0104] Step 12:

[0105] The server lists the most suitable job information and generates JSON data to send to the terminal.

[0106] Step 13:

[0107] The terminal displays the received job information list on the user interface.

[0108] Step 14:

[0109] The user checks the displayed job listings and selects the job listings that interest them.

[0110] Step 15:

[0111] The server generates alerts to businesses associated with the selected job postings, providing information about suitable candidates.

[0112] Step 16:

[0113] The server sends an alert to the company's HR department containing the profile information of the selected candidate.

[0114] Step 17:

[0115] The corporate user reviews the received candidate information and decides on interviews and next steps.

[0116] Example 1

[0117] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0118] Conventional job information systems simply accept the work history information and desired conditions entered by users, and the accuracy of providing job information based on that information is low, making it difficult to provide appropriate job information that meets the user's needs.In addition, the analysis of user information and optimization of job information are limited, and detailed candidate information cannot be provided to companies, resulting in low efficiency in matching companies and users.

[0119] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0120] In this invention, the server includes means for receiving information entered by a user, converting it into a specific data format, and saving it in a database, means for presenting the user with questions about job content and work environment and receiving answers, means for saving the received answers in a database, means for analyzing the user's information and the received answers and using a matching algorithm to generate optimal job information, means for providing the generated optimal job information to the user, and means for providing user profile information to companies that submit job information. This makes it possible to provide highly accurate job information based on the user's detailed needs, and improves the efficiency of matching companies and users.

[0121] A "user" is an individual who uses this system to input work history information and desired conditions in order to obtain the most suitable job information.

[0122] "Work history information" refers to information such as the jobs, positions, and skill sets that a user has had up to now.

[0123] "Desired conditions" are the user's desired work environment, working conditions, work location, and other requirements.

[0124] "Input means" refers to an interface that allows a user to input information into the system, and is primarily operated via a terminal.

[0125] "Data format" refers to a format in which information is expressed as structured data in a certain format, such as JSON format.

[0126] A "database" is a digital storage system that can efficiently store, manage, and search structured data.

[0127] The "means for presenting questions" refers to an interface through which the server displays questions about the job content and work environment to the user.

[0128] The "means for receiving an answer" refers to an interface that allows the system to receive and analyze answers to questions returned by users.

[0129] A "matching algorithm" is a calculation method for selecting the most suitable job information based on the user's work history, desired conditions, and responses.

[0130] "Job information" refers to detailed information provided by companies about job types, positions, and related conditions.

[0131] "Profile information" is information that compiles the user's work history, skill set, desired conditions, and the like.

[0132] A "secure protocol" is a communication protocol for securely transmitting information, and includes, for example, HTTPS.

[0133] This invention relates to a system that provides optimal job information to job seekers. A user inputs their work history and desired conditions, and a server receives and analyzes the information to generate and provide optimal job information. The system includes a terminal used by the user, a database, and a server. Detailed modes for implementing the invention are described below.

[0134] System configuration

[0135] User: A user accesses the system using a terminal and enters their work history and preferences, such as their name, address, past work experience, skill set, and desired work environment.

[0136] Terminal: The terminal receives the information entered by the user and converts it into a specific data format (e.g., JSON format), which is then sent to the server via a secure protocol (e.g., HTTPS).

[0137] Server: The server analyzes the received data and stores it in a database. It presents the user with questions about the job content and work environment, and also receives and stores the answers to the questions in a database. The server analyzes the user's work history and desired conditions and generates optimal job information using a generative AI model.

[0138] Specific examples

[0139] Example of the registration phase

[0140] User: A job seeker accesses the system and enters their name, address, past work experience (e.g., 5 years of Java development experience), skill set (e.g., Java, Python), and desired work environment (e.g., remote work acceptable).

[0141] Terminal: The terminal converts this information into JSON format and sends it to the server.

[0142] Server: The server receives the data, verifies its validity, and then saves it in the database. Once the saving is complete, it returns a processing completion response to the terminal.

[0143] Specific example of the question phase

[0144] Server: The server generates the question "Do you value teamwork?" through a generative AI model and sends it to the device in JSON format.

[0145] Terminal: The terminal presents the received question to the user.

[0146] User: The user answers "yes" and sends the answer to the server via the terminal.

[0147] Server: The server receives the response and stores it in a database.

[0148] A concrete example of the matching phase

[0149] Server: Based on the user's work history information and answers to questions, the server uses a generative AI model to analyze the job listings in the database and generate the most suitable job listings.

[0150] Server: Generates a list containing suitable job information (e.g., "Company - Java Engineer (Remote Work Available)") and sends it to the device.

[0151] Terminal: The terminal displays this list to the user.

[0152] User: The user reviews the displayed job listings and selects the ones that interest them.

[0153] Specific example of the proposal phase

[0154] Server: The server generates and sends an alert to the company containing the user's profile information, stating, "The candidate has been added to your job seeker list. His skill set and preferences match your job opening."

[0155] Company: The company's HR will review the profile information received and schedule an interview.

[0156] Prompt Sentence Examples

[0157] "Please analyze the work history information and desired conditions entered by the user and generate the most suitable job information."

[0158] "Present users with a question about whether they value teamwork."

[0159] Based on the above steps, efficient and highly accurate job-change matching can be achieved for both users and companies.

[0160] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0161] Step 1:

[0162] User: The user enters their work history information and desired conditions into the terminal, specifically, their name, address, past work history (e.g., 5 years of Java development experience), skill set (e.g., Java, Python), and desired work environment (e.g., remote work acceptable).

[0163] Input: User enters work history information and desired qualifications.

[0164] Output: Information typed into the terminal.

[0165] Specific operation: The user enters the required information into the input form and clicks the submit button.

[0166] Step 2:

[0167] Terminal: The terminal receives the input information, converts it into JSON format data, and then sends this data to the server using a secure protocol (e.g., HTTPS).

[0168] Input: The work history information and desired conditions entered by the user into the terminal.

[0169] Output: JSON formatted data sent to the server.

[0170] Specific operation: The device internally converts the information into JSON format and sends the data to the server using HTTPS.

[0171] Step 3:

[0172] Server: The server analyzes the received data and saves it in the database. It verifies the validity of the data and returns an error message to the terminal if the data is invalid. If the data is normal, it saves it and then sends a response indicating that processing is complete.

[0173] Input: JSON format data sent from the terminal.

[0174] Output: User information saved in the database and a response indicating completion of the process.

[0175] Specific operation: The server verifies the validity of the data, and if it is normal, saves it in the database and sends a response to the terminal indicating that processing is complete.

[0176] Step 4:

[0177] Server: The server generates predefined questions for the user through a generative AI model and sends them to the terminal in JSON format.

[0178] Input: A prompt for the generative AI model.

[0179] Output: The JSON data of the question sent to the terminal.

[0180] Specific operation: The server generates a question using the generative AI model and sends it to the device.

[0181] Step 5:

[0182] Terminal: The terminal displays the received question on the user interface (UI). While waiting for the user's answer, it displays an answer input screen to the user.

[0183] Input: JSON data of the question sent by the server.

[0184] Output: The question displayed on the user interface.

[0185] Specific operation: The device analyzes the question data received and displays the question on the UI.

[0186] Step 6:

[0187] User: The user answers questions displayed on the device. For example, the user answers "Yes" to the question "Do you value teamwork?"

[0188] Input: The question displayed from the terminal.

[0189] Output: The answer typed into the terminal.

[0190] Specific behavior: The user enters an answer and clicks the submit button.

[0191] Step 7:

[0192] Terminal: The terminal collects the user's answers, converts them back into JSON format, and sends them to the server.

[0193] Input: The answer entered by the user.

[0194] Output: The JSON formatted response data sent to the server.

[0195] Specific operation: The device converts the response data into JSON format and sends it to the server using HTTPS.

[0196] Step 8:

[0197] Server: The server receives the response data, analyzes it, and stores it in a database.

[0198] Input: JSON formatted response data sent from the device.

[0199] Output: Response data stored in a database.

[0200] Specific operation: The server analyzes the received response data and stores it in the database.

[0201] Step 9:

[0202] Server: The server runs a matching algorithm based on the user's work history and answers to generate the most suitable job listings. The generated job listings are then listed in JSON format.

[0203] Input: User information and response data stored in a database.

[0204] Output: A list of the best job listings.

[0205] Specific operation: Launch the matching algorithm, search the database and select suitable job postings.

[0206] Step 10:

[0207] Server: Sends the generated job information list to the terminal.

[0208] Input: A list of the best job postings.

[0209] Output: A list of job postings sent to your device.

[0210] Specific operation: The server generates a job listing in JSON format and sends it to the terminal.

[0211] Step 11:

[0212] Terminal: The terminal displays the job listings on the user interface and waits for user interaction.

[0213] Input: A list of job postings sent by the server.

[0214] Output: A list of jobs displayed in a user interface.

[0215] Specific operation: The device parses the job listings and displays the list on the UI.

[0216] Step 12:

[0217] User: The user reviews the displayed job listings and selects the ones that interest them.

[0218] Input: A list of jobs displayed on a user interface.

[0219] Output: The job posting selected by the user.

[0220] What happens: User clicks on a job posting that interests them to learn more.

[0221] Step 13:

[0222] Server: The server generates and sends alerts containing the user's profile information to companies based on the selected job information.

[0223] Input: The job posting selected by the user.

[0224] Output: The alert message to be sent to the company.

[0225] Specific operation: The server generates a notification alert message and sends it to the company.

[0226] Step 14:

[0227] Company: The company receives a notification from the server, verifies the profile information provided, and takes the next step, such as scheduling an interview with the candidate.

[0228] Input: The alert message sent by the server.

[0229] Output: Interview schedule set by the company.

[0230] What happens: A company HR representative reviews the user's profile information and schedules an interview.

[0231] (Application example 1)

[0232] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0233] It is not easy for consumers to find the best products based on their preferences and budget, and they are often overwhelmed by the amount of information available. It is also difficult for businesses to find the right product approach to meet the specific needs of consumers. To solve these problems, a system is needed that provides the best product information for consumers and efficiently conveys consumer information to businesses.

[0234] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0235] In this invention, the server includes means for a user to input desired information and conditions, means for receiving the input information and saving it in a database, means for presenting the user with questions about the relevant category and budget and receiving the answers, means for saving the received answers in a database, means for analyzing the user's information and answers and generating optimal product information, means for providing the generated product information to the user, and means for providing consumer information to businesses that present product information. This enables consumers to efficiently obtain product information that best suits their needs, and enables businesses to make product suggestions that meet their targets.

[0236] "Desired information" is information about the user's requests regarding specific products or services or characteristics that the user wishes to obtain.

[0237] "Desired conditions" are the factors and criteria that a user prioritizes when selecting a product or service, and include budget, category, functions, specifications, etc.

[0238] A "database" is a collection of information that systematically stores information entered by users and information collected and generated by systems, making it easily accessible.

[0239] A "machine learning algorithm" is a method for learning patterns and rules based on large amounts of data, and predicting and classifying future data.

[0240] The "matching degree" is an index showing the compatibility between the user's desired conditions and candidate information (product information, etc.) in the database, and the higher the degree, the more suitable the product is.

[0241] "Product information" refers to detailed information about each product stored in the database, and includes multiple elements such as category, price, features, and ratings.

[0242] "Consumer information" refers to desired information and conditions entered by the user, as well as information about the user's preferences and purchasing behavior obtained from data analyzed by the system.

[0243] A "business" is an organization or company that provides goods or services and markets or sells them to consumers.

[0244] An "answer" is a specific response that a user inputs to a question presented by the system, and is information about the user's preferences and conditions.

[0245] This invention relates to a system that allows users to input desired information and conditions and provides optimal product information. The system spans terminals such as smartphones, tablets, and personal computers, as well as databases including a central server, and utilizes generative AI models to improve the user experience.

[0246] Registration Phase

[0247] User

[0248] The user inputs their desired conditions and desired information into the application on the terminal, including their name, email address, desired product category (e.g., home appliances, furniture), and budget.

[0249] Terminal

[0250] The terminal has the ability to convert input information into XML or JSON format and send it to the server, using a scripting language such as Python or the Flask framework.

[0251] server

[0252] The server analyzes the received data and stores it in a database. It creates and properly manages the database using an RDBMS such as MySQL (registered trademark). Once processing is complete, it returns a confirmation response to the terminal.

[0253] Question Phase

[0254] server

[0255] The server presents the user with predefined questions, such as "What category of products do you like?" or "What is your budget?"

[0256] Terminal

[0257] The terminal displays the received question on the user interface and waits for the user's answer.

[0258] User

[0259] The user answers each question using the terminal. For example, the user answers "Home appliances" to the question "Which category of products do you like?"

[0260] Terminal

[0261] The device collects the user's answers, converts them into JSON format, and sends them to the server.

[0262] server

[0263] The server analyzes the received response and stores it in a database.

[0264] Matching Phase

[0265] server

[0266] The server runs a matching algorithm to compare the user's desired conditions and responses with product information in the database, thereby generating optimal product information.

[0267] server

[0268] A list including the selected product information is generated and transmitted to the terminal.

[0269] Terminal

[0270] The terminal displays the product information list on a user interface.

[0271] User

[0272] The user checks the displayed product information and selects a product that interests them.

[0273] Proposal Phase

[0274] server

[0275] The server generates an alert containing the user's profile information to a business that provides product information, for example, by email or dashboard notification.

[0276] business operator

[0277] The business receives the consumer information provided by the server and formulates appropriate marketing and sales strategies.

[0278] Specific examples

[0279] If a user enters the desired conditions "home appliances" and "under 50,000 yen," the system will filter the corresponding products in the database and generate an optimal product list. For example, the result will be "Product A - Home Appliances (45,000 yen)." The business will also receive an alert stating, "User X is looking for a product in the home appliance category. His budget is under 50,000 yen."

[0280] Prompt Sentence Examples

[0281] Prompt: Given a user has specified a desired category of "Home Appliances" and a budget of "50,000 yen", generate a list of products that are optimal for him. Select products in the database that are in the Home Appliances category and are priced at or below 50,000 yen, and output the results in JSON format.

[0282] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0283] Step 1:

[0284] The user enters their desired conditions and desired information (name, email address, desired product category, budget, etc.) through the application on their device. The entered information is sent from the device to the server. At this time, the input information is converted into JSON format.

[0285] Step 2:

[0286] The server receives the JSON-formatted data sent from the device and validates the information, for example, checking that all required fields are filled in and that the data follows a specific format. Once validated, the data is stored in a MySQL database.

[0287] Step 3:

[0288] The server sends predefined questions to the user (such as "Which category of products do you like?" or "What is your budget?") in JSON format to the terminal. The content of the questions is stored in a database.

[0289] Step 4:

[0290] The terminal receives the questions sent from the server and displays them on a user interface. HTML and JavaScript (registered trademark) are used to generate the interface that waits for the user's response.

[0291] Step 5:

[0292] The user answers questions through the device interface. For example, to the question "What category of products do you like?", the user answers "Home appliances." Once the answer is entered, the device converts it back into JSON format and sends it to the server.

[0293] Step 6:

[0294] The server receives the user's answers sent from the terminal and analyzes them. This analysis includes data cleaning and format matching. Once the analysis is complete, the answers are stored in the database again.

[0295] Step 7:

[0296] The server runs a matching algorithm to search the database for matching product information based on the user's desired conditions and responses. For example, this algorithm filters products whose "desired product category" is "home appliances" and whose "budget" is 50,000 yen or less.

[0297] Step 8:

[0298] The server creates a list of the results of the matching algorithm (for example, "Product A - Home Appliance (45,000 yen)") and sends it to the terminal. This list is again in JSON format.

[0299] Step 9:

[0300] The terminal receives the product information list sent from the server and displays it on the user interface, allowing the user to check the list and select products that interest them.

[0301] Step 10:

[0302] The server generates an alert containing the user's profile information and sends it to the product information provider in the form of an email or dashboard notification. For example, "User X is looking for a product in the home appliance category with a budget of 50,000 yen or less."

[0303] Step 11:

[0304] Businesses receive the consumer information sent from the server and use it as basic data for formulating appropriate marketing and sales strategies.

[0305] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0306] This invention is a system that provides optimal job information to job seekers, and by combining it with an emotion engine, it achieves optimal job matching that takes into account the user's emotional state. Users input their work history and desired conditions into a terminal, and the server receives and analyzes this information to generate and provide optimal job information. Furthermore, by using the emotion engine to recognize the user's emotional state and utilizing this information, it is possible to achieve more accurate matching.

[0307] System configuration

[0308] This system includes a terminal used by the user, a server, a database, and an emotion engine. The user uses the terminal to access the system and input and receive information. The server receives the input information and stores and analyzes it in the database. The emotion engine recognizes emotions from the user's input information and responses, and provides the results to the server.

[0309] Explanation of program processing

[0310] Registration Phase

[0311] User: The user enters their work history information and desired conditions into the terminal, specifically, their name, address, past work history, skill set, and desired work environment.

[0312] Terminal: The terminal receives the input information and converts it into a specified format such as JSON.

[0313] Terminal: Sends the converted data to the server via an HTTP POST request.

[0314] Server: The server analyzes the received data, checks its validity, and then saves it in the database. It then sends a processing completion response to the terminal.

[0315] Question Phase

[0316] Server: The server sends a list of predefined questions to the user on the device, such as "Do you value teamwork?" or "Do you prefer to work for a company that allows remote work?"

[0317] Terminal: The terminal displays the question in a user interface.

[0318] User: The user enters an answer to each question, for example, "Do you value teamwork?"

[0319] Terminal: The terminal collects the responses, converts them into JSON format, and sends them to the server.

[0320] Server: The server analyzes the received response and stores it in a database.

[0321] Emotion Recognition Phase

[0322] Server: The server sends the user's input information and responses to the emotion engine.

[0323] Emotion Engine: The emotion engine analyzes the received inputs and responses to recognize the user's emotional state (e.g., stress, joy, anxiety).

[0324] Emotion engine: Sends the recognized emotional state to the server.

[0325] Server: The server stores the emotional state data in a database.

[0326] Matching Phase

[0327] Server: The server runs a matching algorithm based on the user's work history and emotional state, which calculates the degree of match between the job listings in the database and the user's information.

[0328] Server: Uses a matching algorithm to list the most suitable job information and generates JSON data to send to the terminal.

[0329] Terminal: The terminal displays the job listings on a user interface.

[0330] User: The user reviews the displayed job listings and selects the job listings that interest them.

[0331] Proposal Phase

[0332] Server: The server generates alerts to the enterprise that include the user's profile information and emotional state.

[0333] Server: Sends an alert to the company's HR department containing the profile information and emotional state of the selected candidate.

[0334] Corporate User: The corporate user reviews the received candidate information and emotional state and decides on interviews and next steps.

[0335] Specific examples

[0336] Example of the registration phase

[0337] User: Taro Yamada accesses the system and enters his name, address, past work experience (e.g., 5 years of Java development experience), skill set (e.g., Java, Python), and desired work environment (e.g., remote work acceptable).

[0338] Terminal: The terminal converts this information into JSON format and sends it to the server.

[0339] Server: After receiving the data and verifying its validity, the server stores it in a database and returns a processing completion response to the terminal.

[0340] Specific example of the question phase

[0341] Server: The server sends the question "Do you value teamwork?" to the device.

[0342] Terminal: The terminal presents the received question to the user.

[0343] User: Yamada answers "Yes" and sends the answer to the server via his terminal.

[0344] Server: The server receives the answer and stores it in a database.

[0345] A concrete example of the emotion recognition phase

[0346] Server: The server sends Yamada's information and response to the emotion engine.

[0347] Emotion Engine: The emotion engine analyzes Yamada's input and responses and recognizes his emotional state (e.g., joy).

[0348] Emotion engine: Sends the recognized emotional state to the server.

[0349] Server: The server stores the emotional states in a database.

[0350] A concrete example of the matching phase

[0351] Server: Based on Yamada's profile, responses, and emotional state, the server uses a matching algorithm to analyze the job listings in the database and select the most suitable job listing.

[0352] Server: Generates a list containing suitable job information (e.g., "Company B - Java Engineer (remote work available)") and sends it to the device.

[0353] Terminal: The terminal displays this list to Yamada.

[0354] User: Yamada checks the displayed job information and selects the information that interests him.

[0355] Specific example of the proposal phase

[0356] Server: The server generates and sends an alert to Company B containing Yamada's profile information and emotional state.

[0357] Corporate: Corporate HR personnel review the received profile information and emotional state and schedule an interview.

[0358] In this way, a system can be constructed that takes into account the user's emotional state and achieves more accurate job change matching.

[0359] The processing flow will be explained below.

[0360] Step 1:

[0361] Users enter their work history information and desired conditions into the terminal, specifically, their name, address, past work history, skill set (e.g., Java, Python), and desired work environment (e.g., remote work allowed).

[0362] Step 2:

[0363] The terminal receives the input information and converts it into a specified format such as JSON.

[0364] Step 3:

[0365] The terminal sends the converted data to the server via an HTTP POST request.

[0366] Step 4:

[0367] The server parses the received data and validates it, checking that all required fields are present, that the format is correct, etc.

[0368] Step 5:

[0369] The server saves the data that has been successfully validated in the database, and once the saving is complete, it sends the processing result to the terminal as a response.

[0370] Step 6:

[0371] The server sends a list of questions to the user in JSON format to present questions about their job duties and work environment to the terminal.

[0372] Step 7:

[0373] The terminal displays the received question list on the user interface.

[0374] Step 8:

[0375] The user inputs an answer to the displayed question, for example, "Do you value teamwork?", and answers "Yes."

[0376] Step 9:

[0377] The terminal collects the answers entered by the user, converts them back into JSON format, and sends them to the server.

[0378] Step 10:

[0379] The server analyzes the received response and stores it in a database.

[0380] Step 11:

[0381] The server sends the user's input information and responses to the emotion engine.

[0382] Step 12:

[0383] The emotion engine analyzes the received inputs and responses to recognize the user's emotional state (e.g., stress, joy, anxiety).

[0384] Step 13:

[0385] The emotion engine transmits the recognized emotional state to the server.

[0386] Step 14:

[0387] The server stores the emotional states in a database.

[0388] Step 15:

[0389] The server runs a matching algorithm based on the user's work history and emotional state, and calculates the degree of match between the job listings in the database and the user's information.

[0390] Step 16:

[0391] The server lists the most suitable job information and generates JSON data to send to the terminal.

[0392] Step 17:

[0393] The terminal displays the received job information list on the user interface.

[0394] Step 18:

[0395] The user checks the displayed job listings and selects the job listings that interest them.

[0396] Step 19:

[0397] The server generates alerts to businesses associated with selected job postings, providing information and sentiment of suitable candidates.

[0398] Step 20:

[0399] The server sends an alert to the company's HR department containing the profile information and emotional state of the selected candidate.

[0400] Step 21:

[0401] The company user reviews the received candidate information and emotional state and decides on interviews and next steps.

[0402] Example 2

[0403] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0404] Conventional job information systems only provide job information based on the user's work history and desired conditions, and do not perform job matching that takes into account the user's emotional state. As a result, it is difficult to provide job information that matches the user's actual desires and emotional state, and it has not been possible to achieve highly accurate matching.

[0405] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0406] In this invention, the server includes means for a user to input work history information and desired conditions, means for receiving the input information and saving it in a database, means for presenting questions to the user regarding job content and work environment and receiving answers, means for saving the received answers in a database, means for analyzing the user's information and answers and using an emotion engine that recognizes the user's emotional state, means for generating optimal job information based on the recognized emotional state and the user's information, means for providing the generated job information to the user, and means for providing candidate information to companies that submit job information. This enables highly accurate matching of job information that takes the user's emotional state into consideration.

[0407] "User" refers to an individual who accesses the system, inputs work history information and desired conditions, and is provided with the most suitable job information.

[0408] "Work history information" refers to information including a user's previous work experience, skill set, and related accomplishments.

[0409] "Desired conditions" refers to conditions including the user's desired work environment, working conditions, work location, salary, etc.

[0410] "Input means" refers to the interface or device that allows a user to provide their work history information and desired conditions to the system.

[0411] "Means for receiving and storing in a database" refers to the process by which the server receives the information sent by the user and stores it in a database.

[0412] The "means for presenting questions and receiving answers" refers to a method by which the server asks the user questions about the job content and work environment and receives the user's answers.

[0413] "Means for storing the received answers in a database" refers to the process by which the server receives answers from users and stores them in a database.

[0414] "Means for analyzing and using an emotion engine to recognize an emotional state" refers to a process in which the server analyzes the user's information and answers and uses an emotion engine to recognize the user's emotional state.

[0415] "Means for generating optimal job information based on the recognized emotional state and user information" refers to a process for generating optimal job information by combining the emotional state recognized by the emotion engine with the user's work history information and desired conditions.

[0416] The "means for providing the generated job information to the user" refers to a means for presenting the job information generated by the server to the user.

[0417] "Means for providing candidate information to companies that post job information" refers to the process by which the server provides information on selected candidates to companies.

[0418] An "emotion engine" refers to software or algorithms that recognize a user's emotional state from their input and responses.

[0419] "Machine learning algorithm" refers to a technology that learns patterns from data and performs analysis and predictions.

[0420] "Means for calculating the degree of matching" refers to the algorithm or process for comparing user information with job information, calculating the degree of matching, and making the best match.

[0421] This invention is a system that provides optimal job information to job seekers, and by combining it with an emotion engine, it realizes optimal job matching that takes into account the user's emotional state. Specifically, the user inputs their work history and desired conditions using a terminal, and the server receives and analyzes this to generate and provide optimal job information. Furthermore, the emotion engine is used to recognize the user's emotional state, and job information that reflects this is provided.

[0422] Hardware and Software Configuration

[0423] This system includes a device used by the user, a server that receives and analyzes data, a database that stores the data, and an emotion engine that recognizes emotions. The device can be a regular computer or smartphone, while a high-performance computer system is suitable for the server. The server has a database management system (DBMS) and emotion recognition software installed.

[0424] Overview of program processing

[0425] The server performs the following program processing.

[0426] 1. Receiving and storing user information

[0427] The user enters their work history and desired job requirements using a terminal. The terminal receives this information, converts it into JSON format, and sends it as an HTTP POST request to the server. The server analyzes the received information and stores it in a database.

[0428] 2. Posting Questions and Receiving Answers

[0429] The server sends predefined questions to the user's device. For example, questions like "Do you value teamwork?" or "Do you prefer a company that allows remote work?" The user answers these questions, and the device collects the user's answers, converts them into JSON format, and sends them to the server. The server parses the answers and stores them in a database.

[0430] 3. Recognizing emotional states

[0431] The server sends the user's input information and answers to the emotion engine. The emotion engine analyzes this information and recognizes the user's emotional state. For example, it detects positive emotions (joy) from the user's answers. The recognized emotional state is sent to the server, which stores it in a database.

[0432] 4. Job information matching and provision

[0433] The server runs a matching algorithm to match job listings in the database based on the user's work history, desired conditions, and recognized emotional state. It selects the most suitable job listing and sends the results to the terminal. The terminal then displays the most suitable job listing to the user.

[0434] 5. Providing information to companies

[0435] Once the user selects the job postings they are interested in, the server provides that information to the company, which then receives the candidate's profile information and emotional state and uses that information to carry out the next steps (such as setting up an interview).

[0436] Specific examples

[0437] For example, a job seeker named Taro Yamada accesses the system and enters his name, address, work history (e.g., 5 years of Java development experience), skill set (e.g., Java, Python), and desired conditions (e.g., willingness to work remotely). The terminal converts this information into JSON format and sends it to the server. The server receives the information and stores it in a database.

[0438] Next, the server asks Yamada, "Do you value teamwork?", and Yamada answers "Yes." The device converts this answer into JSON format and sends it to the server. The server receives the answer and stores it in a database.

[0439] The server then sends Yamada's information and answer to the emotion engine, which recognizes the positive emotion (joy). This emotional state is sent to the server and stored in a database.

[0440] Finally, the server matches Yamada's information and emotional state with job listings in the database and selects the most suitable one (e.g., "Company B - Java Engineer (remote work available)"). This information is sent to the device and displayed to Yamada. If Yamada shows interest, the server provides the information to the company, which then schedules an interview.

[0441] Prompt Sentence Examples

[0442] Please enter your work history information

[0443] Please tell us your preferred work environment

[0444] "Do you value teamwork?"

[0445] "Do you want a company that allows you to work remotely?"

[0446] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0447] Step 1: Enter your user information

[0448] User: A user accesses the system using a terminal and enters their work history information (e.g., name, address, work experience, skill set) and desired conditions (e.g., desired work environment). For example, Taro Yamada enters "5 years of Java development experience" and "preferred remote work."

[0449] Input: Name, address, work experience, skill set, desired work environment.

[0450] Output: JSON format data of user input information.

[0451] Terminal: The terminal receives this information in real time, converts it into a specified JSON format, checks the converted JSON data, and displays a button to proceed to the next step.

[0452] Step 2: Sending data

[0453] Terminal: The terminal sends the converted JSON data to the server as an HTTP POST request. Specifically, the following is an example request: "POST / register { "name": "Yamada Taro", "address": "Shinjuku-ku, Tokyo", "experience": "5 years of Java development experience", "skills": ["Java", "Python"], "preferences": "Remote work available"}"

[0454] Input: User information data in JSON format.

[0455] Output: A message confirming the completion of the transmission.

[0456] Server: The server receives the HTTP POST request and checks the validity of the data. After checking, it saves the information in the database and returns a processing completion response to the terminal. Example: "HTTP / 1.1 200 OK { "status": "success", "message": "User data saved successfully"}"

[0457] Step 3: Posting a question and receiving an answer

[0458] Server: The server sends predefined questions to the device. For example, "Do you value teamwork?" or "Do you want to work for a company that allows remote work?"

[0459] Input: A predefined question in text format.

[0460] Output: Question list data in JSON format.

[0461] Terminal: The terminal launches an interface to display the received list of questions to the user, for example, providing a "yes" or "no" option for each question.

[0462] User: The user answers each question. For example, "Do you value teamwork?" with "Yes."

[0463] Input: User's answer (in text format).

[0464] Output: JSON format data of user responses.

[0465] Terminal: The terminal collects the user's answers, converts them back into JSON format, and sends them to the server.

[0466] Step 4: Recognizing your emotional state

[0467] Server: The server sends the user's input information and responses to the emotion engine.

[0468] Input: JSON format data of user information and answers.

[0469] Output: JSON format data of the emotional state and its confidence.

[0470] Emotion Engine: The emotion engine analyzes the incoming data and recognizes the user's emotional state. Example: "Emotional state: joy, confidence: 0.85"

[0471] Server: Receives the emotional state sent from the emotion engine and stores it in a database.

[0472] Step 5: Job Matching

[0473] Server: The server uses a matching algorithm to analyze job listings in the database based on the user's work history, desired conditions, and perceived emotional state.

[0474] Input: JSON format data of user information, desired conditions, and emotional state.

[0475] Output: Matching results in JSON format.

[0476] Server: Runs a matching algorithm and selects the job listing that best suits the user. Example: "Company B - Java Engineer (Remote work available)"

[0477] Server: Generates a list of selected job information in JSON format and sends it to the terminal.

[0478] Step 6: View your job listings

[0479] Device: Display the received job information list on the user interface. Example: "Company B - Java Engineer (remote work available)"

[0480] Input: JSON format data for job listings.

[0481] Output: Job listing screen.

[0482] User: The user reviews the displayed job listings and selects the job listings that interest them.

[0483] Step 7: Provide information to companies

[0484] Terminal: Notifies the server of the job information selected by the user. Example: Sends JSON data including the ID of the selected job information.

[0485] Input: The ID of the selected job posting.

[0486] Output: A message confirming your selection.

[0487] Server: The server sends the user's profile information and emotional state to the company's HR system based on the selected job information. Example: "JSON data containing the candidate profile and emotional state."

[0488] Input: JSON format data of user profile information and emotional state.

[0489] Output: A message confirming notification to the company.

[0490] Company: Based on the received information, the company's human resources personnel will carry out the next process (e.g., scheduling an interview).

[0491] (Application example 2)

[0492] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0493] Conventional job information systems only consider the user's career history and desired conditions, and there are challenges in improving the accuracy of job matching by incorporating the user's emotional state. Furthermore, there is a lack of proposals for products and services that correspond to the emotional state of each individual user. Therefore, it is necessary to develop a system that provides optimal job information that takes into account the user's emotional state and proposes products and services that correspond to the user's emotional state.

[0494] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0495] In this invention, the server includes a means for a user to input work history information and desired conditions, a means for receiving the input information and storing it in a database, and a means for presenting questions to the user regarding the job content and work environment and receiving the answers, thereby making it possible to collect the user's work history information and desired conditions.

[0496] The system further includes a means for storing the received responses in a database, a means for analyzing the user's information and responses and generating optimal job information, a means for providing the generated job information to the user, and a means for providing candidate information to companies that submit job information. This makes it possible to provide optimal job information from the collected information to the user and to appropriately provide candidate information to companies.

[0497] The system also includes a means for analyzing the user's input information and responses using an emotion engine to recognize the user's emotional state, and a means for recommending optimal products and services in consideration of the user's emotional state. This makes it possible to provide highly accurate job information that incorporates the user's emotional state, and to suggest products and services according to the user's emotional state.

[0498] "Means for users to input their work history information and desired working conditions" refers to the interface that allows job seekers to input their work history and desired working conditions into the system.

[0499] "Means for receiving input information and storing it in a database" refers to the function by which the system receives information input by job seekers and stores that information in a database.

[0500] "Means of presenting questions about job content and work environment and receiving answers" refers to the function of presenting questions about the work environment and job content to job seekers and collecting their answers.

[0501] "Means for storing received responses in a database" refers to the function by which the system receives responses collected from job seekers and stores them in a database.

[0502] "Means for analyzing user information and responses and generating optimal job information" refers to algorithms and programs that analyze data based on the information and responses provided by job seekers and create job information that best matches them.

[0503] The "means for providing generated job information to a user" refers to an interface for displaying or notifying job seekers of the job information resulting from the analysis.

[0504] "Means of providing candidate information to companies posting job openings" refers to the function of providing information on job seekers' profiles and suitability to companies posting job openings.

[0505] An "emotion engine" refers to a system that analyzes a user's input information and responses to evaluate the user's emotional state.

[0506] "Means for recognizing the user's emotional state" refers to a function that uses an emotion engine to detect the user's current emotional state and reflects that information in the system.

[0507] "Means for recommending optimal products and services taking into account the user's emotional state" refers to algorithms or programs that suggest the most suitable products and services to a user based on the user's emotional state.

[0508] A "machine learning algorithm" is a type of computer program used to create predictive models in data analysis.

[0509] MODE FOR CARRYING OUT THE INVENTION

[0510] This invention is a system that provides optimal job information by analyzing the user's work history and desired conditions after inputting the information. It also uses an emotion engine to consider the user's emotional state, and can provide job information and recommend products and services based on the user's emotions.

[0511] Hardware and software used

[0512] Hardware: Smartphone camera, microphone

[0513] Software: OpenCV, EmotionRecognizer (proprietary emotion recognition engine), RecommendationEngine (proprietary recommendation engine)

[0514] System configuration

[0515] This system includes a terminal used by the user, a server, a database, and an emotion engine, and is realized using the following hardware and software:

[0516] Terminal

[0517] Users access the system using a device such as a smartphone and enter their work history and desired conditions. The device receives the entered information and sends it to the server via an HTTP POST request. An interface is also provided for users to enter their work history and desired conditions into the device.

[0518] server

[0519] The server analyzes the information received from the device and stores it in a database. The server also sends a list of predefined questions to the user to the device, receives the answers, and stores them in a database. Furthermore, the server uses an emotion engine to analyze and recognize the user's emotional state based on the user's input information and answers. The recognized emotional state data is stored in a database.

[0520] Emotion Engine

[0521] The emotion engine recognizes the user's emotional state (e.g., stress, joy, anxiety) based on the user's information and responses sent from the server. This makes it possible to provide optimal job information that takes the user's emotional state into consideration. In addition, the recommendation engine recommends products and services that are suitable for the user based on the emotional state recognized by the emotion engine.

[0522] Data processing and calculation

[0523] The server uses the Emotion Engine and Recommendation Engine to process and calculate data as follows:

[0524] 1. Emotion Recognition: We use OpenCV to capture video from a smartphone camera and EmotionRecognizer to analyze the user's emotional state. Specifically, we analyze facial expression data to recognize emotions such as stress, joy, and anxiety.

[0525] 2. Data analysis: Based on the user's work history, desired conditions, and responses, the system uses a recommendation algorithm to analyze and generate optimal job listings. It also suggests products and services based on the user's emotional state.

[0526] Specific examples

[0527] Example 1: Providing job information based on the user's emotional state

[0528] A user logs into the system and enters their work history information (e.g., 5 years of Java development experience) and desired work environment (e.g., remote work acceptable). After answering corresponding questions (e.g., "Do you value teamwork?"), emotion recognition is performed using the smartphone camera. Through this process, the emotional state of "joy" is recognized. Based on this information, the server provides the user with job information that is most suitable for them.

[0529] Example 2: Product suggestions based on emotional state

[0530] Based on user input and emotion recognition data from the camera (e.g., high stress), the recommendation engine suggests relaxing products (e.g., a tea set with a relaxing effect).

[0531] Example prompts for generative AI models

[0532] "Design an application that analyzes a user's emotional state based on facial expression data, and recommends products that have a relaxing effect if the user's stress level is recognized as high."

[0533] As described above, we provide a highly accurate job information providing system that incorporates the user's emotional state, and a mechanism for recommending products and services based on the user's emotional state.

[0534] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0535] Step 1:

[0536] The user inputs work history information and desired conditions.

[0537] Input: User's work history (e.g., 5 years of Java development experience) and desired conditions (e.g., remote work acceptable)

[0538] How it works: Input is made through the smartphone interface, and the device receives the information, converts it into JSON format, and sends it to the server.

[0539] Output: User's work history and desired conditions sent to the server

[0540] Step 2:

[0541] The server receives the entered information and stores it in a database.

[0542] Input: User's work history and desired conditions sent from the device (JSON format)

[0543] How it works: The server parses the information, validates the data, and then stores it in a database.

[0544] Output: User information stored in the database

[0545] Step 3:

[0546] The server presents the user with questions about their job duties and work environment and receives their answers.

[0547] Input: User's work history and desired conditions stored in the database

[0548] How it works: The server generates a list of predefined questions and sends them to the terminal via HTTP requests. The user enters answers to the questions, and the terminal receives the answers and sends them to the server.

[0549] Output: User's answer sent to the server

[0550] Step 4:

[0551] The server stores the received response in a database.

[0552] Input: User's answer (e.g., "Do you value teamwork?": "Yes")

[0553] How it works: The server stores the received answers in a database and prepares them for analysis.

[0554] Output: User answers stored in the database

[0555] Step 5:

[0556] The server sends the user's input information and responses to the emotion engine.

[0557] Input: User information and answers stored in a database

[0558] How it works: The server sends the user's information and responses to the emotion engine, which analyzes it and recognizes the user's emotional state.

[0559] Output: The user's emotional state as recognized by the emotion engine (e.g., stress, joy, anxiety)

[0560] Step 6:

[0561] The server stores the emotional state data in a database.

[0562] Input: The user's emotional state sent from the emotion engine

[0563] How it works: The server stores the recognized emotional state in a database.

[0564] Output: User's emotional state stored in a database

[0565] Step 7:

[0566] The server runs a matching algorithm based on the user's work history, responses, and emotional state to generate job information.

[0567] Input: User's work history information, responses, and emotional state stored in a database

[0568] How it works: The server runs a matching algorithm to calculate the degree of match with jobs in the database.

[0569] Output: The best job listings generated

[0570] Step 8:

[0571] The server provides the generated job information to the user.

[0572] Input: Generated best-fit job listings

[0573] Operation: The server converts the job information into JSON format and sends it to the terminal as an HTTP response, which displays it on the user interface.

[0574] Output: Job listing displayed on terminal

[0575] Step 9:

[0576] Taking into account the user's emotional state, the server recommends the most suitable products and services.

[0577] Input: User's emotional state, purchase history, and category information of interest

[0578] How it works: The Recommendation Engine analyzes the user's emotional state and recommends the most suitable products and services. The server sends the results to the device, which displays them on the user interface.

[0579] Output: Recommendations for products and services displayed on the device

[0580] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0581] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0582] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0583] [Second embodiment]

[0584] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0585] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0586] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0587] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0588] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0589] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0590] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0591] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0592] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0593] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0594] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0595] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0596] This invention relates to a system that provides optimal job information to job seekers. Users input their work history and desired conditions, and a server receives and analyzes them to generate and provide optimal job information.

[0597] System configuration

[0598] This system includes a terminal used by the user, a database, and a server. Users use their terminal to access the system and input and receive information. The server receives the information and stores and analyzes it in the database.

[0599] Explanation of program processing

[0600] Registration Phase

[0601] User: The user enters their work history information and desired conditions into the terminal, including name, address, past work experience, skill set (e.g., Java, Python), and desired work environment (e.g., remote work acceptable).

[0602] Terminal: The terminal receives the input information, converts it into a specific data format (such as JSON), and sends it to the server.

[0603] Server: The server analyzes the received data and stores it in a database. Once the data is stored, it sends a confirmation response to the device.

[0604] Question Phase

[0605] Server: The server presents the user with predefined questions, such as "Do you value teamwork?" or "Do you prefer a company that allows remote work?"

[0606] Terminal: The terminal displays these questions in a user interface and waits for user input.

[0607] User: The user answers each question using a terminal. For example, the user answers "Yes" to the question "Do you value teamwork?"

[0608] Terminal: The terminal collects the user's answers, converts them into the specified data format, and sends them to the server.

[0609] Server: The server analyzes the received response and stores it in a database.

[0610] Matching Phase

[0611] Server: The server runs a matching algorithm based on the user's work history and answers, which allows the server to compare the user's information with job listings in its database and select the most suitable job listing.

[0612] Server: Generates a list containing selected job information and sends it to the terminal.

[0613] Terminal: The terminal displays the job listings on a user interface.

[0614] User: The user reviews the displayed job information and selects the job that interests them.

[0615] Proposal Phase

[0616] Server: The server generates an alert to the company providing the user's profile information, such as "Candidate A has been added to your job seeker list. His skill set and desired conditions match your job posting."

[0617] Company: The company receives the candidate information provided by the server and schedules interviews and next steps.

[0618] Specific examples

[0619] Example of the registration phase

[0620] User: Taro Yamada accesses the system and enters his name, address, past work experience (e.g., 5 years of Java development experience), skill set (e.g., Java, Python), and desired work environment (e.g., remote work acceptable).

[0621] Terminal: The terminal converts this information into JSON format and sends it to the server.

[0622] Server: After receiving the data and verifying its validity, the server stores it in a database and returns a processing completion response to the terminal.

[0623] Specific example of the question phase

[0624] Server: The server sends the question "Do you value teamwork?" in JSON format to the terminal.

[0625] Terminal: The terminal presents the received question to the user.

[0626] User: Yamada answers "Yes" and sends the answer to the server via his terminal.

[0627] Server: The server receives the answer and stores it in a database.

[0628] A concrete example of the matching phase

[0629] Server: Based on Yamada's profile and answers, the server uses a matching algorithm to analyze the job listings in the database and select the most suitable job listing.

[0630] Server: Generates a list containing suitable job information (e.g., "Company B - Java Engineer (remote work available)") and sends it to the device.

[0631] Terminal: The terminal displays this list to Yamada.

[0632] User: Yamada checks the displayed job information and selects the information that interests him.

[0633] Specific example of the proposal phase

[0634] Server: The server generates and sends an alert to Company B containing Taro Yamada's profile information.

[0635] Company: The company's HR will review the profile information received and schedule an interview.

[0636] In this way, a system can be constructed that realizes efficient and highly accurate job-change matching for both users and companies.

[0637] The processing flow will be explained below.

[0638] Step 1:

[0639] Users enter their work history information and desired conditions into a terminal, specifically, their name, address, past work history, skill set, and desired work environment.

[0640] Step 2:

[0641] The terminal receives the input information and converts it into a specified format such as JSON.

[0642] Step 3:

[0643] The terminal sends the converted data to the server via an HTTP POST request.

[0644] Step 4:

[0645] The server parses the received data and validates it, checking that all required fields are present, that the format is correct, etc.

[0646] Step 5:

[0647] The server saves the data that has been successfully validated in the database, and once the saving is complete, it sends the processing result to the terminal as a response.

[0648] Step 6:

[0649] The server sends a list of questions to the user in JSON format to present questions about their job duties and work environment to the terminal.

[0650] Step 7:

[0651] The terminal displays the received question list on the user interface.

[0652] Step 8:

[0653] The user inputs an answer to the displayed question, for example, "Do you value teamwork?", and answers "Yes."

[0654] Step 9:

[0655] The terminal collects the answers entered by the user, converts them back into JSON format, and sends them to the server.

[0656] Step 10:

[0657] The server analyzes the received responses and stores them in a database, adding them to the user's profile.

[0658] Step 11:

[0659] The server runs a matching algorithm based on the user's work history and responses, calculating the degree of match between the job listings in the database and the user's information.

[0660] Step 12:

[0661] The server lists the most suitable job information and generates JSON data to send to the terminal.

[0662] Step 13:

[0663] The terminal displays the received job information list on the user interface.

[0664] Step 14:

[0665] The user checks the displayed job listings and selects the job listings that interest them.

[0666] Step 15:

[0667] The server generates alerts to businesses associated with the selected job postings, providing information about suitable candidates.

[0668] Step 16:

[0669] The server sends an alert to the company's HR department containing the profile information of the selected candidate.

[0670] Step 17:

[0671] The corporate user reviews the received candidate information and decides on interviews and next steps.

[0672] Example 1

[0673] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0674] Conventional job information systems simply accept the work history information and desired conditions entered by users, and the accuracy of providing job information based on that information is low, making it difficult to provide appropriate job information that meets the user's needs.In addition, the analysis of user information and optimization of job information are limited, and detailed candidate information cannot be provided to companies, resulting in low efficiency in matching companies and users.

[0675] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0676] In this invention, the server includes means for receiving information entered by a user, converting it into a specific data format, and saving it in a database, means for presenting the user with questions about job content and work environment and receiving answers, means for saving the received answers in a database, means for analyzing the user's information and the received answers and using a matching algorithm to generate optimal job information, means for providing the generated optimal job information to the user, and means for providing user profile information to companies that submit job information. This makes it possible to provide highly accurate job information based on the user's detailed needs, and improves the efficiency of matching companies and users.

[0677] A "user" is an individual who uses this system to input work history information and desired conditions in order to obtain the most suitable job information.

[0678] "Work history information" refers to information such as the jobs, positions, and skill sets that a user has had up to now.

[0679] "Desired conditions" are the user's desired work environment, working conditions, work location, and other requirements.

[0680] "Input means" refers to an interface that allows a user to input information into the system, and is primarily operated via a terminal.

[0681] "Data format" refers to a format in which information is expressed as structured data in a certain format, such as JSON format.

[0682] A "database" is a digital storage system that can efficiently store, manage, and search structured data.

[0683] The "means for presenting questions" refers to an interface through which the server displays questions about the job content and work environment to the user.

[0684] The "means for receiving an answer" refers to an interface that allows the system to receive and analyze answers to questions returned by users.

[0685] A "matching algorithm" is a calculation method for selecting the most suitable job information based on the user's work history, desired conditions, and responses.

[0686] "Job information" refers to detailed information provided by companies about job types, positions, and related conditions.

[0687] "Profile information" is information that compiles the user's work history, skill set, desired conditions, and the like.

[0688] A "secure protocol" is a communication protocol for securely transmitting information, and includes, for example, HTTPS.

[0689] This invention relates to a system that provides optimal job information to job seekers. A user inputs their work history and desired conditions, and a server receives and analyzes the information to generate and provide optimal job information. The system includes a terminal used by the user, a database, and a server. Detailed modes for implementing the invention are described below.

[0690] System configuration

[0691] User: A user accesses the system using a terminal and enters their work history and preferences, such as their name, address, past work experience, skill set, and desired work environment.

[0692] Terminal: The terminal receives the information entered by the user and converts it into a specific data format (e.g., JSON format), which is then sent to the server via a secure protocol (e.g., HTTPS).

[0693] Server: The server analyzes the received data and stores it in a database. It presents the user with questions about the job content and work environment, and also receives and stores the answers to the questions in a database. The server analyzes the user's work history and desired conditions and generates optimal job information using a generative AI model.

[0694] Specific examples

[0695] Example of the registration phase

[0696] User: A job seeker accesses the system and enters their name, address, past work experience (e.g., 5 years of Java development experience), skill set (e.g., Java, Python), and desired work environment (e.g., remote work acceptable).

[0697] Terminal: The terminal converts this information into JSON format and sends it to the server.

[0698] Server: The server receives the data, verifies its validity, and then saves it in the database. Once the saving is complete, it returns a processing completion response to the terminal.

[0699] Specific example of the question phase

[0700] Server: The server generates the question "Do you value teamwork?" through a generative AI model and sends it to the device in JSON format.

[0701] Terminal: The terminal presents the received question to the user.

[0702] User: The user answers "yes" and sends the answer to the server via the terminal.

[0703] Server: The server receives the response and stores it in a database.

[0704] A concrete example of the matching phase

[0705] Server: Based on the user's work history information and answers to questions, the server uses a generative AI model to analyze the job listings in the database and generate the most suitable job listings.

[0706] Server: Generates a list containing suitable job information (e.g., "Company - Java Engineer (Remote Work Available)") and sends it to the device.

[0707] Terminal: The terminal displays this list to the user.

[0708] User: The user reviews the displayed job listings and selects the ones that interest them.

[0709] Specific example of the proposal phase

[0710] Server: The server generates and sends an alert to the company containing the user's profile information, stating, "The candidate has been added to your job seeker list. His skill set and preferences match your job opening."

[0711] Company: The company's HR will review the profile information received and schedule an interview.

[0712] Prompt Sentence Examples

[0713] "Please analyze the work history information and desired conditions entered by the user and generate the most suitable job information."

[0714] "Present users with a question about whether they value teamwork."

[0715] Based on the above steps, efficient and highly accurate job-change matching can be achieved for both users and companies.

[0716] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0717] Step 1:

[0718] User: The user enters their work history information and desired conditions into the terminal, specifically, their name, address, past work history (e.g., 5 years of Java development experience), skill set (e.g., Java, Python), and desired work environment (e.g., remote work acceptable).

[0719] Input: User enters work history information and desired qualifications.

[0720] Output: Information typed into the terminal.

[0721] Specific operation: The user enters the required information into the input form and clicks the submit button.

[0722] Step 2:

[0723] Terminal: The terminal receives the input information, converts it into JSON format data, and then sends this data to the server using a secure protocol (e.g., HTTPS).

[0724] Input: The work history information and desired conditions entered by the user into the terminal.

[0725] Output: JSON formatted data sent to the server.

[0726] Specific operation: The device internally converts the information into JSON format and sends the data to the server using HTTPS.

[0727] Step 3:

[0728] Server: The server analyzes the received data and saves it in the database. It verifies the validity of the data and returns an error message to the terminal if the data is invalid. If the data is normal, it saves it and then sends a response indicating that processing is complete.

[0729] Input: JSON format data sent from the terminal.

[0730] Output: User information saved in the database and a response indicating completion of the process.

[0731] Specific operation: The server verifies the validity of the data, and if it is normal, saves it in the database and sends a response to the terminal indicating that processing is complete.

[0732] Step 4:

[0733] Server: The server generates predefined questions for the user through a generative AI model and sends them to the terminal in JSON format.

[0734] Input: A prompt for the generative AI model.

[0735] Output: The JSON data of the question sent to the terminal.

[0736] Specific operation: The server generates a question using the generative AI model and sends it to the device.

[0737] Step 5:

[0738] Terminal: The terminal displays the received question on the user interface (UI). While waiting for the user's answer, it displays an answer input screen to the user.

[0739] Input: JSON data of the question sent by the server.

[0740] Output: The question displayed on the user interface.

[0741] Specific operation: The device analyzes the question data received and displays the question on the UI.

[0742] Step 6:

[0743] User: The user answers questions displayed on the device. For example, the user answers "Yes" to the question "Do you value teamwork?"

[0744] Input: The question displayed from the terminal.

[0745] Output: The answer typed into the terminal.

[0746] Specific behavior: The user enters an answer and clicks the submit button.

[0747] Step 7:

[0748] Terminal: The terminal collects the user's answers, converts them back into JSON format, and sends them to the server.

[0749] Input: The answer entered by the user.

[0750] Output: The JSON formatted response data sent to the server.

[0751] Specific operation: The device converts the response data into JSON format and sends it to the server using HTTPS.

[0752] Step 8:

[0753] Server: The server receives the response data, analyzes it, and stores it in a database.

[0754] Input: JSON formatted response data sent from the device.

[0755] Output: Response data stored in a database.

[0756] Specific operation: The server analyzes the received response data and stores it in the database.

[0757] Step 9:

[0758] Server: The server runs a matching algorithm based on the user's work history and answers to generate the most suitable job listings. The generated job listings are then listed in JSON format.

[0759] Input: User information and response data stored in a database.

[0760] Output: A list of the best job listings.

[0761] Specific operation: Launch the matching algorithm, search the database and select suitable job postings.

[0762] Step 10:

[0763] Server: Sends the generated job information list to the terminal.

[0764] Input: A list of the best job postings.

[0765] Output: A list of job postings sent to your device.

[0766] Specific operation: The server generates a job listing in JSON format and sends it to the terminal.

[0767] Step 11:

[0768] Terminal: The terminal displays the job listings on the user interface and waits for user interaction.

[0769] Input: A list of job postings sent by the server.

[0770] Output: A list of jobs displayed in a user interface.

[0771] Specific operation: The device parses the job listings and displays the list on the UI.

[0772] Step 12:

[0773] User: The user reviews the displayed job listings and selects the ones that interest them.

[0774] Input: A list of jobs displayed on a user interface.

[0775] Output: The job posting selected by the user.

[0776] What happens: User clicks on a job posting that interests them to learn more.

[0777] Step 13:

[0778] Server: The server generates and sends alerts containing the user's profile information to companies based on the selected job information.

[0779] Input: The job posting selected by the user.

[0780] Output: The alert message to be sent to the company.

[0781] Specific operation: The server generates a notification alert message and sends it to the company.

[0782] Step 14:

[0783] Company: The company receives a notification from the server, verifies the profile information provided, and takes the next step, such as scheduling an interview with the candidate.

[0784] Input: The alert message sent by the server.

[0785] Output: Interview schedule set by the company.

[0786] What happens: A company HR representative reviews the user's profile information and schedules an interview.

[0787] (Application example 1)

[0788] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0789] It is not easy for consumers to find the best products based on their preferences and budget, and they are often overwhelmed by the amount of information available. It is also difficult for businesses to find the right product approach to meet the specific needs of consumers. To solve these problems, a system is needed that provides the best product information for consumers and efficiently conveys consumer information to businesses.

[0790] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0791] In this invention, the server includes means for a user to input desired information and conditions, means for receiving the input information and saving it in a database, means for presenting the user with questions about the relevant category and budget and receiving the answers, means for saving the received answers in a database, means for analyzing the user's information and answers and generating optimal product information, means for providing the generated product information to the user, and means for providing consumer information to businesses that present product information. This enables consumers to efficiently obtain product information that best suits their needs, and enables businesses to make product suggestions that meet their targets.

[0792] "Desired information" is information about the user's requests regarding specific products or services or characteristics that the user wishes to obtain.

[0793] "Desired conditions" are the factors and criteria that a user prioritizes when selecting a product or service, and include budget, category, functions, specifications, etc.

[0794] A "database" is a collection of information that systematically stores information entered by users and information collected and generated by systems, making it easily accessible.

[0795] A "machine learning algorithm" is a method for learning patterns and rules based on large amounts of data, and predicting and classifying future data.

[0796] The "matching degree" is an index showing the compatibility between the user's desired conditions and candidate information (product information, etc.) in the database, and the higher the degree, the more suitable the product is.

[0797] "Product information" refers to detailed information about each product stored in the database, and includes multiple elements such as category, price, features, and ratings.

[0798] "Consumer information" refers to desired information and conditions entered by the user, as well as information about the user's preferences and purchasing behavior obtained from data analyzed by the system.

[0799] A "business" is an organization or company that provides goods or services and markets or sells them to consumers.

[0800] An "answer" is a specific response that a user inputs to a question presented by the system, and is information about the user's preferences and conditions.

[0801] This invention relates to a system that allows users to input desired information and conditions and provides optimal product information. The system spans terminals such as smartphones, tablets, and personal computers, as well as databases including a central server, and utilizes generative AI models to improve the user experience.

[0802] Registration Phase

[0803] User

[0804] The user inputs their desired conditions and desired information into the application on the terminal, including their name, email address, desired product category (e.g., home appliances, furniture), and budget.

[0805] Terminal

[0806] The terminal has the ability to convert input information into XML or JSON format and send it to the server, using a scripting language such as Python or the Flask framework.

[0807] server

[0808] The server analyzes the received data and stores it in a database. It creates and properly manages the database using an RDBMS such as MySQL. Once processing is complete, it returns a confirmation response to the terminal.

[0809] Question Phase

[0810] server

[0811] The server presents the user with predefined questions, such as "What category of products do you like?" or "What is your budget?"

[0812] Terminal

[0813] The terminal displays the received question on the user interface and waits for the user's answer.

[0814] User

[0815] The user answers each question using the terminal. For example, the user answers "Home appliances" to the question "Which category of products do you like?"

[0816] Terminal

[0817] The device collects the user's answers, converts them into JSON format, and sends them to the server.

[0818] server

[0819] The server analyzes the received response and stores it in a database.

[0820] Matching Phase

[0821] server

[0822] The server runs a matching algorithm to compare the user's desired conditions and responses with product information in the database, thereby generating optimal product information.

[0823] server

[0824] A list including the selected product information is generated and transmitted to the terminal.

[0825] Terminal

[0826] The terminal displays the product information list on a user interface.

[0827] User

[0828] The user checks the displayed product information and selects a product that interests them.

[0829] Proposal Phase

[0830] server

[0831] The server generates an alert containing the user's profile information to a business that provides product information, for example, by email or dashboard notification.

[0832] business operator

[0833] The business receives the consumer information provided by the server and formulates appropriate marketing and sales strategies.

[0834] Specific examples

[0835] If a user enters the desired conditions "home appliances" and "under 50,000 yen," the system will filter the corresponding products in the database and generate an optimal product list. For example, the result will be "Product A - Home Appliances (45,000 yen)." The business will also receive an alert stating, "User X is looking for a product in the home appliance category. His budget is under 50,000 yen."

[0836] Prompt Sentence Examples

[0837] Prompt: Given a user has specified a desired category of "Home Appliances" and a budget of "50,000 yen", generate a list of products that are optimal for him. Select products in the database that are in the Home Appliances category and are priced at or below 50,000 yen, and output the results in JSON format.

[0838] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0839] Step 1:

[0840] The user enters their desired conditions and desired information (name, email address, desired product category, budget, etc.) through the application on their device. The entered information is sent from the device to the server. At this time, the input information is converted into JSON format.

[0841] Step 2:

[0842] The server receives the JSON-formatted data sent from the device and validates the information, for example, checking that all required fields are filled in and that the data follows a specific format. Once validated, the data is stored in a MySQL database.

[0843] Step 3:

[0844] The server sends predefined questions to the user (such as "Which category of products do you like?" or "What is your budget?") in JSON format to the terminal. The content of the questions is stored in a database.

[0845] Step 4:

[0846] The terminal receives the questions sent from the server and displays them on a user interface. HTML and JavaScript are used to generate the interface and wait for the user's response.

[0847] Step 5:

[0848] The user answers questions through the device interface. For example, to the question "What category of products do you like?", the user answers "Home appliances." Once the answer is entered, the device converts it back into JSON format and sends it to the server.

[0849] Step 6:

[0850] The server receives the user's answers sent from the terminal and analyzes them. This analysis includes data cleaning and format matching. Once the analysis is complete, the answers are stored in the database again.

[0851] Step 7:

[0852] The server runs a matching algorithm to search the database for matching product information based on the user's desired conditions and responses. For example, this algorithm filters products whose "desired product category" is "home appliances" and whose "budget" is 50,000 yen or less.

[0853] Step 8:

[0854] The server creates a list of the results of the matching algorithm (for example, "Product A - Home Appliance (45,000 yen)") and sends it to the terminal. This list is again in JSON format.

[0855] Step 9:

[0856] The terminal receives the product information list sent from the server and displays it on the user interface, allowing the user to check the list and select products that interest them.

[0857] Step 10:

[0858] The server generates an alert containing the user's profile information and sends it to the product information provider in the form of an email or dashboard notification. For example, "User X is looking for a product in the home appliance category with a budget of 50,000 yen or less."

[0859] Step 11:

[0860] Businesses receive the consumer information sent from the server and use it as basic data for formulating appropriate marketing and sales strategies.

[0861] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0862] This invention is a system that provides optimal job information to job seekers, and by combining it with an emotion engine, it achieves optimal job matching that takes into account the user's emotional state. Users input their work history and desired conditions into a terminal, and the server receives and analyzes this information to generate and provide optimal job information. Furthermore, by using the emotion engine to recognize the user's emotional state and utilizing this information, it is possible to achieve more accurate matching.

[0863] System configuration

[0864] This system includes a terminal used by the user, a server, a database, and an emotion engine. The user uses the terminal to access the system and input and receive information. The server receives the input information and stores and analyzes it in the database. The emotion engine recognizes emotions from the user's input information and responses, and provides the results to the server.

[0865] Explanation of program processing

[0866] Registration Phase

[0867] User: The user enters their work history information and desired conditions into the terminal, specifically, their name, address, past work history, skill set, and desired work environment.

[0868] Terminal: The terminal receives the input information and converts it into a specified format such as JSON.

[0869] Terminal: Sends the converted data to the server via an HTTP POST request.

[0870] Server: The server analyzes the received data, checks its validity, and then saves it in the database. It then sends a processing completion response to the terminal.

[0871] Question Phase

[0872] Server: The server sends a list of predefined questions to the user on the device, such as "Do you value teamwork?" or "Do you prefer to work for a company that allows remote work?"

[0873] Terminal: The terminal displays the question in a user interface.

[0874] User: The user enters an answer to each question, for example, "Do you value teamwork?"

[0875] Terminal: The terminal collects the responses, converts them into JSON format, and sends them to the server.

[0876] Server: The server analyzes the received response and stores it in a database.

[0877] Emotion Recognition Phase

[0878] Server: The server sends the user's input information and responses to the emotion engine.

[0879] Emotion Engine: The emotion engine analyzes the received inputs and responses to recognize the user's emotional state (e.g., stress, joy, anxiety).

[0880] Emotion engine: Sends the recognized emotional state to the server.

[0881] Server: The server stores the emotional state data in a database.

[0882] Matching Phase

[0883] Server: The server runs a matching algorithm based on the user's work history and emotional state, which calculates the degree of match between the job listings in the database and the user's information.

[0884] Server: Uses a matching algorithm to list the most suitable job information and generates JSON data to send to the terminal.

[0885] Terminal: The terminal displays the job listings on a user interface.

[0886] User: The user reviews the displayed job listings and selects the job listings that interest them.

[0887] Proposal Phase

[0888] Server: The server generates alerts to the enterprise that include the user's profile information and emotional state.

[0889] Server: Sends an alert to the company's HR department containing the profile information and emotional state of the selected candidate.

[0890] Corporate User: The corporate user reviews the received candidate information and emotional state and decides on interviews and next steps.

[0891] Specific examples

[0892] Example of the registration phase

[0893] User: Taro Yamada accesses the system and enters his name, address, past work experience (e.g., 5 years of Java development experience), skill set (e.g., Java, Python), and desired work environment (e.g., remote work acceptable).

[0894] Terminal: The terminal converts this information into JSON format and sends it to the server.

[0895] Server: After receiving the data and verifying its validity, the server stores it in a database and returns a processing completion response to the terminal.

[0896] Specific example of the question phase

[0897] Server: The server sends the question "Do you value teamwork?" to the device.

[0898] Terminal: The terminal presents the received question to the user.

[0899] User: Yamada answers "Yes" and sends the answer to the server via his terminal.

[0900] Server: The server receives the answer and stores it in a database.

[0901] A concrete example of the emotion recognition phase

[0902] Server: The server sends Yamada's information and response to the emotion engine.

[0903] Emotion Engine: The emotion engine analyzes Yamada's input and responses and recognizes his emotional state (e.g., joy).

[0904] Emotion engine: Sends the recognized emotional state to the server.

[0905] Server: The server stores the emotional states in a database.

[0906] A concrete example of the matching phase

[0907] Server: Based on Yamada's profile, responses, and emotional state, the server uses a matching algorithm to analyze the job listings in the database and select the most suitable job listing.

[0908] Server: Generates a list containing suitable job information (e.g., "Company B - Java Engineer (remote work available)") and sends it to the device.

[0909] Terminal: The terminal displays this list to Yamada.

[0910] User: Yamada checks the displayed job information and selects the information that interests him.

[0911] Specific example of the proposal phase

[0912] Server: The server generates and sends an alert to Company B containing Yamada's profile information and emotional state.

[0913] Corporate: Corporate HR personnel review the received profile information and emotional state and schedule an interview.

[0914] In this way, a system can be constructed that takes into account the user's emotional state and achieves more accurate job change matching.

[0915] The processing flow will be explained below.

[0916] Step 1:

[0917] Users enter their work history information and desired conditions into the terminal, specifically, their name, address, past work history, skill set (e.g., Java, Python), and desired work environment (e.g., remote work allowed).

[0918] Step 2:

[0919] The terminal receives the input information and converts it into a specified format such as JSON.

[0920] Step 3:

[0921] The terminal sends the converted data to the server via an HTTP POST request.

[0922] Step 4:

[0923] The server parses the received data and validates it, checking that all required fields are present, that the format is correct, etc.

[0924] Step 5:

[0925] The server saves the data that has been successfully validated in the database, and once the saving is complete, it sends the processing result to the terminal as a response.

[0926] Step 6:

[0927] The server sends a list of questions to the user in JSON format to present questions about their job duties and work environment to the terminal.

[0928] Step 7:

[0929] The terminal displays the received question list on the user interface.

[0930] Step 8:

[0931] The user inputs an answer to the displayed question, for example, "Do you value teamwork?", and answers "Yes."

[0932] Step 9:

[0933] The terminal collects the answers entered by the user, converts them back into JSON format, and sends them to the server.

[0934] Step 10:

[0935] The server analyzes the received response and stores it in a database.

[0936] Step 11:

[0937] The server sends the user's input information and responses to the emotion engine.

[0938] Step 12:

[0939] The emotion engine analyzes the received inputs and responses to recognize the user's emotional state (e.g., stress, joy, anxiety).

[0940] Step 13:

[0941] The emotion engine transmits the recognized emotional state to the server.

[0942] Step 14:

[0943] The server stores the emotional states in a database.

[0944] Step 15:

[0945] The server runs a matching algorithm based on the user's work history and emotional state, and calculates the degree of match between the job listings in the database and the user's information.

[0946] Step 16:

[0947] The server lists the most suitable job information and generates JSON data to send to the terminal.

[0948] Step 17:

[0949] The terminal displays the received job information list on the user interface.

[0950] Step 18:

[0951] The user checks the displayed job listings and selects the job listings that interest them.

[0952] Step 19:

[0953] The server generates alerts to businesses associated with selected job postings, providing information and sentiment of suitable candidates.

[0954] Step 20:

[0955] The server sends an alert to the company's HR department containing the profile information and emotional state of the selected candidate.

[0956] Step 21:

[0957] The company user reviews the received candidate information and emotional state and decides on interviews and next steps.

[0958] Example 2

[0959] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0960] Conventional job information systems only provide job information based on the user's work history and desired conditions, and do not perform job matching that takes into account the user's emotional state. As a result, it is difficult to provide job information that matches the user's actual desires and emotional state, and it has not been possible to achieve highly accurate matching.

[0961] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0962] In this invention, the server includes means for a user to input work history information and desired conditions, means for receiving the input information and saving it in a database, means for presenting questions to the user regarding job content and work environment and receiving answers, means for saving the received answers in a database, means for analyzing the user's information and answers and using an emotion engine that recognizes the user's emotional state, means for generating optimal job information based on the recognized emotional state and the user's information, means for providing the generated job information to the user, and means for providing candidate information to companies that submit job information. This enables highly accurate matching of job information that takes the user's emotional state into consideration.

[0963] "User" refers to an individual who accesses the system, inputs work history information and desired conditions, and is provided with the most suitable job information.

[0964] "Work history information" refers to information including a user's previous work experience, skill set, and related accomplishments.

[0965] "Desired conditions" refers to conditions including the user's desired work environment, working conditions, work location, salary, etc.

[0966] "Input means" refers to the interface or device that allows a user to provide their work history information and desired conditions to the system.

[0967] "Means for receiving and storing in a database" refers to the process by which the server receives the information sent by the user and stores it in a database.

[0968] The "means for presenting questions and receiving answers" refers to a method by which the server asks the user questions about the job content and work environment and receives the user's answers.

[0969] "Means for storing the received answers in a database" refers to the process by which the server receives answers from users and stores them in a database.

[0970] "Means for analyzing and using an emotion engine to recognize an emotional state" refers to a process in which the server analyzes the user's information and answers and uses an emotion engine to recognize the user's emotional state.

[0971] "Means for generating optimal job information based on the recognized emotional state and user information" refers to a process for generating optimal job information by combining the emotional state recognized by the emotion engine with the user's work history information and desired conditions.

[0972] The "means for providing the generated job information to the user" refers to a means for presenting the job information generated by the server to the user.

[0973] "Means for providing candidate information to companies that post job information" refers to the process by which the server provides information on selected candidates to companies.

[0974] An "emotion engine" refers to software or algorithms that recognize a user's emotional state from their input and responses.

[0975] "Machine learning algorithm" refers to a technology that learns patterns from data and performs analysis and predictions.

[0976] "Means for calculating the degree of matching" refers to the algorithm or process for comparing user information with job information, calculating the degree of matching, and making the best match.

[0977] This invention is a system that provides optimal job information to job seekers, and by combining it with an emotion engine, it realizes optimal job matching that takes into account the user's emotional state. Specifically, the user inputs their work history and desired conditions using a terminal, and the server receives and analyzes this to generate and provide optimal job information. Furthermore, the emotion engine is used to recognize the user's emotional state, and job information that reflects this is provided.

[0978] Hardware and Software Configuration

[0979] This system includes a device used by the user, a server that receives and analyzes data, a database that stores the data, and an emotion engine that recognizes emotions. The device can be a regular computer or smartphone, while a high-performance computer system is suitable for the server. The server has a database management system (DBMS) and emotion recognition software installed.

[0980] Overview of program processing

[0981] The server performs the following program processing.

[0982] 1. Receiving and storing user information

[0983] The user enters their work history and desired job requirements using a terminal. The terminal receives this information, converts it into JSON format, and sends it as an HTTP POST request to the server. The server analyzes the received information and stores it in a database.

[0984] 2. Posting Questions and Receiving Answers

[0985] The server sends predefined questions to the user's device. For example, questions like "Do you value teamwork?" or "Do you prefer a company that allows remote work?" The user answers these questions, and the device collects the user's answers, converts them into JSON format, and sends them to the server. The server parses the answers and stores them in a database.

[0986] 3. Recognizing emotional states

[0987] The server sends the user's input information and answers to the emotion engine. The emotion engine analyzes this information and recognizes the user's emotional state. For example, it detects positive emotions (joy) from the user's answers. The recognized emotional state is sent to the server, which stores it in a database.

[0988] 4. Job information matching and provision

[0989] The server runs a matching algorithm to match job listings in the database based on the user's work history, desired conditions, and recognized emotional state. It selects the most suitable job listing and sends the results to the terminal. The terminal then displays the most suitable job listing to the user.

[0990] 5. Providing information to companies

[0991] Once the user selects the job postings they are interested in, the server provides that information to the company, which then receives the candidate's profile information and emotional state and uses that information to carry out the next steps (such as setting up an interview).

[0992] Specific examples

[0993] For example, a job seeker named Taro Yamada accesses the system and enters his name, address, work history (e.g., 5 years of Java development experience), skill set (e.g., Java, Python), and desired conditions (e.g., willingness to work remotely). The terminal converts this information into JSON format and sends it to the server. The server receives the information and stores it in a database.

[0994] Next, the server asks Yamada, "Do you value teamwork?", and Yamada answers "Yes." The device converts this answer into JSON format and sends it to the server. The server receives the answer and stores it in a database.

[0995] The server then sends Yamada's information and answer to the emotion engine, which recognizes the positive emotion (joy). This emotional state is sent to the server and stored in a database.

[0996] Finally, the server matches Yamada's information and emotional state with job listings in the database and selects the most suitable one (e.g., "Company B - Java Engineer (remote work available)"). This information is sent to the device and displayed to Yamada. If Yamada shows interest, the server provides the information to the company, which then schedules an interview.

[0997] Prompt Sentence Examples

[0998] Please enter your work history information

[0999] Please tell us your preferred work environment

[1000] "Do you value teamwork?"

[1001] "Do you want a company that allows you to work remotely?"

[1002] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1003] Step 1: Enter your user information

[1004] User: A user accesses the system using a terminal and enters their work history information (e.g., name, address, work experience, skill set) and desired conditions (e.g., desired work environment). For example, Taro Yamada enters "5 years of Java development experience" and "preferred remote work."

[1005] Input: Name, address, work experience, skill set, desired work environment.

[1006] Output: JSON format data of user input information.

[1007] Terminal: The terminal receives this information in real time, converts it into a specified JSON format, checks the converted JSON data, and displays a button to proceed to the next step.

[1008] Step 2: Sending data

[1009] Terminal: The terminal sends the converted JSON data to the server as an HTTP POST request. Specifically, the following is an example request: "POST / register { "name": "Yamada Taro", "address": "Shinjuku-ku, Tokyo", "experience": "5 years of Java development experience", "skills": ["Java", "Python"], "preferences": "Remote work available"}"

[1010] Input: User information data in JSON format.

[1011] Output: A message confirming the completion of the transmission.

[1012] Server: The server receives the HTTP POST request and checks the validity of the data. After checking, it saves the information in the database and returns a processing completion response to the terminal. Example: "HTTP / 1.1 200 OK { "status": "success", "message": "User data saved successfully"}"

[1013] Step 3: Posting a question and receiving an answer

[1014] Server: The server sends predefined questions to the device. For example, "Do you value teamwork?" or "Do you want to work for a company that allows remote work?"

[1015] Input: A predefined question in text format.

[1016] Output: Question list data in JSON format.

[1017] Terminal: The terminal launches an interface to display the received list of questions to the user, for example, providing a "yes" or "no" option for each question.

[1018] User: The user answers each question. For example, "Do you value teamwork?" with "Yes."

[1019] Input: User's answer (in text format).

[1020] Output: JSON format data of user responses.

[1021] Terminal: The terminal collects the user's answers, converts them back into JSON format, and sends them to the server.

[1022] Step 4: Recognizing your emotional state

[1023] Server: The server sends the user's input information and responses to the emotion engine.

[1024] Input: JSON format data of user information and answers.

[1025] Output: JSON format data of the emotional state and its confidence.

[1026] Emotion Engine: The emotion engine analyzes the incoming data and recognizes the user's emotional state. Example: "Emotional state: joy, confidence: 0.85"

[1027] Server: Receives the emotional state sent from the emotion engine and stores it in a database.

[1028] Step 5: Job Matching

[1029] Server: The server uses a matching algorithm to analyze job listings in the database based on the user's work history, desired conditions, and perceived emotional state.

[1030] Input: JSON format data of user information, desired conditions, and emotional state.

[1031] Output: Matching results in JSON format.

[1032] Server: Runs a matching algorithm and selects the job listing that best suits the user. Example: "Company B - Java Engineer (Remote work available)"

[1033] Server: Generates a list of selected job information in JSON format and sends it to the terminal.

[1034] Step 6: View your job listings

[1035] Device: Display the received job information list on the user interface. Example: "Company B - Java Engineer (remote work available)"

[1036] Input: JSON format data for job listings.

[1037] Output: Job listing screen.

[1038] User: The user reviews the displayed job listings and selects the job listings that interest them.

[1039] Step 7: Provide information to companies

[1040] Terminal: Notifies the server of the job information selected by the user. Example: Sends JSON data including the ID of the selected job information.

[1041] Input: The ID of the selected job posting.

[1042] Output: A message confirming your selection.

[1043] Server: The server sends the user's profile information and emotional state to the company's HR system based on the selected job information. Example: "JSON data containing the candidate profile and emotional state."

[1044] Input: JSON format data of user profile information and emotional state.

[1045] Output: A message confirming notification to the company.

[1046] Company: Based on the received information, the company's human resources personnel will carry out the next process (e.g., scheduling an interview).

[1047] (Application example 2)

[1048] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1049] Conventional job information systems only consider the user's career history and desired conditions, and there are challenges in improving the accuracy of job matching by incorporating the user's emotional state. Furthermore, there is a lack of proposals for products and services that correspond to the emotional state of each individual user. Therefore, it is necessary to develop a system that provides optimal job information that takes into account the user's emotional state and proposes products and services that correspond to the user's emotional state.

[1050] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1051] In this invention, the server includes a means for a user to input work history information and desired conditions, a means for receiving the input information and storing it in a database, and a means for presenting questions to the user regarding the job content and work environment and receiving the answers, thereby making it possible to collect the user's work history information and desired conditions.

[1052] The system further includes a means for storing the received responses in a database, a means for analyzing the user's information and responses and generating optimal job information, a means for providing the generated job information to the user, and a means for providing candidate information to companies that submit job information. This makes it possible to provide optimal job information from the collected information to the user and to appropriately provide candidate information to companies.

[1053] The system also includes a means for analyzing the user's input information and responses using an emotion engine to recognize the user's emotional state, and a means for recommending optimal products and services in consideration of the user's emotional state. This makes it possible to provide highly accurate job information that incorporates the user's emotional state, and to suggest products and services according to the user's emotional state.

[1054] "Means for users to input their work history information and desired working conditions" refers to the interface that allows job seekers to input their work history and desired working conditions into the system.

[1055] "Means for receiving input information and storing it in a database" refers to the function by which the system receives information input by job seekers and stores that information in a database.

[1056] "Means of presenting questions about job content and work environment and receiving answers" refers to the function of presenting questions about the work environment and job content to job seekers and collecting their answers.

[1057] "Means for storing received responses in a database" refers to the function by which the system receives responses collected from job seekers and stores them in a database.

[1058] "Means for analyzing user information and responses and generating optimal job information" refers to algorithms and programs that analyze data based on the information and responses provided by job seekers and create job information that best matches them.

[1059] The "means for providing generated job information to a user" refers to an interface for displaying or notifying job seekers of the job information resulting from the analysis.

[1060] "Means of providing candidate information to companies posting job openings" refers to the function of providing information on job seekers' profiles and suitability to companies posting job openings.

[1061] An "emotion engine" refers to a system that analyzes a user's input information and responses to evaluate the user's emotional state.

[1062] "Means for recognizing the user's emotional state" refers to a function that uses an emotion engine to detect the user's current emotional state and reflects that information in the system.

[1063] "Means for recommending optimal products and services taking into account the user's emotional state" refers to algorithms or programs that suggest the most suitable products and services to a user based on the user's emotional state.

[1064] A "machine learning algorithm" is a type of computer program used to create predictive models in data analysis.

[1065] MODE FOR CARRYING OUT THE INVENTION

[1066] This invention is a system that provides optimal job information by analyzing the user's work history and desired conditions after inputting the information. It also uses an emotion engine to consider the user's emotional state, and can provide job information and recommend products and services based on the user's emotions.

[1067] Hardware and software used

[1068] Hardware: Smartphone camera, microphone

[1069] Software: OpenCV, EmotionRecognizer (proprietary emotion recognition engine), RecommendationEngine (proprietary recommendation engine)

[1070] System configuration

[1071] This system includes a terminal used by the user, a server, a database, and an emotion engine, and is realized using the following hardware and software:

[1072] Terminal

[1073] Users access the system using a device such as a smartphone and enter their work history and desired conditions. The device receives the entered information and sends it to the server via an HTTP POST request. An interface is also provided for users to enter their work history and desired conditions into the device.

[1074] server

[1075] The server analyzes the information received from the device and stores it in a database. The server also sends a list of predefined questions to the user to the device, receives the answers, and stores them in a database. Furthermore, the server uses an emotion engine to analyze and recognize the user's emotional state based on the user's input information and answers. The recognized emotional state data is stored in a database.

[1076] Emotion Engine

[1077] The emotion engine recognizes the user's emotional state (e.g., stress, joy, anxiety) based on the user's information and responses sent from the server. This makes it possible to provide optimal job information that takes the user's emotional state into consideration. In addition, the recommendation engine recommends products and services that are suitable for the user based on the emotional state recognized by the emotion engine.

[1078] Data processing and calculation

[1079] The server uses the Emotion Engine and Recommendation Engine to process and calculate data as follows:

[1080] 1. Emotion Recognition: We use OpenCV to capture video from a smartphone camera and EmotionRecognizer to analyze the user's emotional state. Specifically, we analyze facial expression data to recognize emotions such as stress, joy, and anxiety.

[1081] 2. Data analysis: Based on the user's work history, desired conditions, and responses, the system uses a recommendation algorithm to analyze and generate optimal job listings. It also suggests products and services based on the user's emotional state.

[1082] Specific examples

[1083] Example 1: Providing job information based on the user's emotional state

[1084] A user logs into the system and enters their work history information (e.g., 5 years of Java development experience) and desired work environment (e.g., remote work acceptable). After answering corresponding questions (e.g., "Do you value teamwork?"), emotion recognition is performed using the smartphone camera. Through this process, the emotional state of "joy" is recognized. Based on this information, the server provides the user with job information that is most suitable for them.

[1085] Example 2: Product suggestions based on emotional state

[1086] Based on user input and emotion recognition data from the camera (e.g., high stress), the recommendation engine suggests relaxing products (e.g., a tea set with a relaxing effect).

[1087] Example prompts for generative AI models

[1088] "Design an application that analyzes a user's emotional state based on facial expression data, and recommends products that have a relaxing effect if the user's stress level is recognized as high."

[1089] As described above, we provide a highly accurate job information providing system that incorporates the user's emotional state, and a mechanism for recommending products and services based on the user's emotional state.

[1090] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1091] Step 1:

[1092] The user inputs work history information and desired conditions.

[1093] Input: User's work history (e.g., 5 years of Java development experience) and desired conditions (e.g., remote work acceptable)

[1094] How it works: Input is made through the smartphone interface, and the device receives the information, converts it into JSON format, and sends it to the server.

[1095] Output: User's work history and desired conditions sent to the server

[1096] Step 2:

[1097] The server receives the entered information and stores it in a database.

[1098] Input: User's work history and desired conditions sent from the device (JSON format)

[1099] How it works: The server parses the information, validates the data, and then stores it in a database.

[1100] Output: User information stored in the database

[1101] Step 3:

[1102] The server presents the user with questions about their job duties and work environment and receives their answers.

[1103] Input: User's work history and desired conditions stored in the database

[1104] How it works: The server generates a list of predefined questions and sends them to the terminal via HTTP requests. The user enters answers to the questions, and the terminal receives the answers and sends them to the server.

[1105] Output: User's answer sent to the server

[1106] Step 4:

[1107] The server stores the received response in a database.

[1108] Input: User's answer (e.g., "Do you value teamwork?": "Yes")

[1109] How it works: The server stores the received answers in a database and prepares them for analysis.

[1110] Output: User answers stored in the database

[1111] Step 5:

[1112] The server sends the user's input information and responses to the emotion engine.

[1113] Input: User information and answers stored in a database

[1114] How it works: The server sends the user's information and responses to the emotion engine, which analyzes it and recognizes the user's emotional state.

[1115] Output: The user's emotional state as recognized by the emotion engine (e.g., stress, joy, anxiety)

[1116] Step 6:

[1117] The server stores the emotional state data in a database.

[1118] Input: The user's emotional state sent from the emotion engine

[1119] How it works: The server stores the recognized emotional state in a database.

[1120] Output: User's emotional state stored in a database

[1121] Step 7:

[1122] The server runs a matching algorithm based on the user's work history, responses, and emotional state to generate job information.

[1123] Input: User's work history information, responses, and emotional state stored in a database

[1124] How it works: The server runs a matching algorithm to calculate the degree of match with jobs in the database.

[1125] Output: The best job listings generated

[1126] Step 8:

[1127] The server provides the generated job information to the user.

[1128] Input: Generated best-fit job listings

[1129] Operation: The server converts the job information into JSON format and sends it to the terminal as an HTTP response, which displays it on the user interface.

[1130] Output: Job listing displayed on terminal

[1131] Step 9:

[1132] Taking into account the user's emotional state, the server recommends the most suitable products and services.

[1133] Input: User's emotional state, purchase history, and category information of interest

[1134] How it works: The Recommendation Engine analyzes the user's emotional state and recommends the most suitable products and services. The server sends the results to the device, which displays them on the user interface.

[1135] Output: Recommendations for products and services displayed on the device

[1136] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1137] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1138] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1139] [Third embodiment]

[1140] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1141] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1142] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1143] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1144] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1145] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1146] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1147] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1148] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1149] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1150] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1151] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1152] This invention relates to a system that provides optimal job information to job seekers. Users input their work history and desired conditions, and a server receives and analyzes them to generate and provide optimal job information.

[1153] System configuration

[1154] This system includes a terminal used by the user, a database, and a server. Users use their terminal to access the system and input and receive information. The server receives the information and stores and analyzes it in the database.

[1155] Explanation of program processing

[1156] Registration Phase

[1157] User: The user enters their work history information and desired conditions into the terminal, including name, address, past work experience, skill set (e.g., Java, Python), and desired work environment (e.g., remote work acceptable).

[1158] Terminal: The terminal receives the input information, converts it into a specific data format (such as JSON), and sends it to the server.

[1159] Server: The server analyzes the received data and stores it in a database. Once the data is stored, it sends a confirmation response to the device.

[1160] Question Phase

[1161] Server: The server presents the user with predefined questions, such as "Do you value teamwork?" or "Do you prefer a company that allows remote work?"

[1162] Terminal: The terminal displays these questions in a user interface and waits for user input.

[1163] User: The user answers each question using a terminal. For example, the user answers "Yes" to the question "Do you value teamwork?"

[1164] Terminal: The terminal collects the user's answers, converts them into the specified data format, and sends them to the server.

[1165] Server: The server analyzes the received response and stores it in a database.

[1166] Matching Phase

[1167] Server: The server runs a matching algorithm based on the user's work history and answers, which allows the server to compare the user's information with job listings in its database and select the most suitable job listing.

[1168] Server: Generates a list containing selected job information and sends it to the terminal.

[1169] Terminal: The terminal displays the job listings on a user interface.

[1170] User: The user reviews the displayed job information and selects the job that interests them.

[1171] Proposal Phase

[1172] Server: The server generates an alert to the company providing the user's profile information, such as "Candidate A has been added to your job seeker list. His skill set and desired conditions match your job posting."

[1173] Company: The company receives the candidate information provided by the server and schedules interviews and next steps.

[1174] Specific examples

[1175] Example of the registration phase

[1176] User: Taro Yamada accesses the system and enters his name, address, past work experience (e.g., 5 years of Java development experience), skill set (e.g., Java, Python), and desired work environment (e.g., remote work acceptable).

[1177] Terminal: The terminal converts this information into JSON format and sends it to the server.

[1178] Server: After receiving the data and verifying its validity, the server stores it in a database and returns a processing completion response to the terminal.

[1179] Specific example of the question phase

[1180] Server: The server sends the question "Do you value teamwork?" in JSON format to the terminal.

[1181] Terminal: The terminal presents the received question to the user.

[1182] User: Yamada answers "Yes" and sends the answer to the server via his terminal.

[1183] Server: The server receives the answer and stores it in a database.

[1184] A concrete example of the matching phase

[1185] Server: Based on Yamada's profile and answers, the server uses a matching algorithm to analyze the job listings in the database and select the most suitable job listing.

[1186] Server: Generates a list containing suitable job information (e.g., "Company B - Java Engineer (remote work available)") and sends it to the device.

[1187] Terminal: The terminal displays this list to Yamada.

[1188] User: Yamada checks the displayed job information and selects the information that interests him.

[1189] Specific example of the proposal phase

[1190] Server: The server generates and sends an alert to Company B containing Taro Yamada's profile information.

[1191] Company: The company's HR will review the profile information received and schedule an interview.

[1192] In this way, a system can be constructed that realizes efficient and highly accurate job-change matching for both users and companies.

[1193] The processing flow will be explained below.

[1194] Step 1:

[1195] Users enter their work history information and desired conditions into a terminal, specifically, their name, address, past work history, skill set, and desired work environment.

[1196] Step 2:

[1197] The terminal receives the input information and converts it into a specified format such as JSON.

[1198] Step 3:

[1199] The terminal sends the converted data to the server via an HTTP POST request.

[1200] Step 4:

[1201] The server parses the received data and validates it, checking that all required fields are present, that the format is correct, etc.

[1202] Step 5:

[1203] The server saves the data that has been successfully validated in the database, and once the saving is complete, it sends the processing result to the terminal as a response.

[1204] Step 6:

[1205] The server sends a list of questions to the user in JSON format to present questions about their job duties and work environment to the terminal.

[1206] Step 7:

[1207] The terminal displays the received question list on the user interface.

[1208] Step 8:

[1209] The user inputs an answer to the displayed question, for example, "Do you value teamwork?", and answers "Yes."

[1210] Step 9:

[1211] The terminal collects the answers entered by the user, converts them back into JSON format, and sends them to the server.

[1212] Step 10:

[1213] The server analyzes the received responses and stores them in a database, adding them to the user's profile.

[1214] Step 11:

[1215] The server runs a matching algorithm based on the user's work history and responses, calculating the degree of match between the job listings in the database and the user's information.

[1216] Step 12:

[1217] The server lists the most suitable job information and generates JSON data to send to the terminal.

[1218] Step 13:

[1219] The terminal displays the received job information list on the user interface.

[1220] Step 14:

[1221] The user checks the displayed job listings and selects the job listings that interest them.

[1222] Step 15:

[1223] The server generates alerts to businesses associated with the selected job postings, providing information about suitable candidates.

[1224] Step 16:

[1225] The server sends an alert to the company's HR department containing the profile information of the selected candidate.

[1226] Step 17:

[1227] The corporate user reviews the received candidate information and decides on interviews and next steps.

[1228] Example 1

[1229] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1230] Conventional job information systems simply accept the work history information and desired conditions entered by users, and the accuracy of providing job information based on that information is low, making it difficult to provide appropriate job information that meets the user's needs.In addition, the analysis of user information and optimization of job information are limited, and detailed candidate information cannot be provided to companies, resulting in low efficiency in matching companies and users.

[1231] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1232] In this invention, the server includes means for receiving information entered by a user, converting it into a specific data format, and saving it in a database, means for presenting the user with questions about job content and work environment and receiving answers, means for saving the received answers in a database, means for analyzing the user's information and the received answers and using a matching algorithm to generate optimal job information, means for providing the generated optimal job information to the user, and means for providing user profile information to companies that submit job information. This makes it possible to provide highly accurate job information based on the user's detailed needs, and improves the efficiency of matching companies and users.

[1233] A "user" is an individual who uses this system to input work history information and desired conditions in order to obtain the most suitable job information.

[1234] "Work history information" refers to information such as the jobs, positions, and skill sets that a user has had up to now.

[1235] "Desired conditions" are the user's desired work environment, working conditions, work location, and other requirements.

[1236] "Input means" refers to an interface that allows a user to input information into the system, and is primarily operated via a terminal.

[1237] "Data format" refers to a format in which information is expressed as structured data in a certain format, such as JSON format.

[1238] A "database" is a digital storage system that can efficiently store, manage, and search structured data.

[1239] The "means for presenting questions" refers to an interface through which the server displays questions about the job content and work environment to the user.

[1240] The "means for receiving an answer" refers to an interface that allows the system to receive and analyze answers to questions returned by users.

[1241] A "matching algorithm" is a calculation method for selecting the most suitable job information based on the user's work history, desired conditions, and responses.

[1242] "Job information" refers to detailed information provided by companies about job types, positions, and related conditions.

[1243] "Profile information" is information that compiles the user's work history, skill set, desired conditions, and the like.

[1244] A "secure protocol" is a communication protocol for securely transmitting information, and includes, for example, HTTPS.

[1245] This invention relates to a system that provides optimal job information to job seekers. A user inputs their work history and desired conditions, and a server receives and analyzes the information to generate and provide optimal job information. The system includes a terminal used by the user, a database, and a server. Detailed modes for implementing the invention are described below.

[1246] System configuration

[1247] User: A user accesses the system using a terminal and enters their work history and preferences, such as their name, address, past work experience, skill set, and desired work environment.

[1248] Terminal: The terminal receives the information entered by the user and converts it into a specific data format (e.g., JSON format), which is then sent to the server via a secure protocol (e.g., HTTPS).

[1249] Server: The server analyzes the received data and stores it in a database. It presents the user with questions about the job content and work environment, and also receives and stores the answers to the questions in a database. The server analyzes the user's work history and desired conditions and generates optimal job information using a generative AI model.

[1250] Specific examples

[1251] Example of the registration phase

[1252] User: A job seeker accesses the system and enters their name, address, past work experience (e.g., 5 years of Java development experience), skill set (e.g., Java, Python), and desired work environment (e.g., remote work acceptable).

[1253] Terminal: The terminal converts this information into JSON format and sends it to the server.

[1254] Server: The server receives the data, verifies its validity, and then saves it in the database. Once the saving is complete, it returns a processing completion response to the terminal.

[1255] Specific example of the question phase

[1256] Server: The server generates the question "Do you value teamwork?" through a generative AI model and sends it to the device in JSON format.

[1257] Terminal: The terminal presents the received question to the user.

[1258] User: The user answers "yes" and sends the answer to the server via the terminal.

[1259] Server: The server receives the response and stores it in a database.

[1260] A concrete example of the matching phase

[1261] Server: Based on the user's work history information and answers to questions, the server uses a generative AI model to analyze the job listings in the database and generate the most suitable job listings.

[1262] Server: Generates a list containing suitable job information (e.g., "Company - Java Engineer (Remote Work Available)") and sends it to the device.

[1263] Terminal: The terminal displays this list to the user.

[1264] User: The user reviews the displayed job listings and selects the ones that interest them.

[1265] Specific example of the proposal phase

[1266] Server: The server generates and sends an alert to the company containing the user's profile information, stating, "The candidate has been added to your job seeker list. His skill set and preferences match your job opening."

[1267] Company: The company's HR will review the profile information received and schedule an interview.

[1268] Prompt Sentence Examples

[1269] "Please analyze the work history information and desired conditions entered by the user and generate the most suitable job information."

[1270] "Present users with a question about whether they value teamwork."

[1271] Based on the above steps, efficient and highly accurate job-change matching can be achieved for both users and companies.

[1272] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1273] Step 1:

[1274] User: The user enters their work history information and desired conditions into the terminal, specifically, their name, address, past work history (e.g., 5 years of Java development experience), skill set (e.g., Java, Python), and desired work environment (e.g., remote work acceptable).

[1275] Input: User enters work history information and desired qualifications.

[1276] Output: Information typed into the terminal.

[1277] Specific operation: The user enters the required information into the input form and clicks the submit button.

[1278] Step 2:

[1279] Terminal: The terminal receives the input information, converts it into JSON format data, and then sends this data to the server using a secure protocol (e.g., HTTPS).

[1280] Input: The work history information and desired conditions entered by the user into the terminal.

[1281] Output: JSON formatted data sent to the server.

[1282] Specific operation: The device internally converts the information into JSON format and sends the data to the server using HTTPS.

[1283] Step 3:

[1284] Server: The server analyzes the received data and saves it in the database. It verifies the validity of the data and returns an error message to the terminal if the data is invalid. If the data is normal, it saves it and then sends a response indicating that processing is complete.

[1285] Input: JSON format data sent from the terminal.

[1286] Output: User information saved in the database and a response indicating completion of the process.

[1287] Specific operation: The server verifies the validity of the data, and if it is normal, saves it in the database and sends a response to the terminal indicating that processing is complete.

[1288] Step 4:

[1289] Server: The server generates predefined questions for the user through a generative AI model and sends them to the terminal in JSON format.

[1290] Input: A prompt for the generative AI model.

[1291] Output: The JSON data of the question sent to the terminal.

[1292] Specific operation: The server generates a question using the generative AI model and sends it to the device.

[1293] Step 5:

[1294] Terminal: The terminal displays the received question on the user interface (UI). While waiting for the user's answer, it displays an answer input screen to the user.

[1295] Input: JSON data of the question sent by the server.

[1296] Output: The question displayed on the user interface.

[1297] Specific operation: The device analyzes the question data received and displays the question on the UI.

[1298] Step 6:

[1299] User: The user answers questions displayed on the device. For example, the user answers "Yes" to the question "Do you value teamwork?"

[1300] Input: The question displayed from the terminal.

[1301] Output: The answer typed into the terminal.

[1302] Specific behavior: The user enters an answer and clicks the submit button.

[1303] Step 7:

[1304] Terminal: The terminal collects the user's answers, converts them back into JSON format, and sends them to the server.

[1305] Input: The answer entered by the user.

[1306] Output: The JSON formatted response data sent to the server.

[1307] Specific operation: The device converts the response data into JSON format and sends it to the server using HTTPS.

[1308] Step 8:

[1309] Server: The server receives the response data, analyzes it, and stores it in a database.

[1310] Input: JSON formatted response data sent from the device.

[1311] Output: Response data stored in a database.

[1312] Specific operation: The server analyzes the received response data and stores it in the database.

[1313] Step 9:

[1314] Server: The server runs a matching algorithm based on the user's work history and answers to generate the most suitable job listings. The generated job listings are then listed in JSON format.

[1315] Input: User information and response data stored in a database.

[1316] Output: A list of the best job listings.

[1317] Specific operation: Launch the matching algorithm, search the database and select suitable job postings.

[1318] Step 10:

[1319] Server: Sends the generated job information list to the terminal.

[1320] Input: A list of the best job postings.

[1321] Output: A list of job postings sent to your device.

[1322] Specific operation: The server generates a job listing in JSON format and sends it to the terminal.

[1323] Step 11:

[1324] Terminal: The terminal displays the job listings on the user interface and waits for user interaction.

[1325] Input: A list of job postings sent by the server.

[1326] Output: A list of jobs displayed in a user interface.

[1327] Specific operation: The device parses the job listings and displays the list on the UI.

[1328] Step 12:

[1329] User: The user reviews the displayed job listings and selects the ones that interest them.

[1330] Input: A list of jobs displayed on a user interface.

[1331] Output: The job posting selected by the user.

[1332] What happens: User clicks on a job posting that interests them to learn more.

[1333] Step 13:

[1334] Server: The server generates and sends alerts containing the user's profile information to companies based on the selected job information.

[1335] Input: The job posting selected by the user.

[1336] Output: The alert message to be sent to the company.

[1337] Specific operation: The server generates a notification alert message and sends it to the company.

[1338] Step 14:

[1339] Company: The company receives a notification from the server, verifies the profile information provided, and takes the next step, such as scheduling an interview with the candidate.

[1340] Input: The alert message sent by the server.

[1341] Output: Interview schedule set by the company.

[1342] What happens: A company HR representative reviews the user's profile information and schedules an interview.

[1343] (Application example 1)

[1344] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1345] It is not easy for consumers to find the best products based on their preferences and budget, and they are often overwhelmed by the amount of information available. It is also difficult for businesses to find the right product approach to meet the specific needs of consumers. To solve these problems, a system is needed that provides the best product information for consumers and efficiently conveys consumer information to businesses.

[1346] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1347] In this invention, the server includes means for a user to input desired information and conditions, means for receiving the input information and saving it in a database, means for presenting the user with questions about the relevant category and budget and receiving the answers, means for saving the received answers in a database, means for analyzing the user's information and answers and generating optimal product information, means for providing the generated product information to the user, and means for providing consumer information to businesses that present product information. This enables consumers to efficiently obtain product information that best suits their needs, and enables businesses to make product suggestions that meet their targets.

[1348] "Desired information" is information about the user's requests regarding specific products or services or characteristics that the user wishes to obtain.

[1349] "Desired conditions" are the factors and criteria that a user prioritizes when selecting a product or service, and include budget, category, functions, specifications, etc.

[1350] A "database" is a collection of information that systematically stores information entered by users and information collected and generated by systems, making it easily accessible.

[1351] A "machine learning algorithm" is a method for learning patterns and rules based on large amounts of data, and predicting and classifying future data.

[1352] The "matching degree" is an index showing the compatibility between the user's desired conditions and candidate information (product information, etc.) in the database, and the higher the degree, the more suitable the product is.

[1353] "Product information" refers to detailed information about each product stored in the database, and includes multiple elements such as category, price, features, and ratings.

[1354] "Consumer information" refers to desired information and conditions entered by the user, as well as information about the user's preferences and purchasing behavior obtained from data analyzed by the system.

[1355] A "business" is an organization or company that provides goods or services and markets or sells them to consumers.

[1356] An "answer" is a specific response that a user inputs to a question presented by the system, and is information about the user's preferences and conditions.

[1357] This invention relates to a system that allows users to input desired information and conditions and provides optimal product information. The system spans terminals such as smartphones, tablets, and personal computers, as well as databases including a central server, and utilizes generative AI models to improve the user experience.

[1358] Registration Phase

[1359] User

[1360] The user inputs their desired conditions and desired information into the application on the terminal, including their name, email address, desired product category (e.g., home appliances, furniture), and budget.

[1361] Terminal

[1362] The terminal has the ability to convert input information into XML or JSON format and send it to the server, using a scripting language such as Python or the Flask framework.

[1363] server

[1364] The server analyzes the received data and stores it in a database. It creates and properly manages the database using an RDBMS such as MySQL. Once processing is complete, it returns a confirmation response to the terminal.

[1365] Question Phase

[1366] server

[1367] The server presents the user with predefined questions, such as "What category of products do you like?" or "What is your budget?"

[1368] Terminal

[1369] The terminal displays the received question on the user interface and waits for the user's answer.

[1370] User

[1371] The user answers each question using the terminal. For example, the user answers "Home appliances" to the question "Which category of products do you like?"

[1372] Terminal

[1373] The device collects the user's answers, converts them into JSON format, and sends them to the server.

[1374] server

[1375] The server analyzes the received response and stores it in a database.

[1376] Matching Phase

[1377] server

[1378] The server runs a matching algorithm to compare the user's desired conditions and responses with product information in the database, thereby generating optimal product information.

[1379] server

[1380] A list including the selected product information is generated and transmitted to the terminal.

[1381] Terminal

[1382] The terminal displays the product information list on a user interface.

[1383] User

[1384] The user checks the displayed product information and selects a product that interests them.

[1385] Proposal Phase

[1386] server

[1387] The server generates an alert containing the user's profile information to a business that provides product information, for example, by email or dashboard notification.

[1388] business operator

[1389] The business receives the consumer information provided by the server and formulates appropriate marketing and sales strategies.

[1390] Specific examples

[1391] If a user enters the desired conditions "home appliances" and "under 50,000 yen," the system will filter the corresponding products in the database and generate an optimal product list. For example, the result will be "Product A - Home Appliances (45,000 yen)." The business will also receive an alert stating, "User X is looking for a product in the home appliance category. His budget is under 50,000 yen."

[1392] Prompt Sentence Examples

[1393] Prompt: Given a user has specified a desired category of "Home Appliances" and a budget of "50,000 yen", generate a list of products that are optimal for him. Select products in the database that are in the Home Appliances category and are priced at or below 50,000 yen, and output the results in JSON format.

[1394] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1395] Step 1:

[1396] The user enters their desired conditions and desired information (name, email address, desired product category, budget, etc.) through the application on their device. The entered information is sent from the device to the server. At this time, the input information is converted into JSON format.

[1397] Step 2:

[1398] The server receives the JSON-formatted data sent from the device and validates the information, for example, checking that all required fields are filled in and that the data follows a specific format. Once validated, the data is stored in a MySQL database.

[1399] Step 3:

[1400] The server sends predefined questions to the user (such as "Which category of products do you like?" or "What is your budget?") in JSON format to the terminal. The content of the questions is stored in a database.

[1401] Step 4:

[1402] The terminal receives the questions sent from the server and displays them on a user interface. HTML and JavaScript are used to generate the interface and wait for the user's response.

[1403] Step 5:

[1404] The user answers questions through the device interface. For example, to the question "What category of products do you like?", the user answers "Home appliances." Once the answer is entered, the device converts it back into JSON format and sends it to the server.

[1405] Step 6:

[1406] The server receives the user's answers sent from the terminal and analyzes them. This analysis includes data cleaning and format matching. Once the analysis is complete, the answers are stored in the database again.

[1407] Step 7:

[1408] The server runs a matching algorithm to search the database for matching product information based on the user's desired conditions and responses. For example, this algorithm filters products whose "desired product category" is "home appliances" and whose "budget" is 50,000 yen or less.

[1409] Step 8:

[1410] The server creates a list of the results of the matching algorithm (for example, "Product A - Home Appliance (45,000 yen)") and sends it to the terminal. This list is again in JSON format.

[1411] Step 9:

[1412] The terminal receives the product information list sent from the server and displays it on the user interface, allowing the user to check the list and select products that interest them.

[1413] Step 10:

[1414] The server generates an alert containing the user's profile information and sends it to the product information provider in the form of an email or dashboard notification. For example, "User X is looking for a product in the home appliance category with a budget of 50,000 yen or less."

[1415] Step 11:

[1416] Businesses receive the consumer information sent from the server and use it as basic data for formulating appropriate marketing and sales strategies.

[1417] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1418] This invention is a system that provides optimal job information to job seekers, and by combining it with an emotion engine, it achieves optimal job matching that takes into account the user's emotional state. Users input their work history and desired conditions into a terminal, and the server receives and analyzes this information to generate and provide optimal job information. Furthermore, by using the emotion engine to recognize the user's emotional state and utilizing this information, it is possible to achieve more accurate matching.

[1419] System configuration

[1420] This system includes a terminal used by the user, a server, a database, and an emotion engine. The user uses the terminal to access the system and input and receive information. The server receives the input information and stores and analyzes it in the database. The emotion engine recognizes emotions from the user's input information and responses, and provides the results to the server.

[1421] Explanation of program processing

[1422] Registration Phase

[1423] User: The user enters their work history information and desired conditions into the terminal, specifically, their name, address, past work history, skill set, and desired work environment.

[1424] Terminal: The terminal receives the input information and converts it into a specified format such as JSON.

[1425] Terminal: Sends the converted data to the server via an HTTP POST request.

[1426] Server: The server analyzes the received data, checks its validity, and then saves it in the database. It then sends a processing completion response to the terminal.

[1427] Question Phase

[1428] Server: The server sends a list of predefined questions to the user on the device, such as "Do you value teamwork?" or "Do you prefer to work for a company that allows remote work?"

[1429] Terminal: The terminal displays the question in a user interface.

[1430] User: The user enters an answer to each question, for example, "Do you value teamwork?"

[1431] Terminal: The terminal collects the responses, converts them into JSON format, and sends them to the server.

[1432] Server: The server analyzes the received response and stores it in a database.

[1433] Emotion Recognition Phase

[1434] Server: The server sends the user's input information and responses to the emotion engine.

[1435] Emotion Engine: The emotion engine analyzes the received inputs and responses to recognize the user's emotional state (e.g., stress, joy, anxiety).

[1436] Emotion engine: Sends the recognized emotional state to the server.

[1437] Server: The server stores the emotional state data in a database.

[1438] Matching Phase

[1439] Server: The server runs a matching algorithm based on the user's work history and emotional state, which calculates the degree of match between the job listings in the database and the user's information.

[1440] Server: Uses a matching algorithm to list the most suitable job information and generates JSON data to send to the terminal.

[1441] Terminal: The terminal displays the job listings on a user interface.

[1442] User: The user reviews the displayed job listings and selects the job listings that interest them.

[1443] Proposal Phase

[1444] Server: The server generates alerts to the enterprise that include the user's profile information and emotional state.

[1445] Server: Sends an alert to the company's HR department containing the profile information and emotional state of the selected candidate.

[1446] Corporate User: The corporate user reviews the received candidate information and emotional state and decides on interviews and next steps.

[1447] Specific examples

[1448] Example of the registration phase

[1449] User: Taro Yamada accesses the system and enters his name, address, past work experience (e.g., 5 years of Java development experience), skill set (e.g., Java, Python), and desired work environment (e.g., remote work acceptable).

[1450] Terminal: The terminal converts this information into JSON format and sends it to the server.

[1451] Server: After receiving the data and verifying its validity, the server stores it in a database and returns a processing completion response to the terminal.

[1452] Specific example of the question phase

[1453] Server: The server sends the question "Do you value teamwork?" to the device.

[1454] Terminal: The terminal presents the received question to the user.

[1455] User: Yamada answers "Yes" and sends the answer to the server via his terminal.

[1456] Server: The server receives the answer and stores it in a database.

[1457] A concrete example of the emotion recognition phase

[1458] Server: The server sends Yamada's information and response to the emotion engine.

[1459] Emotion Engine: The emotion engine analyzes Yamada's input and responses and recognizes his emotional state (e.g., joy).

[1460] Emotion engine: Sends the recognized emotional state to the server.

[1461] Server: The server stores the emotional states in a database.

[1462] A concrete example of the matching phase

[1463] Server: Based on Yamada's profile, responses, and emotional state, the server uses a matching algorithm to analyze the job listings in the database and select the most suitable job listing.

[1464] Server: Generates a list containing suitable job information (e.g., "Company B - Java Engineer (remote work available)") and sends it to the device.

[1465] Terminal: The terminal displays this list to Yamada.

[1466] User: Yamada checks the displayed job information and selects the information that interests him.

[1467] Specific example of the proposal phase

[1468] Server: The server generates and sends an alert to Company B containing Yamada's profile information and emotional state.

[1469] Corporate: Corporate HR personnel review the received profile information and emotional state and schedule an interview.

[1470] In this way, a system can be constructed that takes into account the user's emotional state and achieves more accurate job change matching.

[1471] The processing flow will be explained below.

[1472] Step 1:

[1473] Users enter their work history information and desired conditions into the terminal, specifically, their name, address, past work history, skill set (e.g., Java, Python), and desired work environment (e.g., remote work allowed).

[1474] Step 2:

[1475] The terminal receives the input information and converts it into a specified format such as JSON.

[1476] Step 3:

[1477] The terminal sends the converted data to the server via an HTTP POST request.

[1478] Step 4:

[1479] The server parses the received data and validates it, checking that all required fields are present, that the format is correct, etc.

[1480] Step 5:

[1481] The server saves the data that has been successfully validated in the database, and once the saving is complete, it sends the processing result to the terminal as a response.

[1482] Step 6:

[1483] The server sends a list of questions to the user in JSON format to present questions about their job duties and work environment to the terminal.

[1484] Step 7:

[1485] The terminal displays the received question list on the user interface.

[1486] Step 8:

[1487] The user inputs an answer to the displayed question, for example, "Do you value teamwork?", and answers "Yes."

[1488] Step 9:

[1489] The terminal collects the answers entered by the user, converts them back into JSON format, and sends them to the server.

[1490] Step 10:

[1491] The server analyzes the received response and stores it in a database.

[1492] Step 11:

[1493] The server sends the user's input information and responses to the emotion engine.

[1494] Step 12:

[1495] The emotion engine analyzes the received inputs and responses to recognize the user's emotional state (e.g., stress, joy, anxiety).

[1496] Step 13:

[1497] The emotion engine transmits the recognized emotional state to the server.

[1498] Step 14:

[1499] The server stores the emotional states in a database.

[1500] Step 15:

[1501] The server runs a matching algorithm based on the user's work history and emotional state, and calculates the degree of match between the job listings in the database and the user's information.

[1502] Step 16:

[1503] The server lists the most suitable job information and generates JSON data to send to the terminal.

[1504] Step 17:

[1505] The terminal displays the received job information list on the user interface.

[1506] Step 18:

[1507] The user checks the displayed job listings and selects the job listings that interest them.

[1508] Step 19:

[1509] The server generates alerts to businesses associated with selected job postings, providing information and sentiment of suitable candidates.

[1510] Step 20:

[1511] The server sends an alert to the company's HR department containing the profile information and emotional state of the selected candidate.

[1512] Step 21:

[1513] The company user reviews the received candidate information and emotional state and decides on interviews and next steps.

[1514] Example 2

[1515] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1516] Conventional job information systems only provide job information based on the user's work history and desired conditions, and do not perform job matching that takes into account the user's emotional state. As a result, it is difficult to provide job information that matches the user's actual desires and emotional state, and it has not been possible to achieve highly accurate matching.

[1517] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1518] In this invention, the server includes means for a user to input work history information and desired conditions, means for receiving the input information and saving it in a database, means for presenting questions to the user regarding job content and work environment and receiving answers, means for saving the received answers in a database, means for analyzing the user's information and answers and using an emotion engine that recognizes the user's emotional state, means for generating optimal job information based on the recognized emotional state and the user's information, means for providing the generated job information to the user, and means for providing candidate information to companies that submit job information. This enables highly accurate matching of job information that takes the user's emotional state into consideration.

[1519] "User" refers to an individual who accesses the system, inputs work history information and desired conditions, and is provided with the most suitable job information.

[1520] "Work history information" refers to information including a user's previous work experience, skill set, and related accomplishments.

[1521] "Desired conditions" refers to conditions including the user's desired work environment, working conditions, work location, salary, etc.

[1522] "Input means" refers to the interface or device that allows a user to provide their work history information and desired conditions to the system.

[1523] "Means for receiving and storing in a database" refers to the process by which the server receives the information sent by the user and stores it in a database.

[1524] The "means for presenting questions and receiving answers" refers to a method by which the server asks the user questions about the job content and work environment and receives the user's answers.

[1525] "Means for storing the received answers in a database" refers to the process by which the server receives answers from users and stores them in a database.

[1526] "Means for analyzing and using an emotion engine to recognize an emotional state" refers to a process in which the server analyzes the user's information and answers and uses an emotion engine to recognize the user's emotional state.

[1527] "Means for generating optimal job information based on the recognized emotional state and user information" refers to a process for generating optimal job information by combining the emotional state recognized by the emotion engine with the user's work history information and desired conditions.

[1528] The "means for providing the generated job information to the user" refers to a means for presenting the job information generated by the server to the user.

[1529] "Means for providing candidate information to companies that post job information" refers to the process by which the server provides information on selected candidates to companies.

[1530] An "emotion engine" refers to software or algorithms that recognize a user's emotional state from their input and responses.

[1531] "Machine learning algorithm" refers to a technology that learns patterns from data and performs analysis and predictions.

[1532] "Means for calculating the degree of matching" refers to the algorithm or process for comparing user information with job information, calculating the degree of matching, and making the best match.

[1533] This invention is a system that provides optimal job information to job seekers, and by combining it with an emotion engine, it realizes optimal job matching that takes into account the user's emotional state. Specifically, the user inputs their work history and desired conditions using a terminal, and the server receives and analyzes this to generate and provide optimal job information. Furthermore, the emotion engine is used to recognize the user's emotional state, and job information that reflects this is provided.

[1534] Hardware and Software Configuration

[1535] This system includes a device used by the user, a server that receives and analyzes data, a database that stores the data, and an emotion engine that recognizes emotions. The device can be a regular computer or smartphone, while a high-performance computer system is suitable for the server. The server has a database management system (DBMS) and emotion recognition software installed.

[1536] Overview of program processing

[1537] The server performs the following program processing.

[1538] 1. Receiving and storing user information

[1539] The user enters their work history and desired job requirements using a terminal. The terminal receives this information, converts it into JSON format, and sends it as an HTTP POST request to the server. The server analyzes the received information and stores it in a database.

[1540] 2. Posting Questions and Receiving Answers

[1541] The server sends predefined questions to the user's device. For example, questions like "Do you value teamwork?" or "Do you prefer a company that allows remote work?" The user answers these questions, and the device collects the user's answers, converts them into JSON format, and sends them to the server. The server parses the answers and stores them in a database.

[1542] 3. Recognizing emotional states

[1543] The server sends the user's input information and answers to the emotion engine. The emotion engine analyzes this information and recognizes the user's emotional state. For example, it detects positive emotions (joy) from the user's answers. The recognized emotional state is sent to the server, which stores it in a database.

[1544] 4. Job information matching and provision

[1545] The server runs a matching algorithm to match job listings in the database based on the user's work history, desired conditions, and recognized emotional state. It selects the most suitable job listing and sends the results to the terminal. The terminal then displays the most suitable job listing to the user.

[1546] 5. Providing information to companies

[1547] Once the user selects the job postings they are interested in, the server provides that information to the company, which then receives the candidate's profile information and emotional state and uses that information to carry out the next steps (such as setting up an interview).

[1548] Specific examples

[1549] For example, a job seeker named Taro Yamada accesses the system and enters his name, address, work history (e.g., 5 years of Java development experience), skill set (e.g., Java, Python), and desired conditions (e.g., willingness to work remotely). The terminal converts this information into JSON format and sends it to the server. The server receives the information and stores it in a database.

[1550] Next, the server asks Yamada, "Do you value teamwork?", and Yamada answers "Yes." The device converts this answer into JSON format and sends it to the server. The server receives the answer and stores it in a database.

[1551] The server then sends Yamada's information and answer to the emotion engine, which recognizes the positive emotion (joy). This emotional state is sent to the server and stored in a database.

[1552] Finally, the server matches Yamada's information and emotional state with job listings in the database and selects the most suitable one (e.g., "Company B - Java Engineer (remote work available)"). This information is sent to the device and displayed to Yamada. If Yamada shows interest, the server provides the information to the company, which then schedules an interview.

[1553] Prompt Sentence Examples

[1554] Please enter your work history information

[1555] Please tell us your preferred work environment

[1556] "Do you value teamwork?"

[1557] "Do you want a company that allows you to work remotely?"

[1558] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1559] Step 1: Enter your user information

[1560] User: A user accesses the system using a terminal and enters their work history information (e.g., name, address, work experience, skill set) and desired conditions (e.g., desired work environment). For example, Taro Yamada enters "5 years of Java development experience" and "preferred remote work."

[1561] Input: Name, address, work experience, skill set, desired work environment.

[1562] Output: JSON format data of user input information.

[1563] Terminal: The terminal receives this information in real time, converts it into a specified JSON format, checks the converted JSON data, and displays a button to proceed to the next step.

[1564] Step 2: Sending data

[1565] Terminal: The terminal sends the converted JSON data to the server as an HTTP POST request. Specifically, the following is an example request: "POST / register { "name": "Yamada Taro", "address": "Shinjuku-ku, Tokyo", "experience": "5 years of Java development experience", "skills": ["Java", "Python"], "preferences": "Remote work available"}"

[1566] Input: User information data in JSON format.

[1567] Output: A message confirming the completion of the transmission.

[1568] Server: The server receives the HTTP POST request and checks the validity of the data. After checking, it saves the information in the database and returns a processing completion response to the terminal. Example: "HTTP / 1.1 200 OK { "status": "success", "message": "User data saved successfully"}"

[1569] Step 3: Posting a question and receiving an answer

[1570] Server: The server sends predefined questions to the device. For example, "Do you value teamwork?" or "Do you want to work for a company that allows remote work?"

[1571] Input: A predefined question in text format.

[1572] Output: Question list data in JSON format.

[1573] Terminal: The terminal launches an interface to display the received list of questions to the user, for example, providing a "yes" or "no" option for each question.

[1574] User: The user answers each question. For example, "Do you value teamwork?" with "Yes."

[1575] Input: User's answer (in text format).

[1576] Output: JSON format data of user responses.

[1577] Terminal: The terminal collects the user's answers, converts them back into JSON format, and sends them to the server.

[1578] Step 4: Recognizing your emotional state

[1579] Server: The server sends the user's input information and responses to the emotion engine.

[1580] Input: JSON format data of user information and answers.

[1581] Output: JSON format data of the emotional state and its confidence.

[1582] Emotion Engine: The emotion engine analyzes the incoming data and recognizes the user's emotional state. Example: "Emotional state: joy, confidence: 0.85"

[1583] Server: Receives the emotional state sent from the emotion engine and stores it in a database.

[1584] Step 5: Job Matching

[1585] Server: The server uses a matching algorithm to analyze job listings in the database based on the user's work history, desired conditions, and perceived emotional state.

[1586] Input: JSON format data of user information, desired conditions, and emotional state.

[1587] Output: Matching results in JSON format.

[1588] Server: Runs a matching algorithm and selects the job listing that best suits the user. Example: "Company B - Java Engineer (Remote work available)"

[1589] Server: Generates a list of selected job information in JSON format and sends it to the terminal.

[1590] Step 6: View your job listings

[1591] Device: Display the received job information list on the user interface. Example: "Company B - Java Engineer (remote work available)"

[1592] Input: JSON format data for job listings.

[1593] Output: Job listing screen.

[1594] User: The user reviews the displayed job listings and selects the job listings that interest them.

[1595] Step 7: Provide information to companies

[1596] Terminal: Notifies the server of the job information selected by the user. Example: Sends JSON data including the ID of the selected job information.

[1597] Input: The ID of the selected job posting.

[1598] Output: A message confirming your selection.

[1599] Server: The server sends the user's profile information and emotional state to the company's HR system based on the selected job information. Example: "JSON data containing the candidate profile and emotional state."

[1600] Input: JSON format data of user profile information and emotional state.

[1601] Output: A message confirming notification to the company.

[1602] Company: Based on the received information, the company's human resources personnel will carry out the next process (e.g., scheduling an interview).

[1603] (Application example 2)

[1604] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1605] Conventional job information systems only consider the user's career history and desired conditions, and there are challenges in improving the accuracy of job matching by incorporating the user's emotional state. Furthermore, there is a lack of proposals for products and services that correspond to the emotional state of each individual user. Therefore, it is necessary to develop a system that provides optimal job information that takes into account the user's emotional state and proposes products and services that correspond to the user's emotional state.

[1606] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1607] In this invention, the server includes a means for a user to input work history information and desired conditions, a means for receiving the input information and storing it in a database, and a means for presenting questions to the user regarding the job content and work environment and receiving the answers, thereby making it possible to collect the user's work history information and desired conditions.

[1608] The system further includes a means for storing the received responses in a database, a means for analyzing the user's information and responses and generating optimal job information, a means for providing the generated job information to the user, and a means for providing candidate information to companies that submit job information. This makes it possible to provide optimal job information from the collected information to the user and to appropriately provide candidate information to companies.

[1609] The system also includes a means for analyzing the user's input information and responses using an emotion engine to recognize the user's emotional state, and a means for recommending optimal products and services in consideration of the user's emotional state. This makes it possible to provide highly accurate job information that incorporates the user's emotional state, and to suggest products and services according to the user's emotional state.

[1610] "Means for users to input their work history information and desired working conditions" refers to the interface that allows job seekers to input their work history and desired working conditions into the system.

[1611] "Means for receiving input information and storing it in a database" refers to the function by which the system receives information input by job seekers and stores that information in a database.

[1612] "Means of presenting questions about job content and work environment and receiving answers" refers to the function of presenting questions about the work environment and job content to job seekers and collecting their answers.

[1613] "Means for storing received responses in a database" refers to the function by which the system receives responses collected from job seekers and stores them in a database.

[1614] "Means for analyzing user information and responses and generating optimal job information" refers to algorithms and programs that analyze data based on the information and responses provided by job seekers and create job information that best matches them.

[1615] The "means for providing generated job information to a user" refers to an interface for displaying or notifying job seekers of the job information resulting from the analysis.

[1616] "Means of providing candidate information to companies posting job openings" refers to the function of providing information on job seekers' profiles and suitability to companies posting job openings.

[1617] An "emotion engine" refers to a system that analyzes a user's input information and responses to evaluate the user's emotional state.

[1618] "Means for recognizing the user's emotional state" refers to a function that uses an emotion engine to detect the user's current emotional state and reflects that information in the system.

[1619] "Means for recommending optimal products and services taking into account the user's emotional state" refers to algorithms or programs that suggest the most suitable products and services to a user based on the user's emotional state.

[1620] A "machine learning algorithm" is a type of computer program used to create predictive models in data analysis.

[1621] MODE FOR CARRYING OUT THE INVENTION

[1622] This invention is a system that provides optimal job information by analyzing the user's work history and desired conditions after inputting the information. It also uses an emotion engine to consider the user's emotional state, and can provide job information and recommend products and services based on the user's emotions.

[1623] Hardware and software used

[1624] Hardware: Smartphone camera, microphone

[1625] Software: OpenCV, EmotionRecognizer (proprietary emotion recognition engine), RecommendationEngine (proprietary recommendation engine)

[1626] System configuration

[1627] This system includes a terminal used by the user, a server, a database, and an emotion engine, and is realized using the following hardware and software:

[1628] Terminal

[1629] Users access the system using a device such as a smartphone and enter their work history and desired conditions. The device receives the entered information and sends it to the server via an HTTP POST request. An interface is also provided for users to enter their work history and desired conditions into the device.

[1630] server

[1631] The server analyzes the information received from the device and stores it in a database. The server also sends a list of predefined questions to the user to the device, receives the answers, and stores them in a database. Furthermore, the server uses an emotion engine to analyze and recognize the user's emotional state based on the user's input information and answers. The recognized emotional state data is stored in a database.

[1632] Emotion Engine

[1633] The emotion engine recognizes the user's emotional state (e.g., stress, joy, anxiety) based on the user's information and responses sent from the server. This makes it possible to provide optimal job information that takes the user's emotional state into consideration. In addition, the recommendation engine recommends products and services that are suitable for the user based on the emotional state recognized by the emotion engine.

[1634] Data processing and calculation

[1635] The server uses the Emotion Engine and Recommendation Engine to process and calculate data as follows:

[1636] 1. Emotion Recognition: We use OpenCV to capture video from a smartphone camera and EmotionRecognizer to analyze the user's emotional state. Specifically, we analyze facial expression data to recognize emotions such as stress, joy, and anxiety.

[1637] 2. Data analysis: Based on the user's work history, desired conditions, and responses, the system uses a recommendation algorithm to analyze and generate optimal job listings. It also suggests products and services based on the user's emotional state.

[1638] Specific examples

[1639] Example 1: Providing job information based on the user's emotional state

[1640] A user logs into the system and enters their work history information (e.g., 5 years of Java development experience) and desired work environment (e.g., remote work acceptable). After answering corresponding questions (e.g., "Do you value teamwork?"), emotion recognition is performed using the smartphone camera. Through this process, the emotional state of "joy" is recognized. Based on this information, the server provides the user with job information that is most suitable for them.

[1641] Example 2: Product suggestions based on emotional state

[1642] Based on user input and emotion recognition data from the camera (e.g., high stress), the recommendation engine suggests relaxing products (e.g., a tea set with a relaxing effect).

[1643] Example prompts for generative AI models

[1644] "Design an application that analyzes a user's emotional state based on facial expression data, and recommends products that have a relaxing effect if the user's stress level is recognized as high."

[1645] As described above, we provide a highly accurate job information providing system that incorporates the user's emotional state, and a mechanism for recommending products and services based on the user's emotional state.

[1646] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1647] Step 1:

[1648] The user inputs work history information and desired conditions.

[1649] Input: User's work history (e.g., 5 years of Java development experience) and desired conditions (e.g., remote work acceptable)

[1650] How it works: Input is made through the smartphone interface, and the device receives the information, converts it into JSON format, and sends it to the server.

[1651] Output: User's work history and desired conditions sent to the server

[1652] Step 2:

[1653] The server receives the entered information and stores it in a database.

[1654] Input: User's work history and desired conditions sent from the device (JSON format)

[1655] How it works: The server parses the information, validates the data, and then stores it in a database.

[1656] Output: User information stored in the database

[1657] Step 3:

[1658] The server presents the user with questions about their job duties and work environment and receives their answers.

[1659] Input: User's work history and desired conditions stored in the database

[1660] How it works: The server generates a list of predefined questions and sends them to the terminal via HTTP requests. The user enters answers to the questions, and the terminal receives the answers and sends them to the server.

[1661] Output: User's answer sent to the server

[1662] Step 4:

[1663] The server stores the received response in a database.

[1664] Input: User's answer (e.g., "Do you value teamwork?": "Yes")

[1665] How it works: The server stores the received answers in a database and prepares them for analysis.

[1666] Output: User answers stored in the database

[1667] Step 5:

[1668] The server sends the user's input information and responses to the emotion engine.

[1669] Input: User information and answers stored in a database

[1670] How it works: The server sends the user's information and responses to the emotion engine, which analyzes it and recognizes the user's emotional state.

[1671] Output: The user's emotional state as recognized by the emotion engine (e.g., stress, joy, anxiety)

[1672] Step 6:

[1673] The server stores the emotional state data in a database.

[1674] Input: The user's emotional state sent from the emotion engine

[1675] How it works: The server stores the recognized emotional state in a database.

[1676] Output: User's emotional state stored in a database

[1677] Step 7:

[1678] The server runs a matching algorithm based on the user's work history, responses, and emotional state to generate job information.

[1679] Input: User's work history information, responses, and emotional state stored in a database

[1680] How it works: The server runs a matching algorithm to calculate the degree of match with jobs in the database.

[1681] Output: The best job listings generated

[1682] Step 8:

[1683] The server provides the generated job information to the user.

[1684] Input: Generated best-fit job listings

[1685] Operation: The server converts the job information into JSON format and sends it to the terminal as an HTTP response, which displays it on the user interface.

[1686] Output: Job listing displayed on terminal

[1687] Step 9:

[1688] Taking into account the user's emotional state, the server recommends the most suitable products and services.

[1689] Input: User's emotional state, purchase history, and category information of interest

[1690] How it works: The Recommendation Engine analyzes the user's emotional state and recommends the most suitable products and services. The server sends the results to the device, which displays them on the user interface.

[1691] Output: Recommendations for products and services displayed on the device

[1692] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1693] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1694] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1695] [Fourth embodiment]

[1696] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1697] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1698] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1699] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1700] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1701] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1702] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1703] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1704] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1705] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1706] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1707] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1708] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1709] This invention relates to a system that provides optimal job information to job seekers. Users input their work history and desired conditions, and a server receives and analyzes them to generate and provide optimal job information.

[1710] System configuration

[1711] This system includes a terminal used by the user, a database, and a server. Users use their terminal to access the system and input and receive information. The server receives the information and stores and analyzes it in the database.

[1712] Explanation of program processing

[1713] Registration Phase

[1714] User: The user enters their work history information and desired conditions into the terminal, including name, address, past work experience, skill set (e.g., Java, Python), and desired work environment (e.g., remote work acceptable).

[1715] Terminal: The terminal receives the input information, converts it into a specific data format (such as JSON), and sends it to the server.

[1716] Server: The server analyzes the received data and stores it in a database. Once the data is stored, it sends a confirmation response to the device.

[1717] Question Phase

[1718] Server: The server presents the user with predefined questions, such as "Do you value teamwork?" or "Do you prefer a company that allows remote work?"

[1719] Terminal: The terminal displays these questions in a user interface and waits for user input.

[1720] User: The user answers each question using a terminal. For example, the user answers "Yes" to the question "Do you value teamwork?"

[1721] Terminal: The terminal collects the user's answers, converts them into the specified data format, and sends them to the server.

[1722] Server: The server analyzes the received response and stores it in a database.

[1723] Matching Phase

[1724] Server: The server runs a matching algorithm based on the user's work history and answers, which allows the server to compare the user's information with job listings in its database and select the most suitable job listing.

[1725] Server: Generates a list containing selected job information and sends it to the terminal.

[1726] Terminal: The terminal displays the job listings on a user interface.

[1727] User: The user reviews the displayed job information and selects the job that interests them.

[1728] Proposal Phase

[1729] Server: The server generates an alert to the company providing the user's profile information, such as "Candidate A has been added to your job seeker list. His skill set and desired conditions match your job posting."

[1730] Company: The company receives the candidate information provided by the server and schedules interviews and next steps.

[1731] Specific examples

[1732] Example of the registration phase

[1733] User: Taro Yamada accesses the system and enters his name, address, past work experience (e.g., 5 years of Java development experience), skill set (e.g., Java, Python), and desired work environment (e.g., remote work acceptable).

[1734] Terminal: The terminal converts this information into JSON format and sends it to the server.

[1735] Server: After receiving the data and verifying its validity, the server stores it in a database and returns a processing completion response to the terminal.

[1736] Specific example of the question phase

[1737] Server: The server sends the question "Do you value teamwork?" in JSON format to the terminal.

[1738] Terminal: The terminal presents the received question to the user.

[1739] User: Yamada answers "Yes" and sends the answer to the server via his terminal.

[1740] Server: The server receives the answer and stores it in a database.

[1741] A concrete example of the matching phase

[1742] Server: Based on Yamada's profile and answers, the server uses a matching algorithm to analyze the job listings in the database and select the most suitable job listing.

[1743] Server: Generates a list containing suitable job information (e.g., "Company B - Java Engineer (remote work available)") and sends it to the device.

[1744] Terminal: The terminal displays this list to Yamada.

[1745] User: Yamada checks the displayed job information and selects the information that interests him.

[1746] Specific example of the proposal phase

[1747] Server: The server generates and sends an alert to Company B containing Taro Yamada's profile information.

[1748] Company: The company's HR will review the profile information received and schedule an interview.

[1749] In this way, a system can be constructed that realizes efficient and highly accurate job-change matching for both users and companies.

[1750] The processing flow will be explained below.

[1751] Step 1:

[1752] Users enter their work history information and desired conditions into a terminal, specifically, their name, address, past work history, skill set, and desired work environment.

[1753] Step 2:

[1754] The terminal receives the input information and converts it into a specified format such as JSON.

[1755] Step 3:

[1756] The terminal sends the converted data to the server via an HTTP POST request.

[1757] Step 4:

[1758] The server parses the received data and validates it, checking that all required fields are present, that the format is correct, etc.

[1759] Step 5:

[1760] The server saves the data that has been successfully validated in the database, and once the saving is complete, it sends the processing result to the terminal as a response.

[1761] Step 6:

[1762] The server sends a list of questions to the user in JSON format to present questions about their job duties and work environment to the terminal.

[1763] Step 7:

[1764] The terminal displays the received question list on the user interface.

[1765] Step 8:

[1766] The user inputs an answer to the displayed question, for example, "Do you value teamwork?", and answers "Yes."

[1767] Step 9:

[1768] The terminal collects the answers entered by the user, converts them back into JSON format, and sends them to the server.

[1769] Step 10:

[1770] The server analyzes the received responses and stores them in a database, adding them to the user's profile.

[1771] Step 11:

[1772] The server runs a matching algorithm based on the user's work history and responses, calculating the degree of match between the job listings in the database and the user's information.

[1773] Step 12:

[1774] The server lists the most suitable job information and generates JSON data to send to the terminal.

[1775] Step 13:

[1776] The terminal displays the received job information list on the user interface.

[1777] Step 14:

[1778] The user checks the displayed job listings and selects the job listings that interest them.

[1779] Step 15:

[1780] The server generates alerts to businesses associated with the selected job postings, providing information about suitable candidates.

[1781] Step 16:

[1782] The server sends an alert to the company's HR department containing the profile information of the selected candidate.

[1783] Step 17:

[1784] The corporate user reviews the received candidate information and decides on interviews and next steps.

[1785] Example 1

[1786] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1787] Conventional job information systems simply accept the work history information and desired conditions entered by users, and the accuracy of providing job information based on that information is low, making it difficult to provide appropriate job information that meets the user's needs.In addition, the analysis of user information and optimization of job information are limited, and detailed candidate information cannot be provided to companies, resulting in low efficiency in matching companies and users.

[1788] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1789] In this invention, the server includes means for receiving information entered by a user, converting it into a specific data format, and saving it in a database, means for presenting the user with questions about job content and work environment and receiving answers, means for saving the received answers in a database, means for analyzing the user's information and the received answers and using a matching algorithm to generate optimal job information, means for providing the generated optimal job information to the user, and means for providing user profile information to companies that submit job information. This makes it possible to provide highly accurate job information based on the user's detailed needs, and improves the efficiency of matching companies and users.

[1790] A "user" is an individual who uses this system to input work history information and desired conditions in order to obtain the most suitable job information.

[1791] "Work history information" refers to information such as the jobs, positions, and skill sets that a user has had up to now.

[1792] "Desired conditions" are the user's desired work environment, working conditions, work location, and other requirements.

[1793] "Input means" refers to an interface that allows a user to input information into the system, and is primarily operated via a terminal.

[1794] "Data format" refers to a format in which information is expressed as structured data in a certain format, such as JSON format.

[1795] A "database" is a digital storage system that can efficiently store, manage, and search structured data.

[1796] The "means for presenting questions" refers to an interface through which the server displays questions about the job content and work environment to the user.

[1797] The "means for receiving an answer" refers to an interface that allows the system to receive and analyze answers to questions returned by users.

[1798] A "matching algorithm" is a calculation method for selecting the most suitable job information based on the user's work history, desired conditions, and responses.

[1799] "Job information" refers to detailed information provided by companies about job types, positions, and related conditions.

[1800] "Profile information" is information that compiles the user's work history, skill set, desired conditions, and the like.

[1801] A "secure protocol" is a communication protocol for securely transmitting information, and includes, for example, HTTPS.

[1802] This invention relates to a system that provides optimal job information to job seekers. A user inputs their work history and desired conditions, and a server receives and analyzes the information to generate and provide optimal job information. The system includes a terminal used by the user, a database, and a server. Detailed modes for implementing the invention are described below.

[1803] System configuration

[1804] User: A user accesses the system using a terminal and enters their work history and preferences, such as their name, address, past work experience, skill set, and desired work environment.

[1805] Terminal: The terminal receives the information entered by the user and converts it into a specific data format (e.g., JSON format), which is then sent to the server via a secure protocol (e.g., HTTPS).

[1806] Server: The server analyzes the received data and stores it in a database. It presents the user with questions about the job content and work environment, and also receives and stores the answers to the questions in a database. The server analyzes the user's work history and desired conditions and generates optimal job information using a generative AI model.

[1807] Specific examples

[1808] Example of the registration phase

[1809] User: A job seeker accesses the system and enters their name, address, past work experience (e.g., 5 years of Java development experience), skill set (e.g., Java, Python), and desired work environment (e.g., remote work acceptable).

[1810] Terminal: The terminal converts this information into JSON format and sends it to the server.

[1811] Server: The server receives the data, verifies its validity, and then saves it in the database. Once the saving is complete, it returns a processing completion response to the terminal.

[1812] Specific example of the question phase

[1813] Server: The server generates the question "Do you value teamwork?" through a generative AI model and sends it to the device in JSON format.

[1814] Terminal: The terminal presents the received question to the user.

[1815] User: The user answers "yes" and sends the answer to the server via the terminal.

[1816] Server: The server receives the response and stores it in a database.

[1817] A concrete example of the matching phase

[1818] Server: Based on the user's work history information and answers to questions, the server uses a generative AI model to analyze the job listings in the database and generate the most suitable job listings.

[1819] Server: Generates a list containing suitable job information (e.g., "Company - Java Engineer (Remote Work Available)") and sends it to the device.

[1820] Terminal: The terminal displays this list to the user.

[1821] User: The user reviews the displayed job listings and selects the ones that interest them.

[1822] Specific example of the proposal phase

[1823] Server: The server generates and sends an alert to the company containing the user's profile information, stating, "The candidate has been added to your job seeker list. His skill set and preferences match your job opening."

[1824] Company: The company's HR will review the profile information received and schedule an interview.

[1825] Prompt Sentence Examples

[1826] "Please analyze the work history information and desired conditions entered by the user and generate the most suitable job information."

[1827] "Present users with a question about whether they value teamwork."

[1828] Based on the above steps, efficient and highly accurate job-change matching can be achieved for both users and companies.

[1829] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1830] Step 1:

[1831] User: The user enters their work history information and desired conditions into the terminal, specifically, their name, address, past work history (e.g., 5 years of Java development experience), skill set (e.g., Java, Python), and desired work environment (e.g., remote work acceptable).

[1832] Input: User enters work history information and desired qualifications.

[1833] Output: Information typed into the terminal.

[1834] Specific operation: The user enters the required information into the input form and clicks the submit button.

[1835] Step 2:

[1836] Terminal: The terminal receives the input information, converts it into JSON format data, and then sends this data to the server using a secure protocol (e.g., HTTPS).

[1837] Input: The work history information and desired conditions entered by the user into the terminal.

[1838] Output: JSON formatted data sent to the server.

[1839] Specific operation: The device internally converts the information into JSON format and sends the data to the server using HTTPS.

[1840] Step 3:

[1841] Server: The server analyzes the received data and saves it in the database. It verifies the validity of the data and returns an error message to the terminal if the data is invalid. If the data is normal, it saves it and then sends a response indicating that processing is complete.

[1842] Input: JSON format data sent from the terminal.

[1843] Output: User information saved in the database and a response indicating completion of the process.

[1844] Specific operation: The server verifies the validity of the data, and if it is normal, saves it in the database and sends a response to the terminal indicating that processing is complete.

[1845] Step 4:

[1846] Server: The server generates predefined questions for the user through a generative AI model and sends them to the terminal in JSON format.

[1847] Input: A prompt for the generative AI model.

[1848] Output: The JSON data of the question sent to the terminal.

[1849] Specific operation: The server generates a question using the generative AI model and sends it to the device.

[1850] Step 5:

[1851] Terminal: The terminal displays the received question on the user interface (UI). While waiting for the user's answer, it displays an answer input screen to the user.

[1852] Input: JSON data of the question sent by the server.

[1853] Output: The question displayed on the user interface.

[1854] Specific operation: The device analyzes the question data received and displays the question on the UI.

[1855] Step 6:

[1856] User: The user answers questions displayed on the device. For example, the user answers "Yes" to the question "Do you value teamwork?"

[1857] Input: The question displayed from the terminal.

[1858] Output: The answer typed into the terminal.

[1859] Specific behavior: The user enters an answer and clicks the submit button.

[1860] Step 7:

[1861] Terminal: The terminal collects the user's answers, converts them back into JSON format, and sends them to the server.

[1862] Input: The answer entered by the user.

[1863] Output: The JSON formatted response data sent to the server.

[1864] Specific operation: The device converts the response data into JSON format and sends it to the server using HTTPS.

[1865] Step 8:

[1866] Server: The server receives the response data, analyzes it, and stores it in a database.

[1867] Input: JSON formatted response data sent from the device.

[1868] Output: Response data stored in a database.

[1869] Specific operation: The server analyzes the received response data and stores it in the database.

[1870] Step 9:

[1871] Server: The server runs a matching algorithm based on the user's work history and answers to generate the most suitable job listings. The generated job listings are then listed in JSON format.

[1872] Input: User information and response data stored in a database.

[1873] Output: A list of the best job listings.

[1874] Specific operation: Launch the matching algorithm, search the database and select suitable job postings.

[1875] Step 10:

[1876] Server: Sends the generated job information list to the terminal.

[1877] Input: A list of the best job postings.

[1878] Output: A list of job postings sent to your device.

[1879] Specific operation: The server generates a job listing in JSON format and sends it to the terminal.

[1880] Step 11:

[1881] Terminal: The terminal displays the job listings on the user interface and waits for user interaction.

[1882] Input: A list of job postings sent by the server.

[1883] Output: A list of jobs displayed in a user interface.

[1884] Specific operation: The device parses the job listings and displays the list on the UI.

[1885] Step 12:

[1886] User: The user reviews the displayed job listings and selects the ones that interest them.

[1887] Input: A list of jobs displayed on a user interface.

[1888] Output: The job posting selected by the user.

[1889] What happens: User clicks on a job posting that interests them to learn more.

[1890] Step 13:

[1891] Server: The server generates and sends alerts containing the user's profile information to companies based on the selected job information.

[1892] Input: The job posting selected by the user.

[1893] Output: The alert message to be sent to the company.

[1894] Specific operation: The server generates a notification alert message and sends it to the company.

[1895] Step 14:

[1896] Company: The company receives a notification from the server, verifies the profile information provided, and takes the next step, such as scheduling an interview with the candidate.

[1897] Input: The alert message sent by the server.

[1898] Output: Interview schedule set by the company.

[1899] What happens: A company HR representative reviews the user's profile information and schedules an interview.

[1900] (Application example 1)

[1901] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1902] It is not easy for consumers to find the best products based on their preferences and budget, and they are often overwhelmed by the amount of information available. It is also difficult for businesses to find the right product approach to meet the specific needs of consumers. To solve these problems, a system is needed that provides the best product information for consumers and efficiently conveys consumer information to businesses.

[1903] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1904] In this invention, the server includes means for a user to input desired information and conditions, means for receiving the input information and saving it in a database, means for presenting the user with questions about the relevant category and budget and receiving the answers, means for saving the received answers in a database, means for analyzing the user's information and answers and generating optimal product information, means for providing the generated product information to the user, and means for providing consumer information to businesses that present product information. This enables consumers to efficiently obtain product information that best suits their needs, and enables businesses to make product suggestions that meet their targets.

[1905] "Desired information" is information about the user's requests regarding specific products or services or characteristics that the user wishes to obtain.

[1906] "Desired conditions" are the factors and criteria that a user prioritizes when selecting a product or service, and include budget, category, functions, specifications, etc.

[1907] A "database" is a collection of information that systematically stores information entered by users and information collected and generated by systems, making it easily accessible.

[1908] A "machine learning algorithm" is a method for learning patterns and rules based on large amounts of data, and predicting and classifying future data.

[1909] The "matching degree" is an index showing the compatibility between the user's desired conditions and candidate information (product information, etc.) in the database, and the higher the degree, the more suitable the product is.

[1910] "Product information" refers to detailed information about each product stored in the database, and includes multiple elements such as category, price, features, and ratings.

[1911] "Consumer information" refers to desired information and conditions entered by the user, as well as information about the user's preferences and purchasing behavior obtained from data analyzed by the system.

[1912] A "business" is an organization or company that provides goods or services and markets or sells them to consumers.

[1913] An "answer" is a specific response that a user inputs to a question presented by the system, and is information about the user's preferences and conditions.

[1914] This invention relates to a system that allows users to input desired information and conditions and provides optimal product information. The system spans terminals such as smartphones, tablets, and personal computers, as well as databases including a central server, and utilizes generative AI models to improve the user experience.

[1915] Registration Phase

[1916] User

[1917] The user inputs their desired conditions and desired information into the application on the terminal, including their name, email address, desired product category (e.g., home appliances, furniture), and budget.

[1918] Terminal

[1919] The terminal has the ability to convert input information into XML or JSON format and send it to the server, using a scripting language such as Python or the Flask framework.

[1920] server

[1921] The server analyzes the received data and stores it in a database. It creates and properly manages the database using an RDBMS such as MySQL. Once processing is complete, it returns a confirmation response to the terminal.

[1922] Question Phase

[1923] server

[1924] The server presents the user with predefined questions, such as "What category of products do you like?" or "What is your budget?"

[1925] Terminal

[1926] The terminal displays the received question on the user interface and waits for the user's answer.

[1927] User

[1928] The user answers each question using the terminal. For example, the user answers "Home appliances" to the question "Which category of products do you like?"

[1929] Terminal

[1930] The device collects the user's answers, converts them into JSON format, and sends them to the server.

[1931] server

[1932] The server analyzes the received response and stores it in a database.

[1933] Matching Phase

[1934] server

[1935] The server runs a matching algorithm to compare the user's desired conditions and responses with product information in the database, thereby generating optimal product information.

[1936] server

[1937] A list including the selected product information is generated and transmitted to the terminal.

[1938] Terminal

[1939] The terminal displays the product information list on a user interface.

[1940] User

[1941] The user checks the displayed product information and selects a product that interests them.

[1942] Proposal Phase

[1943] server

[1944] The server generates an alert containing the user's profile information to a business that provides product information, for example, by email or dashboard notification.

[1945] business operator

[1946] The business receives the consumer information provided by the server and formulates appropriate marketing and sales strategies.

[1947] Specific examples

[1948] If a user enters the desired conditions "home appliances" and "under 50,000 yen," the system will filter the corresponding products in the database and generate an optimal product list. For example, the result will be "Product A - Home Appliances (45,000 yen)." The business will also receive an alert stating, "User X is looking for a product in the home appliance category. His budget is under 50,000 yen."

[1949] Prompt Sentence Examples

[1950] Prompt: Given a user has specified a desired category of "Home Appliances" and a budget of "50,000 yen", generate a list of products that are optimal for him. Select products in the database that are in the Home Appliances category and are priced at or below 50,000 yen, and output the results in JSON format.

[1951] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1952] Step 1:

[1953] The user enters their desired conditions and desired information (name, email address, desired product category, budget, etc.) through the application on their device. The entered information is sent from the device to the server. At this time, the input information is converted into JSON format.

[1954] Step 2:

[1955] The server receives the JSON-formatted data sent from the device and validates the information, for example, checking that all required fields are filled in and that the data follows a specific format. Once validated, the data is stored in a MySQL database.

[1956] Step 3:

[1957] The server sends predefined questions to the user (such as "Which category of products do you like?" or "What is your budget?") in JSON format to the terminal. The content of the questions is stored in a database.

[1958] Step 4:

[1959] The terminal receives the questions sent from the server and displays them on a user interface. HTML and JavaScript are used to generate the interface and wait for the user's response.

[1960] Step 5:

[1961] The user answers questions through the device interface. For example, to the question "What category of products do you like?", the user answers "Home appliances." Once the answer is entered, the device converts it back into JSON format and sends it to the server.

[1962] Step 6:

[1963] The server receives the user's answers sent from the terminal and analyzes them. This analysis includes data cleaning and format matching. Once the analysis is complete, the answers are stored in the database again.

[1964] Step 7:

[1965] The server runs a matching algorithm to search the database for matching product information based on the user's desired conditions and responses. For example, this algorithm filters products whose "desired product category" is "home appliances" and whose "budget" is 50,000 yen or less.

[1966] Step 8:

[1967] The server creates a list of the results of the matching algorithm (for example, "Product A - Home Appliance (45,000 yen)") and sends it to the terminal. This list is again in JSON format.

[1968] Step 9:

[1969] The terminal receives the product information list sent from the server and displays it on the user interface, allowing the user to check the list and select products that interest them.

[1970] Step 10:

[1971] The server generates an alert containing the user's profile information and sends it to the product information provider in the form of an email or dashboard notification. For example, "User X is looking for a product in the home appliance category with a budget of 50,000 yen or less."

[1972] Step 11:

[1973] Businesses receive the consumer information sent from the server and use it as basic data for formulating appropriate marketing and sales strategies.

[1974] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1975] This invention is a system that provides optimal job information to job seekers, and by combining it with an emotion engine, it achieves optimal job matching that takes into account the user's emotional state. Users input their work history and desired conditions into a terminal, and the server receives and analyzes this information to generate and provide optimal job information. Furthermore, by using the emotion engine to recognize the user's emotional state and utilizing this information, it is possible to achieve more accurate matching.

[1976] System configuration

[1977] This system includes a terminal used by the user, a server, a database, and an emotion engine. The user uses the terminal to access the system and input and receive information. The server receives the input information and stores and analyzes it in the database. The emotion engine recognizes emotions from the user's input information and responses, and provides the results to the server.

[1978] Explanation of program processing

[1979] Registration Phase

[1980] User: The user enters their work history information and desired conditions into the terminal, specifically, their name, address, past work history, skill set, and desired work environment.

[1981] Terminal: The terminal receives the input information and converts it into a specified format such as JSON.

[1982] Terminal: Sends the converted data to the server via an HTTP POST request.

[1983] Server: The server analyzes the received data, checks its validity, and then saves it in the database. It then sends a processing completion response to the terminal.

[1984] Question Phase

[1985] Server: The server sends a list of predefined questions to the user on the device, such as "Do you value teamwork?" or "Do you prefer to work for a company that allows remote work?"

[1986] Terminal: The terminal displays the question in a user interface.

[1987] User: The user enters an answer to each question, for example, "Do you value teamwork?"

[1988] Terminal: The terminal collects the responses, converts them into JSON format, and sends them to the server.

[1989] Server: The server analyzes the received response and stores it in a database.

[1990] Emotion Recognition Phase

[1991] Server: The server sends the user's input information and responses to the emotion engine.

[1992] Emotion Engine: The emotion engine analyzes the received inputs and responses to recognize the user's emotional state (e.g., stress, joy, anxiety).

[1993] Emotion engine: Sends the recognized emotional state to the server.

[1994] Server: The server stores the emotional state data in a database.

[1995] Matching Phase

[1996] Server: The server runs a matching algorithm based on the user's work history and emotional state, which calculates the degree of match between the job listings in the database and the user's information.

[1997] Server: Uses a matching algorithm to list the most suitable job information and generates JSON data to send to the terminal.

[1998] Terminal: The terminal displays the job listings on a user interface.

[1999] User: The user reviews the displayed job listings and selects the job listings that interest them.

[2000] Proposal Phase

[2001] Server: The server generates alerts to the enterprise that include the user's profile information and emotional state.

[2002] Server: Sends an alert to the company's HR department containing the profile information and emotional state of the selected candidate.

[2003] Corporate User: The corporate user reviews the received candidate information and emotional state and decides on interviews and next steps.

[2004] Specific examples

[2005] Example of the registration phase

[2006] User: Taro Yamada accesses the system and enters his name, address, past work experience (e.g., 5 years of Java development experience), skill set (e.g., Java, Python), and desired work environment (e.g., remote work acceptable).

[2007] Terminal: The terminal converts this information into JSON format and sends it to the server.

[2008] Server: After receiving the data and verifying its validity, the server stores it in a database and returns a processing completion response to the terminal.

[2009] Specific example of the question phase

[2010] Server: The server sends the question "Do you value teamwork?" to the device.

[2011] Terminal: The terminal presents the received question to the user.

[2012] User: Yamada answers "Yes" and sends the answer to the server via his terminal.

[2013] Server: The server receives the answer and stores it in a database.

[2014] A concrete example of the emotion recognition phase

[2015] Server: The server sends Yamada's information and response to the emotion engine.

[2016] Emotion Engine: The emotion engine analyzes Yamada's input and responses and recognizes his emotional state (e.g., joy).

[2017] Emotion engine: Sends the recognized emotional state to the server.

[2018] Server: The server stores the emotional states in a database.

[2019] A concrete example of the matching phase

[2020] Server: Based on Yamada's profile, responses, and emotional state, the server uses a matching algorithm to analyze the job listings in the database and select the most suitable job listing.

[2021] Server: Generates a list containing suitable job information (e.g., "Company B - Java Engineer (remote work available)") and sends it to the device.

[2022] Terminal: The terminal displays this list to Yamada.

[2023] User: Yamada checks the displayed job information and selects the information that interests him.

[2024] Specific example of the proposal phase

[2025] Server: The server generates and sends an alert to Company B containing Yamada's profile information and emotional state.

[2026] Corporate: Corporate HR personnel review the received profile information and emotional state and schedule an interview.

[2027] In this way, a system can be constructed that takes into account the user's emotional state and achieves more accurate job change matching.

[2028] The processing flow will be explained below.

[2029] Step 1:

[2030] Users enter their work history information and desired conditions into the terminal, specifically, their name, address, past work history, skill set (e.g., Java, Python), and desired work environment (e.g., remote work allowed).

[2031] Step 2:

[2032] The terminal receives the input information and converts it into a specified format such as JSON.

[2033] Step 3:

[2034] The terminal sends the converted data to the server via an HTTP POST request.

[2035] Step 4:

[2036] The server parses the received data and validates it, checking that all required fields are present, that the format is correct, etc.

[2037] Step 5:

[2038] The server saves the data that has been successfully validated in the database, and once the saving is complete, it sends the processing result to the terminal as a response.

[2039] Step 6:

[2040] The server sends a list of questions to the user in JSON format to present questions about their job duties and work environment to the terminal.

[2041] Step 7:

[2042] The terminal displays the received question list on the user interface.

[2043] Step 8:

[2044] The user inputs an answer to the displayed question, for example, "Do you value teamwork?", and answers "Yes."

[2045] Step 9:

[2046] The terminal collects the answers entered by the user, converts them back into JSON format, and sends them to the server.

[2047] Step 10:

[2048] The server analyzes the received response and stores it in a database.

[2049] Step 11:

[2050] The server sends the user's input information and responses to the emotion engine.

[2051] Step 12:

[2052] The emotion engine analyzes the received inputs and responses to recognize the user's emotional state (e.g., stress, joy, anxiety).

[2053] Step 13:

[2054] The emotion engine transmits the recognized emotional state to the server.

[2055] Step 14:

[2056] The server stores the emotional states in a database.

[2057] Step 15:

[2058] The server runs a matching algorithm based on the user's work history and emotional state, and calculates the degree of match between the job listings in the database and the user's information.

[2059] Step 16:

[2060] The server lists the most suitable job information and generates JSON data to send to the terminal.

[2061] Step 17:

[2062] The terminal displays the received job information list on the user interface.

[2063] Step 18:

[2064] The user checks the displayed job listings and selects the job listings that interest them.

[2065] Step 19:

[2066] The server generates alerts to businesses associated with selected job postings, providing information and sentiment of suitable candidates.

[2067] Step 20:

[2068] The server sends an alert to the company's HR department containing the profile information and emotional state of the selected candidate.

[2069] Step 21:

[2070] The company user reviews the received candidate information and emotional state and decides on interviews and next steps.

[2071] Example 2

[2072] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2073] Conventional job information systems only provide job information based on the user's work history and desired conditions, and do not perform job matching that takes into account the user's emotional state. As a result, it is difficult to provide job information that matches the user's actual desires and emotional state, and it has not been possible to achieve highly accurate matching.

[2074] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2075] In this invention, the server includes means for a user to input work history information and desired conditions, means for receiving the input information and saving it in a database, means for presenting questions to the user regarding job content and work environment and receiving answers, means for saving the received answers in a database, means for analyzing the user's information and answers and using an emotion engine that recognizes the user's emotional state, means for generating optimal job information based on the recognized emotional state and the user's information, means for providing the generated job information to the user, and means for providing candidate information to companies that submit job information. This enables highly accurate matching of job information that takes the user's emotional state into consideration.

[2076] "User" refers to an individual who accesses the system, inputs work history information and desired conditions, and is provided with the most suitable job information.

[2077] "Work history information" refers to information including a user's previous work experience, skill set, and related accomplishments.

[2078] "Desired conditions" refers to conditions including the user's desired work environment, working conditions, work location, salary, etc.

[2079] "Input means" refers to the interface or device that allows a user to provide their work history information and desired conditions to the system.

[2080] "Means for receiving and storing in a database" refers to the process by which the server receives the information sent by the user and stores it in a database.

[2081] The "means for presenting questions and receiving answers" refers to a method by which the server asks the user questions about the job content and work environment and receives the user's answers.

[2082] "Means for storing the received answers in a database" refers to the process by which the server receives answers from users and stores them in a database.

[2083] "Means for analyzing and using an emotion engine to recognize an emotional state" refers to a process in which the server analyzes the user's information and answers and uses an emotion engine to recognize the user's emotional state.

[2084] "Means for generating optimal job information based on the recognized emotional state and user information" refers to a process for generating optimal job information by combining the emotional state recognized by the emotion engine with the user's work history information and desired conditions.

[2085] The "means for providing the generated job information to the user" refers to a means for presenting the job information generated by the server to the user.

[2086] "Means for providing candidate information to companies that post job information" refers to the process by which the server provides information on selected candidates to companies.

[2087] An "emotion engine" refers to software or algorithms that recognize a user's emotional state from their input and responses.

[2088] "Machine learning algorithm" refers to a technology that learns patterns from data and performs analysis and predictions.

[2089] "Means for calculating the degree of matching" refers to the algorithm or process for comparing user information with job information, calculating the degree of matching, and making the best match.

[2090] This invention is a system that provides optimal job information to job seekers, and by combining it with an emotion engine, it realizes optimal job matching that takes into account the user's emotional state. Specifically, the user inputs their work history and desired conditions using a terminal, and the server receives and analyzes this to generate and provide optimal job information. Furthermore, the emotion engine is used to recognize the user's emotional state, and job information that reflects this is provided.

[2091] Hardware and Software Configuration

[2092] This system includes a device used by the user, a server that receives and analyzes data, a database that stores the data, and an emotion engine that recognizes emotions. The device can be a regular computer or smartphone, while a high-performance computer system is suitable for the server. The server has a database management system (DBMS) and emotion recognition software installed.

[2093] Overview of program processing

[2094] The server performs the following program processing.

[2095] 1. Receiving and storing user information

[2096] The user enters their work history and desired job requirements using a terminal. The terminal receives this information, converts it into JSON format, and sends it as an HTTP POST request to the server. The server analyzes the received information and stores it in a database.

[2097] 2. Posting Questions and Receiving Answers

[2098] The server sends predefined questions to the user's device. For example, questions like "Do you value teamwork?" or "Do you prefer a company that allows remote work?" The user answers these questions, and the device collects the user's answers, converts them into JSON format, and sends them to the server. The server parses the answers and stores them in a database.

[2099] 3. Recognizing emotional states

[2100] The server sends the user's input information and answers to the emotion engine. The emotion engine analyzes this information and recognizes the user's emotional state. For example, it detects positive emotions (joy) from the user's answers. The recognized emotional state is sent to the server, which stores it in a database.

[2101] 4. Job information matching and provision

[2102] The server runs a matching algorithm to match job listings in the database based on the user's work history, desired conditions, and recognized emotional state. It selects the most suitable job listing and sends the results to the terminal. The terminal then displays the most suitable job listing to the user.

[2103] 5. Providing information to companies

[2104] Once the user selects the job postings they are interested in, the server provides that information to the company, which then receives the candidate's profile information and emotional state and uses that information to carry out the next steps (such as setting up an interview).

[2105] Specific examples

[2106] For example, a job seeker named Taro Yamada accesses the system and enters his name, address, work history (e.g., 5 years of Java development experience), skill set (e.g., Java, Python), and desired conditions (e.g., willingness to work remotely). The terminal converts this information into JSON format and sends it to the server. The server receives the information and stores it in a database.

[2107] Next, the server asks Yamada, "Do you value teamwork?", and Yamada answers "Yes." The device converts this answer into JSON format and sends it to the server. The server receives the answer and stores it in a database.

[2108] The server then sends Yamada's information and answer to the emotion engine, which recognizes the positive emotion (joy). This emotional state is sent to the server and stored in a database.

[2109] Finally, the server matches Yamada's information and emotional state with job listings in the database and selects the most suitable one (e.g., "Company B - Java Engineer (remote work available)"). This information is sent to the device and displayed to Yamada. If Yamada shows interest, the server provides the information to the company, which then schedules an interview.

[2110] Prompt Sentence Examples

[2111] Please enter your work history information

[2112] Please tell us your preferred work environment

[2113] "Do you value teamwork?"

[2114] "Do you want a company that allows you to work remotely?"

[2115] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2116] Step 1: Enter your user information

[2117] User: A user accesses the system using a terminal and enters their work history information (e.g., name, address, work experience, skill set) and desired conditions (e.g., desired work environment). For example, Taro Yamada enters "5 years of Java development experience" and "preferred remote work."

[2118] Input: Name, address, work experience, skill set, desired work environment.

[2119] Output: JSON format data of user input information.

[2120] Terminal: The terminal receives this information in real time, converts it into a specified JSON format, checks the converted JSON data, and displays a button to proceed to the next step.

[2121] Step 2: Sending data

[2122] Terminal: The terminal sends the converted JSON data to the server as an HTTP POST request. Specifically, the following is an example request: "POST / register { "name": "Yamada Taro", "address": "Shinjuku-ku, Tokyo", "experience": "5 years of Java development experience", "skills": ["Java", "Python"], "preferences": "Remote work available"}"

[2123] Input: User information data in JSON format.

[2124] Output: A message confirming the completion of the transmission.

[2125] Server: The server receives the HTTP POST request and checks the validity of the data. After checking, it saves the information in the database and returns a processing completion response to the terminal. Example: "HTTP / 1.1 200 OK { "status": "success", "message": "User data saved successfully"}"

[2126] Step 3: Posting a question and receiving an answer

[2127] Server: The server sends predefined questions to the device. For example, "Do you value teamwork?" or "Do you want to work for a company that allows remote work?"

[2128] Input: A predefined question in text format.

[2129] Output: Question list data in JSON format.

[2130] Terminal: The terminal launches an interface to display the received list of questions to the user, for example, providing a "yes" or "no" option for each question.

[2131] User: The user answers each question. For example, "Do you value teamwork?" with "Yes."

[2132] Input: User's answer (in text format).

[2133] Output: JSON format data of user responses.

[2134] Terminal: The terminal collects the user's answers, converts them back into JSON format, and sends them to the server.

[2135] Step 4: Recognizing your emotional state

[2136] Server: The server sends the user's input information and responses to the emotion engine.

[2137] Input: JSON format data of user information and answers.

[2138] Output: JSON format data of the emotional state and its confidence.

[2139] Emotion Engine: The emotion engine analyzes the incoming data and recognizes the user's emotional state. Example: "Emotional state: joy, confidence: 0.85"

[2140] Server: Receives the emotional state sent from the emotion engine and stores it in a database.

[2141] Step 5: Job Matching

[2142] Server: The server uses a matching algorithm to analyze job listings in the database based on the user's work history, desired conditions, and perceived emotional state.

[2143] Input: JSON format data of user information, desired conditions, and emotional state.

[2144] Output: Matching results in JSON format.

[2145] Server: Runs a matching algorithm and selects the job listing that best suits the user. Example: "Company B - Java Engineer (Remote work available)"

[2146] Server: Generates a list of selected job information in JSON format and sends it to the terminal.

[2147] Step 6: View your job listings

[2148] Device: Display the received job information list on the user interface. Example: "Company B - Java Engineer (remote work available)"

[2149] Input: JSON format data for job listings.

[2150] Output: Job listing screen.

[2151] User: The user reviews the displayed job listings and selects the job listings that interest them.

[2152] Step 7: Provide information to companies

[2153] Terminal: Notifies the server of the job information selected by the user. Example: Sends JSON data including the ID of the selected job information.

[2154] Input: The ID of the selected job posting.

[2155] Output: A message confirming your selection.

[2156] Server: The server sends the user's profile information and emotional state to the company's HR system based on the selected job information. Example: "JSON data containing the candidate profile and emotional state."

[2157] Input: JSON format data of user profile information and emotional state.

[2158] Output: A message confirming notification to the company.

[2159] Company: Based on the received information, the company's human resources personnel will carry out the next process (e.g., scheduling an interview).

[2160] (Application example 2)

[2161] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2162] Conventional job information systems only consider the user's career history and desired conditions, and there are challenges in improving the accuracy of job matching by incorporating the user's emotional state. Furthermore, there is a lack of proposals for products and services that correspond to the emotional state of each individual user. Therefore, it is necessary to develop a system that provides optimal job information that takes into account the user's emotional state and proposes products and services that correspond to the user's emotional state.

[2163] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2164] In this invention, the server includes a means for a user to input work history information and desired conditions, a means for receiving the input information and storing it in a database, and a means for presenting questions to the user regarding the job content and work environment and receiving the answers, thereby making it possible to collect the user's work history information and desired conditions.

[2165] The system further includes a means for storing the received responses in a database, a means for analyzing the user's information and responses and generating optimal job information, a means for providing the generated job information to the user, and a means for providing candidate information to companies that submit job information. This makes it possible to provide optimal job information from the collected information to the user and to appropriately provide candidate information to companies.

[2166] The system also includes a means for analyzing the user's input information and responses using an emotion engine to recognize the user's emotional state, and a means for recommending optimal products and services in consideration of the user's emotional state. This makes it possible to provide highly accurate job information that incorporates the user's emotional state, and to suggest products and services according to the user's emotional state.

[2167] "Means for users to input their work history information and desired working conditions" refers to the interface that allows job seekers to input their work history and desired working conditions into the system.

[2168] "Means for receiving input information and storing it in a database" refers to the function by which the system receives information input by job seekers and stores that information in a database.

[2169] "Means of presenting questions about job content and work environment and receiving answers" refers to the function of presenting questions about the work environment and job content to job seekers and collecting their answers.

[2170] "Means for storing received responses in a database" refers to the function by which the system receives responses collected from job seekers and stores them in a database.

[2171] "Means for analyzing user information and responses and generating optimal job information" refers to algorithms and programs that analyze data based on the information and responses provided by job seekers and create job information that best matches them.

[2172] The "means for providing generated job information to a user" refers to an interface for displaying or notifying job seekers of the job information resulting from the analysis.

[2173] "Means of providing candidate information to companies posting job openings" refers to the function of providing information on job seekers' profiles and suitability to companies posting job openings.

[2174] An "emotion engine" refers to a system that analyzes a user's input information and responses to evaluate the user's emotional state.

[2175] "Means for recognizing the user's emotional state" refers to a function that uses an emotion engine to detect the user's current emotional state and reflects that information in the system.

[2176] "Means for recommending optimal products and services taking into account the user's emotional state" refers to algorithms or programs that suggest the most suitable products and services to a user based on the user's emotional state.

[2177] A "machine learning algorithm" is a type of computer program used to create predictive models in data analysis.

[2178] MODE FOR CARRYING OUT THE INVENTION

[2179] This invention is a system that provides optimal job information by analyzing the user's work history and desired conditions after inputting the information. It also uses an emotion engine to consider the user's emotional state, and can provide job information and recommend products and services based on the user's emotions.

[2180] Hardware and software used

[2181] Hardware: Smartphone camera, microphone

[2182] Software: OpenCV, EmotionRecognizer (proprietary emotion recognition engine), RecommendationEngine (proprietary recommendation engine)

[2183] System configuration

[2184] This system includes a terminal used by the user, a server, a database, and an emotion engine, and is realized using the following hardware and software:

[2185] Terminal

[2186] Users access the system using a device such as a smartphone and enter their work history and desired conditions. The device receives the entered information and sends it to the server via an HTTP POST request. An interface is also provided for users to enter their work history and desired conditions into the device.

[2187] server

[2188] The server analyzes the information received from the device and stores it in a database. The server also sends a list of predefined questions to the user to the device, receives the answers, and stores them in a database. Furthermore, the server uses an emotion engine to analyze and recognize the user's emotional state based on the user's input information and answers. The recognized emotional state data is stored in a database.

[2189] Emotion Engine

[2190] The emotion engine recognizes the user's emotional state (e.g., stress, joy, anxiety) based on the user's information and responses sent from the server. This makes it possible to provide optimal job information that takes the user's emotional state into consideration. In addition, the recommendation engine recommends products and services that are suitable for the user based on the emotional state recognized by the emotion engine.

[2191] Data processing and calculation

[2192] The server uses the Emotion Engine and Recommendation Engine to process and calculate data as follows:

[2193] 1. Emotion Recognition: We use OpenCV to capture video from a smartphone camera and EmotionRecognizer to analyze the user's emotional state. Specifically, we analyze facial expression data to recognize emotions such as stress, joy, and anxiety.

[2194] 2. Data analysis: Based on the user's work history, desired conditions, and responses, the system uses a recommendation algorithm to analyze and generate optimal job listings. It also suggests products and services based on the user's emotional state.

[2195] Specific examples

[2196] Example 1: Providing job information based on the user's emotional state

[2197] A user logs into the system and enters their work history information (e.g., 5 years of Java development experience) and desired work environment (e.g., remote work acceptable). After answering corresponding questions (e.g., "Do you value teamwork?"), emotion recognition is performed using the smartphone camera. Through this process, the emotional state of "joy" is recognized. Based on this information, the server provides the user with job information that is most suitable for them.

[2198] Example 2: Product suggestions based on emotional state

[2199] Based on user input and emotion recognition data from the camera (e.g., high stress), the recommendation engine suggests relaxing p...

Claims

1. A means for a user to input work history information and desired conditions; means for receiving the input information and storing it in a database; a means for presenting questions to a user regarding job duties and work environment and receiving answers; a means for storing the received responses in a database; A means for analyzing user information and responses and generating optimal job information; A means for providing the generated job information to a user; A means for providing candidate information to companies that post job information; A system including:

2. The system of claim 1 , further comprising: means for using machine learning algorithms to analyze the user's information and responses.

3. The system of claim 1 , further comprising means for calculating a match degree of the job posting.

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