System

Abstract

A system is provided.SOLUTION: A system comprising: interaction module means for interacting with a candidate; skill assessment means for assessing the candidate's skills; biometric collection means for collecting biometric data of the candidate; data analysis means for analyzing the collected biometric data and skill assessment results to assess the candidate's aptitude and personality; and matching means for matching the assessment results with the needs of the enterprise.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Traditional recruitment processes rely heavily on resumes and interviews, making it difficult to fully evaluate a candidate's true skills, aptitude, and personality. As a result, it becomes difficult to select the right person for the right job, leading to problems such as hiring bias and underestimation of skills. Furthermore, these problems become more pronounced when there are a large number of applicants or when companies are seeking different skills. The purpose of this invention is to solve these problems and achieve objective, bias-free talent evaluation and matching. [Means for solving the problem]

[0005] The present invention provides a system including a dialogue module means for dialogue with candidates, a skill assessment means for assessing the skills of candidates, a biometrics collection means for collecting biometric data of candidates, a data analysis means for analyzing the collected biometric data and skill assessment results to assess the aptitude and personality of candidates, and a matching means for matching the assessment results with the needs of companies. The system further includes a generative artificial intelligence (AI) means for assessing the potential and future prospects of candidates, and a user interface means for acquiring candidate authentication information and providing a dashboard screen. This enables a comprehensive evaluation of candidates and realizes optimal talent matching tailored to the needs of companies.

[0006] "Dialogue module means" means a software component that uses artificial intelligence (AI) to engage in dialogue with candidates.

[0007] "Skills Assessment Instrument" means an algorithm and executable program for measuring and assessing a Candidate's technical or job skills.

[0008] "Biometrics collection means" refers to a sensor for collecting a candidate's biometric data (e.g., heart rate, facial expression changes, etc.) in real time and a system for processing that data.

[0009] "Data analysis means" refers to algorithms and software for comprehensively analyzing the collected biometric data and skill assessment results to evaluate the aptitude and personality of candidates.

[0010] The "matching tool" is a software component that selects the most suitable candidate based on the candidate evaluation results and the company's needs, and matches the company with the candidate.

[0011] "Generative artificial intelligence (AI) means" are algorithms and software that use generative artificial intelligence to assess a candidate's potential and future prospects.

[0012] "User Interface Means" means the graphical user interface (GUI) and authentication system for obtaining candidate authentication information and providing interaction with the system. [Brief explanation of the drawings]

[0013] [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

[0014] 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.

[0015] First, the terms used in the following description will be explained.

[0016] 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).

[0017] 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.

[0018] 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.

[0019] 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.

[0020] 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."

[0021] [First embodiment]

[0022] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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."

[0034] An embodiment of the present invention is a system for matching candidates with companies in a fairer and more efficient manner. This system includes the following elements.

[0035] 1. User Interface Methods

[0036] Users access the system using a web browser or a dedicated application and log in by entering their authentication information (ID and password).

[0037] The server checks the user's authentication information against a database, and if authentication is successful, displays the user's dashboard screen.

[0038] 2. Interaction Module Means

[0039] The device displays a "Start Dialogue" button on the dashboard screen, and when the user clicks it, the AI ​​dialogue module is launched.

[0040] The server sends the candidate an initial question (e.g., "Please tell us about yourself") and receives the user's answer.

[0041] 3. Skills Assessment Tools

[0042] The server presents candidates with skill tests and challenges through an interactive module, including programming problems and logic puzzles.

[0043] The user works on the displayed tasks and enters their answers.

[0044] The terminal transmits the user's answer to the server.

[0045] 4. Biometrics Collection Methods

[0046] The device collects biometric data from the user through wearable devices and cameras, including heart rate, facial expression changes, and reaction speed.

[0047] The server receives this data in real time and records it in a database.

[0048] 5. Data Analysis Methods

[0049] The server integrates the collected skill test answer data and biometric data and performs analysis using a data analysis module.

[0050] The data analysis module assesses candidates' skills, aptitudes, and personality, records the results, and also uses generative artificial intelligence (AI) to assess their potential and future prospects.

[0051] 6. Matching Methods

[0052] The matching module (server) compares the candidate evaluation results with the company's job information to make the best match.

[0053] The server notifies the user and the company of the matching results.

[0054] Specific examples

[0055] For example, when a user logs into the system, a dialogue module is launched and they are asked to introduce themselves. The user then takes a skill test and solves programming problems and logic puzzles. During this time, the device continues to collect the user's heart rate and facial expression changes. The data analysis module analyzes this data and provides an overall evaluation of the user. Finally, the matching module compares the evaluation results with the needs of companies and suggests the most suitable company to the user. This series of processes ensures bias-free and objective recruitment.

[0056] The above is an embodiment of the present invention, which enables companies to efficiently recruit suitable personnel for the long term.

[0057] The processing flow will be explained below.

[0058] Step 1:

[0059] Users access the system using a web browser or a dedicated application and log in by entering their ID and password.

[0060] Step 2:

[0061] The terminal transmits the input authentication information to the server.

[0062] Step 3:

[0063] The server checks the authentication information against a database, and if authentication is successful, generates a dashboard screen for the user and sends it to the terminal.

[0064] Step 4:

[0065] The terminal displays a dashboard screen to the user.

[0066] Step 5:

[0067] The user clicks the "Start conversation" button on the dashboard.

[0068] Step 6:

[0069] The server launches an AI dialogue module, generates an initial question for the candidate, and sends it to the terminal.

[0070] Step 7:

[0071] The terminal displays the initial question sent from the server (e.g., "Please introduce yourself") to the user.

[0072] Step 8:

[0073] The user inputs the answer to the question and sends it to the server via the terminal.

[0074] Step 9:

[0075] The server receives the user's answer, generates the next question or challenge, and sends it to the terminal.

[0076] Step 10:

[0077] The device displays the next question or challenge (e.g., a skills test question) to the user.

[0078] Step 11:

[0079] The user solves the problem and sends the answer to the server via the terminal.

[0080] Step 12:

[0081] The terminal transmits the user's answers to the server, and at the same time collects the user's biometric data (e.g., heart rate, facial expression changes) and transmits it to the server in real time.

[0082] Step 13:

[0083] The server records the received answer data and biometric data in a database.

[0084] Step 14:

[0085] The data analysis module (server) analyzes this data and makes a comprehensive assessment of the candidate's skills, aptitude, personality, potential, and future prospects.

[0086] Step 15:

[0087] The server generates and sends the evaluation results to the matching module.

[0088] Step 16:

[0089] The matching module (server) compares the evaluation results with company job information to make the best match.

[0090] Step 17:

[0091] The server generates data for notifying the user and the company of the matching results and transmits the data to the terminal.

[0092] Step 18:

[0093] The device displays the matching results to the user, and the results are also notified to the company's recruiting staff.

[0094] Example 1

[0095] 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."

[0096] In the modern recruitment process, matching between candidates and companies is often influenced by subjective factors, making it difficult to achieve fair and efficient matching. Furthermore, there is a need to evaluate not only candidates' skills and aptitude, but also their potential and future prospects. Current technology lacks a system that can comprehensively evaluate these factors and achieve optimal matching, so this problem needs to be solved.

[0097] 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.

[0098] In this invention, the server includes a user interface means, a dialogue module means for dialogue with candidates, a skill evaluation means for evaluating the skills of the candidates, a biometrics collection means for collecting biometric data of the candidates, a data analysis means for analyzing the collected biometric data and the skill evaluation results to evaluate the aptitude and personality of the candidates, and a matching means for matching the evaluation results with the needs of companies, thereby enabling fair and efficient matching of candidates and companies.

[0099] The "user interface means" is a means by which a user accesses the system, inputs authentication information, and performs various operations via the dashboard screen.

[0100] The "dialogue module means" is a module for dialogue with candidates, and is a means for presenting initial questions and skill test tasks and collecting responses from candidates.

[0101] A "skill assessment means" is a means for assessing the skills of a candidate, and is a means for presenting tasks such as programming problems and logic puzzles and accepting the candidate's answers.

[0102] "Biometrics collection means" means a means for collecting biometric data such as a candidate's heart rate, facial expression changes, reaction speed, etc. This includes wearable devices and cameras.

[0103] "Data Analysis Means" refers to means for integrating collected biometric data and skill assessment results to evaluate a candidate's aptitude and personality, including a data analysis module and a generative AI model.

[0104] "Matching methods" are methods for comparing candidate evaluation results with the needs of the company to achieve optimal matching. Based on the evaluation results, the company proposes the most suitable candidate.

[0105] A "generative artificial intelligence (AI) means" is a means that uses AI technology to assess a candidate's potential and future prospects.

[0106] An embodiment of the present invention is a system for matching candidates with companies in a fairer and more efficient manner. This system includes the following elements.

[0107] 1. User Interface Methods

[0108] A user accesses the system using a web browser or a dedicated application and enters authentication information (ID and password) to log in. The server checks the user's authentication information against a database (e.g., MySQL database), and if authentication is successful, displays the user's dashboard screen.

[0109] 2. Interaction Module Means

[0110] The terminal displays a "Start Dialogue" button on the dashboard screen, and when the user clicks it, the AI ​​dialogue module is launched. The server sends the first question to the candidate (e.g., "Please introduce yourself") and receives the user's answer.

[0111] 3. Skills Assessment Tools

[0112] The server presents skill tests and challenges to the candidate through the dialogue module, such as programming problems and logic puzzles. The user works through the challenges displayed and enters their answers. The terminal then transmits the user's answers to the server.

[0113] 4. Biometrics Collection Methods

[0114] The terminal collects biometric data from the user through a wearable device or camera, including heart rate, facial expression changes, reaction speed, etc. The server receives this data in real time and records it in a database.

[0115] 5. Data Analysis Methods

[0116] The server integrates the collected skill test answer data and biometric data and analyzes them using a data analysis module. The data analysis module evaluates the candidate's skills, aptitude, and personality, and records the evaluation results. It also evaluates the candidate's potential and future prospects using generative artificial intelligence (AI) methods. This data analysis module can be implemented using Python and the scikit-learn library.

[0117] 6. Matching Methods

[0118] The matching module (server) compares the candidate's evaluation results with the company's job information to find the best match. The server then notifies the user and the company of the matching results. Notification can be via email or in-system messages.

[0119] Specific examples

[0120] For example, when a user logs into the system, the server displays a dashboard screen after authentication. The terminal then displays a "Start Dialogue" button, and when the user clicks it, the server sends a message saying, "Please introduce yourself." When the user enters their answers to a skill test, the data is sent to the server. The terminal also collects the user's real-time biometric data and sends it to the server. Finally, the server analyzes this data, performs optimal matching with companies, and notifies the user and company of the results.

[0121] Prompt Sentence Examples

[0122] "Please introduce yourself."

[0123] "Solve a programming problem. Example: Predict the output of the following code."

[0124] "Please relax as we will be recording your heart rate and facial expressions."

[0125] The above is an embodiment of the present invention, which realizes fair and efficient matching between candidates and companies. Furthermore, the various means included in the system work in conjunction with each other to provide highly accurate evaluation and optimal matching.

[0126] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0127] Step 1:

[0128] A user accesses the system using a web browser or a dedicated application. As input, the user enters an ID and password and attempts to log in to the system. As output, an authentication request is generated and sent to the server.

[0129] Step 2:

[0130] The server compares the received authentication information with the information stored in a database (for example, a MySQL database). This process involves searching the database for the relevant user information and verifying that it matches the entered ID and password. The output is an authentication result (success or failure).

[0131] Step 3:

[0132] If authentication is successful, the server displays the user's dashboard screen. If there is an error message, it notifies the user. The server makes a decision based on the authentication result as input, and generates the next screen information to be displayed as output.

[0133] Step 4:

[0134] The terminal displays a "Start Interaction" button on the dashboard screen. The configuration information of the dashboard screen is read as input, and the "Start Interaction" button is displayed on the user interface as output.

[0135] Step 5:

[0136] The user clicks the "Start Interaction" button, which generates a click event as input and sends a request to the server to start an interaction as output.

[0137] Step 6:

[0138] The server starts the AI ​​dialogue module and sends the first question (e.g., "Please introduce yourself") to the user. It receives a click event as input and generates a prompt sentence as output, which is sent to the user's device.

[0139] Step 7:

[0140] The user answers the first question by entering the answer text as input, and the answer is sent to the server as output.

[0141] Step 8:

[0142] The server records the received answers in a database. It receives the candidate's answer data as input and generates a request to save the answer contents in a database as output.

[0143] Step 9:

[0144] The server presents the candidate with the next skill test or challenge through a dialogue module, which can include programming questions, logic puzzles, etc. It receives triggers from previous answers as input and generates the next challenge as output, which it then sends to the user.

[0145] Step 10:

[0146] The user works on the displayed assignment and inputs the answer. The assignment content is read as input, and the answer is generated as output and sent to the server.

[0147] Step 11:

[0148] The terminal sends the user's answer to the server, which takes the answer data as input and generates a request to send it as output.

[0149] Step 12:

[0150] The terminal collects biometric data through a wearable device or camera attached to the user, including heart rate, facial expression changes, reaction speed, etc. It receives sensor data as input and transmits it to a server in real time as output.

[0151] Step 13:

[0152] The server receives the collected biometric data in real time and records it in a database. It receives the biometric data stream as input and generates a request to store the data in a database as output.

[0153] Step 14:

[0154] The server integrates the collected skill test answer data and biometric data and performs analysis using a data analysis module. It reads the integrated data as input and generates evaluation results as output.

[0155] Step 15:

[0156] The data analysis module evaluates the candidate's skills, aptitude, and personality, and records the evaluation results. Furthermore, it uses a generative AI model to evaluate the candidate's potential and future prospects. Each piece of data is analyzed as input, and a comprehensive evaluation result is generated as output.

[0157] Step 16:

[0158] The matching module (server) compares the candidate evaluation results with the company's job information to make the best match. It receives the evaluation results and the company's needs as input, and generates and notifies the matching results as output.

[0159] Step 17:

[0160] The server notifies users and companies of the matching results via email or internal system messages. Based on the matching results as input, notifications are generated and sent as output.

[0161] Through the above processing steps, the present invention achieves fair and efficient matching between candidates and companies.

[0162] (Application example 1)

[0163] 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."

[0164] Traditional staff recruitment and evaluation processes in brick-and-mortar stores require a lot of time and effort, and are prone to subjective bias. Furthermore, it is often difficult to accurately assess candidates' skills and aptitude, making it difficult to efficiently hire the best talent. Furthermore, traditional methods make it difficult to utilize biometric data, such as a candidate's stress level or reaction speed.

[0165] 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.

[0166] In this invention, the server includes a dialogue module means for dialogue with candidates, a skill evaluation means for evaluating the skills of the candidates, a biometrics collection means for collecting biometric data of the candidates, a data analysis means for analyzing the collected biometric data and the skill evaluation results and evaluating the aptitude and personality of the candidates, a matching means for matching the evaluation results with the needs of the company, a means for streamlining the staff recruitment and evaluation process for the brick-and-mortar store, a means for collecting biometric data using a smartphone camera or a wearable device, and a means for collecting input from the candidates and providing a user interface. This enables an integrated evaluation of the skills and biometric data of candidates and enables efficient and fair hiring of the best talent.

[0167] An "interaction module" is a component that interacts with candidates, generates questions, and collects answers.

[0168] A "skills assessment tool" is a tool that presents tests or tasks to assess candidates' skills and collects the results.

[0169] "Biometrics collection means" refers to a device or system that collects biometric data such as a candidate's heart rate, facial expression changes, and reaction speed.

[0170] The "data analysis means" is a module that integrates the collected biometric data with the skill assessment results to evaluate the candidate's aptitude and personality.

[0171] A "matching method" is a system that compares the candidate evaluation results with the company's needs to make the optimal match.

[0172] "Means for streamlining the staff recruitment and evaluation process for brick-and-mortar stores" refers to tools and systems that automate and streamline the traditional staff recruitment and evaluation process.

[0173] "Means for collecting biometric data using a smartphone camera or a wearable device" refers to means for collecting biometric information such as heart rate, facial expression changes, and reaction speed using a smartphone camera or a wearable device.

[0174] The "means for providing a user interface" is a component that provides an interface for candidates to log in to the system and use various functions.

[0175] This invention is a system for making the staff recruitment and evaluation process in a brick-and-mortar store more efficient and fair. Below, we will explain in detail the program and processing method for realizing this system.

[0176] The server includes a dialogue module, a skill assessment unit, a biometrics collection unit, a data analysis unit, and a matching unit, which enable an integrated assessment of a candidate's skills and biometric data, thereby enabling efficient and fair recruitment of the most suitable personnel.

[0177] Hardware and software used

[0178] Smartphones: Use cameras and touchscreens to gather user input.

[0179] Wearable devices: Used to collect biometric data such as heart rate, facial expression changes, and reaction speed.

[0180] Server: Candidate data management and analysis is performed using the Django framework.

[0181] Client-side software: Building the user interface using React.

[0182] Processing Description

[0183] 1. Authentication and Login

[0184] Users access the system using their smartphones and enter their authentication information (ID and password) to log in. The server compares this information with the database, and if authentication is successful, displays the user's dashboard screen.

[0185] 2. Starting the dialogue module

[0186] When a user clicks the "Start Dialogue" button on the dashboard screen, the dialogue module is launched. The server uses the generative AI model to generate an initial question (e.g., "Please introduce yourself") and sends it to the user.

[0187] Example prompt sentence:

[0188] "Generate the best questions for candidates to introduce themselves."

[0189] 3. Skills Assessment

[0190] Through the dialogue module, the server presents the candidate with skill tests and assignments. The user enters their answers using their smartphone, and this data is sent to the server, which stores the data and prepares it for analysis.

[0191] 4. Biometric Data Collection

[0192] Candidates wear wearable devices that collect real-time data such as heart rate, facial expression changes, and reaction time. Smartphone cameras may also be used. This data is sent to a server and recorded in a database.

[0193] 5. Data Analysis

[0194] The server integrates the collected skill test answer data and biometric data and performs analysis using a data analysis module, which also uses generative AI models to evaluate the candidate's skills, aptitude, personality, and potential and future prospects.

[0195] Example prompt sentence:

[0196] "Please rate the candidate's skill level based on their answers."

[0197] "Assess the candidate's stress level based on heart rate and facial expression changes."

[0198] 6. Matching

[0199] Finally, the server uses a matching module to compare the evaluation results with the needs of the company and make the best match, which is then notified to the user and the company.

[0200] This system streamlines the hiring process for brick-and-mortar stores and ensures unbiased and fair evaluations.

[0201] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0202] Step 1:

[0203] Users access the system using their smartphones and log in by entering their authentication information (ID and password). The server checks the user's authentication information against the database, and if authentication is successful, displays the user's dashboard screen. The input here is the user's ID and password, and the output is the dashboard screen.

[0204] Step 2:

[0205] When a user clicks the "Start Dialogue" button on the dashboard screen, the server launches the dialogue module. The server uses a generative AI model to generate an initial question (e.g., "Please introduce yourself") and sends it to the user. The input here is the event of pressing the "Start Dialogue" button, and the output is the generated question.

[0206] Step 3:

[0207] The user uses a smartphone to input answers to questions sent from the server. The server receives the answers and stores them in a database. The input here is the user's answer, and the output is the saved answer data.

[0208] Step 4:

[0209] The server presents skill tests and assignments to the user through the dialogue module. The user answers these tests and assignments using their smartphone and sends the answers to the server, which receives them and stores them in a database. The input here is the answers to the skill tests and assignments, and the output is the stored skill assessment data.

[0210] Step 5:

[0211] The user wears a wearable device and uses the smartphone camera to collect biometric data. The collected data includes heart rate, facial expression changes, reaction speed, etc. The device transmits this biometric data to a server in real time. The input here is the collected biometric data, and the output is the data transmitted to the server.

[0212] Step 6:

[0213] The server integrates the collected skill assessment data and biometric data and performs analysis using a data analysis module. This analysis evaluates the candidate's skills, aptitude, and personality. It also evaluates the candidate's potential and future prospects using a generative AI model. The input here is the integrated skill assessment data and biometric data, and the output is the analysis results.

[0214] Step 7:

[0215] The server uses a matching module to compare the analysis results with the company's needs and make the best match. The matching results are notified to the user and the company. The input here is the analysis results and the company's needs, and the output is the matching results.

[0216] 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.

[0217] One embodiment of the present invention is a system for matching candidates with companies in a fairer and more efficient manner. The system incorporates an emotion engine that recognizes the user's emotions and can use emotion data to provide more accurate evaluations.

[0218] 1. User Interface Methods

[0219] Users access the system using a web browser or a dedicated application and log in by entering their ID and password.

[0220] The server checks the user's authentication information against a database, and if authentication is successful, generates a dashboard screen for the user and sends it to the terminal.

[0221] 2. Interaction Module Means

[0222] The device displays a "Start Dialogue" button on the dashboard screen, and when the user clicks it, the AI ​​dialogue module is launched.

[0223] The server generates an initial question for the candidate (e.g., "Please tell us about yourself") and sends it to the terminal.

[0224] 3. Skills Assessment Tools

[0225] The server presents candidates with skill tests and challenges through an interactive module, including programming problems and logic puzzles.

[0226] The user works on the displayed tasks and enters their answers.

[0227] The terminal transmits the user's answer to the server.

[0228] 4. Biometrics Collection Methods

[0229] The device collects biometric data from the user through wearable devices and cameras, including heart rate, facial expression changes, and reaction speed.

[0230] The server receives this data in real time and records it in a database.

[0231] 5. Emotional Engine Means

[0232] The terminal transmits the collected biometric data to the emotion engine.

[0233] The server analyzes the user's emotional state in real time using the emotion engine, and the resulting emotion data is provided to the data analysis means as part of the user's aptitude and personality evaluation.

[0234] 6. Data Analysis Methods

[0235] The server integrates the collected skill test answer data, biometric data, and emotion data provided by the emotion engine, and performs analysis using a data analysis module.

[0236] The data analysis module conducts a comprehensive assessment of the candidate's skills, aptitude, personality, potential and future prospects.

[0237] 7. Matching Methods

[0238] The matching module (server) compares the evaluation results with company job information to make the best match.

[0239] The server generates data for notifying the user and the company of the matching results and transmits the data to the terminal.

[0240] Specific examples

[0241] For example, when a user logs into the system, a dialogue module is launched and the user is asked to introduce themselves. The user then takes a skill test and solves programming problems and logic puzzles. During this time, the device continues to collect the user's heart rate and facial expression changes, and this data is analyzed in real time by the emotion engine. The emotion engine analyzes the user's emotional state (e.g., tension, relaxation) and provides the emotion data to the data analysis means. The data analysis module analyzes this data and performs an overall evaluation of the user. Finally, the matching module compares the evaluation results with the needs of companies and suggests the most suitable company to the user. Through this series of processes, bias-free and objective recruitment is achieved.

[0242] The above is an embodiment of the present invention, which enables companies to efficiently recruit suitable personnel for the long term.

[0243] The processing flow will be explained below.

[0244] Step 1:

[0245] Users access the system using a web browser or a dedicated application and log in by entering their ID and password.

[0246] Step 2:

[0247] The terminal transmits the input authentication information to the server.

[0248] Step 3:

[0249] The server checks the authentication information against a database, and if authentication is successful, generates a dashboard screen for the user and sends it to the terminal.

[0250] Step 4:

[0251] The terminal displays a dashboard screen to the user.

[0252] Step 5:

[0253] The user clicks the "Start conversation" button on the dashboard.

[0254] Step 6:

[0255] The server launches an AI dialogue module, generates an initial question for the candidate, and sends it to the terminal.

[0256] Step 7:

[0257] The terminal displays the initial question sent from the server (e.g., "Please introduce yourself") to the user.

[0258] Step 8:

[0259] The user inputs the answer to the question and sends it to the server via the terminal.

[0260] Step 9:

[0261] The server receives the user's answer, generates the next question or challenge, and sends it to the terminal.

[0262] Step 10:

[0263] The device displays the next question or challenge (e.g., a skills test question) to the user.

[0264] Step 11:

[0265] The user solves the problem and sends the answer to the server via the terminal.

[0266] Step 12:

[0267] The terminal transmits the user's answers to the server, and at the same time collects the user's biometric data (e.g., heart rate, facial expression changes) and transmits it to the server in real time.

[0268] Step 13:

[0269] The server records the received answer data and biometric data in a database.

[0270] Step 14:

[0271] The terminal transmits the collected biometric data to the emotion engine.

[0272] Step 15:

[0273] The emotion engine (server) analyzes the user's emotional state in real time based on biometric data and generates emotion data.

[0274] Step 16:

[0275] The server transmits the emotion data and the answer data of the skill test to the data analysis module.

[0276] Step 17:

[0277] The data analysis module (server) analyzes this data and makes a comprehensive assessment of the candidate's skills, aptitude, personality, potential, and future prospects.

[0278] Step 18:

[0279] The server sends the evaluation results to the matching module.

[0280] Step 19:

[0281] The matching module (server) compares the evaluation results with company job information to make the best match.

[0282] Step 20:

[0283] The server generates data for notifying the user and the company of the matching results and transmits the data to the terminal.

[0284] Step 21:

[0285] The device displays the matching results to the user, and the results are also notified to the company's recruiting staff.

[0286] Example 2

[0287] 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."

[0288] In conventional recruitment systems, matching candidates with companies relied on subjective evaluations, making it difficult to efficiently find the best talent. Furthermore, aptitude assessment based not only on the content of candidates' responses, but also on their emotional state and biometric data was not adequately conducted. Therefore, there was a need for a system that comprehensively evaluates candidates' potential and future prospects, and matches them fairly and efficiently with the needs of companies.

[0289] 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.

[0290] In this invention, the server includes authentication means for verifying authentication information, dialogue means for dialogue with the candidate, ability evaluation means for evaluating the candidate's abilities, biometric information collection means for collecting the candidate's biometric information, information analysis means for analyzing the collected biometric information and the ability evaluation results to evaluate the candidate's aptitude and personality, and matching means for matching the evaluation results with job requirements. This enables bias-free evaluation that eliminates subjectivity and realizes optimal matching between candidates and companies.

[0291] The "authentication means" is a function for verifying the user's authentication information and confirming legitimate access rights.

[0292] "Interaction means" refers to an interface for exchanging information between candidates and the system.

[0293] "Competency assessment tools" are functions for assessing candidates' skills and knowledge.

[0294] "Biometric information collection means" is a function for collecting biometric data such as the candidate's heart rate and facial expression changes.

[0295] "Information analysis means" is a function that integrates collected biometric information with the results of ability assessments to evaluate the suitability and personality of candidates.

[0296] "Matching methods" are functions that use evaluation results to compare candidates with the needs of companies and make optimal matches.

[0297] The present invention relates to a system for matching candidates with companies in a fair and efficient manner. The system incorporates an emotion engine that recognizes the emotions of candidates and can provide more accurate evaluations by utilizing emotion data.

[0298] The system is implemented using the following hardware and software:

[0299] Hardware

[0300] Server: A cloud-based server (e.g., AWS, Google Cloud) can be used. The server includes functions for user authentication, database management, execution of AI dialogue modules, and execution of data analysis.

[0301] Terminal: This refers to a user's PC, tablet, smartphone, etc. The system is accessed through a web browser or dedicated application.

[0302] Wearable device: A device used to collect biometric data about a user (e.g., smartwatch, fitness tracker).

[0303] software

[0304] Sentiment engine: AI tools and libraries for sentiment analysis (e.g., TensorFlow, PyTorch).

[0305] Data Analysis Module: Analysis software for integrating multiple data sets and evaluating candidates.

[0306] Specific operating procedures for the system

[0307] 1. User authentication: A user accesses the system using a web browser or a dedicated app and logs in by entering their ID and password. The server receives this authentication information and compares it with the data stored in the database. If authentication is successful, the user's dashboard screen is generated and sent to the terminal.

[0308] 2. Starting a conversation: The terminal displays a "Start conversation" button on the dashboard screen, and when the user clicks it, the conversation module starts. The server generates an initial question (e.g., "Please introduce yourself") and sends it to the terminal. The terminal displays the received question to the user.

[0309] 3. Skill Assessment: The server presents skill tests and challenges to the user through the dialogue module. The user tackles the problems and enters the answers, which are then sent to the server. The server stores the answers in a database and begins analyzing them as part of the skill assessment.

[0310] 4. Biometric data collection: The terminal collects biometric data such as heart rate, facial expression changes, and reaction speed through the wearable device and camera attached to the user. The server receives this data in real time and records it in a database.

[0311] 5. Emotion Analysis: The terminal sends the collected biometric data to the emotion engine. The server uses the emotion engine to analyze the user's emotional state in real time. The resulting emotion data is provided to the data analysis means as part of the user's aptitude and personality assessment.

[0312] 6. Data integration and analysis: The server integrates the collected skill test answer data, biometric data, and emotional data provided by the emotion engine and records them in a database. The data analysis module comprehensively analyzes this data and performs a subjective evaluation of the candidate, including an evaluation of skills, aptitude, personality, potential, and future prospects.

[0313] 7. Matching: The matching module compares the evaluation results with the company's job information and proposes the most suitable candidates to the company. The server generates data to notify the user and the company of the matching results and sends it to the terminal. The terminal displays the received matching results to the user.

[0314] Examples of concrete examples and prompts

[0315] For example, when a user logs into the system, the dialogue module is activated and the first question displayed is, "Please introduce yourself." The user then attempts skill tests such as programming problems and logic puzzles. In parallel, the device continues to collect the user's heart rate and facial expression changes, and this data is analyzed in real time by the emotion engine. The emotion data is provided to the data analysis means, which performs a comprehensive evaluation. Finally, the matching module compares the needs of companies with the evaluation results and suggests the most suitable companies to the user.

[0316] Example prompt sentence:

[0317] "Please explain the process by which a user logs in and an interaction module is initiated."

[0318] "Please explain with examples how the system works when a user completes a skills test."

[0319] "Please explain how the emotion engine analyzes biometric data and how the results of this analysis are used in the evaluation."

[0320] "Please explain how the matching module uses the assessment results to match with company job openings."

[0321] The above is an embodiment of the present invention, and this system makes it possible to optimally match companies with suitable candidates in a fair and efficient manner.

[0322] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0323] Step 1:

[0324] User authentication: The user accesses the system using a web browser or a dedicated app and logs in by entering their ID and password. The server receives this authentication information and compares it with the authentication information stored in the database. If authentication is successful, the server generates the user's dashboard screen and sends it to the terminal. The terminal displays the dashboard screen received from the server to the user.

[0325] Input: User ID and password

[0326] Data processing: Verification against the server database

[0327] Output: Dashboard screen

[0328] Step 2:

[0329] Activating the dialogue module: The terminal displays a "Start dialogue" button on the dashboard screen. When the user clicks the "Start dialogue" button, the server's dialogue module is activated, which generates the first question (e.g., "Please introduce yourself") and sends it to the terminal. The terminal then displays the received question to the user.

[0330] Input: User clicks

[0331] Data processing: The server generates the initial question

[0332] Output: Question

[0333] Step 3:

[0334] Skill assessment: The server presents skill tests and challenges (e.g., programming problems, logic puzzles) to the user through the dialogue module. The user works on the challenges and enters their answers. The device sends the user's answers to the server. The server stores the received answers in a database and begins analyzing them as part of the skill assessment.

[0335] Input: User's answer

[0336] Data processing: The server evaluates the answers

[0337] Output: Evaluation result

[0338] Step 4:

[0339] Biometric data collection: The terminal collects biometric data such as heart rate, facial expression changes, and reaction speed through a wearable device or camera attached to the user. The server receives this data in real time and records it in a database.

[0340] Input: Data from wearable devices and cameras

[0341] Data processing: The server records the data

[0342] Output: Recorded biometric data

[0343] Step 5:

[0344] Emotion analysis: The terminal sends the collected biometric data to the emotion engine on the server. The server uses the emotion engine to analyze the user's emotional state (e.g., tension, relaxation). The resulting emotion data is provided to the data analysis means as part of the user's aptitude and personality assessment.

[0345] Input: Biometric data

[0346] Data processing: Data analysis using emotion engines

[0347] Output: Emotion data

[0348] Step 6:

[0349] Data integration and analysis: The server integrates the collected skill test answer data, biometric data, and emotion data provided by the emotion engine, and records them in a database. The data analysis module comprehensively analyzes this data and makes a comprehensive evaluation of the candidate's skills, aptitude, personality, potential, and future prospects.

[0350] Input: Skill test answer data, biometric data, emotion data

[0351] Data processing: Comprehensive data analysis

[0352] Output: Overall evaluation result

[0353] Step 7:

[0354] Matching: The server's matching module compares the evaluation results with the company's job information to make the best match. The server generates data to notify the user and the company of the matching results and sends it to the device. The device then displays the received matching results to the user.

[0355] Input: Overall evaluation results, company job information

[0356] Data processing: Matching algorithm

[0357] Output: Matching results

[0358] Through these steps, a fair and efficient matching system will be realized, which will enable optimal matching between companies and suitable candidates.

[0359] (Application example 2)

[0360] 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."

[0361] Traditional candidate-to-company matching systems rely on superficial skills and resume information, failing to fully grasp a candidate's emotional state, aptitude, or personality. Furthermore, it's difficult to assess a candidate's potential through skill assessment alone, making it difficult to find the best candidate who best meets a company's needs. Furthermore, candidate authentication and dialogue based on fixed questions fail to capture the candidate's true character, potentially resulting in mismatches.

[0362] 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.

[0363] In this invention, the server includes a dialogue module means for dialogue with candidates, a skill assessment means for assessing the candidates' skills, a biometrics collection means for collecting the candidates' biometric data, a data analysis means for analyzing the collected biometric data and the skill assessment results to assess the candidates' aptitude and personality, a matching means for matching the assessment results with the company's needs, and an emotion engine means for analyzing the collected biometric data in real time and assessing the candidates' emotional state. This enables real-time assessment of the candidates' emotional state and aptitude, enabling more appropriate and efficient matching. Furthermore, by using a generative model means, it is possible to evaluate the candidates' potential and future potential and find talent that is suitable for the company in the long term. Furthermore, a dialogue generation means is used to generate prompt sentences, allowing the candidate's true character to be captured through more personalized dialogue.

[0364] The "interaction module means" is a means for providing an interface and functionality for a candidate to interact with the system.

[0365] A "skills assessment instrument" is an instrument that has the means and function to assess a candidate's technical and professional competence.

[0366] "Biometrics collection means" refers to means including devices and technologies for collecting biometric information such as a candidate's heart rate and facial expression changes.

[0367] "Data analysis means" refers to means having algorithms and functions for analyzing collected biometric data and skill assessment results and evaluating the aptitude and personality of candidates.

[0368] A "matching tool" is a tool that has the method and function to compare the evaluation results with the needs of the company and select the most suitable candidate.

[0369] "Emotion engine means" means means having algorithms and techniques for analyzing collected biometric data in real time and assessing the emotional state of a candidate.

[0370] A "generative modeling tool" is a tool that uses generative artificial intelligence (AI) to assess a candidate's potential and future prospects.

[0371] "User Interface Means" means means for obtaining candidate authentication information and providing an interface for enabling access and operation of the system.

[0372] A "dialogue generation means" is a means having a language model and technology for generating appropriate questions and responses when a candidate and the system interact.

[0373] The present invention provides a system for matching candidates with companies more fairly and efficiently, which includes a dialogue module, a skill assessment means, a biometrics collection means, a data analysis means, a matching means, an emotion engine means, a generative model means, a user interface means, and a dialogue generation means.

[0374] System Program

[0375] 1. Log in and create a dashboard

[0376] The user logs in using a smartphone app or smart glasses with an ID and password. The server checks the authentication information against a database, and if authentication is successful, a dashboard screen is generated and sent to the user's device.

[0377] 2. Starting a dialogue

[0378] When the user taps the "Start Dialogue" button on the dashboard screen, the server starts the dialogue module means, generates an initial question, and sends it to the user. For example, a prompt such as "Please introduce yourself" is presented.

[0379] 3. Skills Assessment and Biometrics Collection

[0380] The server uses the skill assessment tool to present skill tests and tasks (e.g., programming problems and logic puzzles) to the candidates, while collecting biometric data (e.g., heart rate, facial expression changes) from the user's device (e.g., smart glasses or smartphone camera).

[0381] 4. Analysis by Emotion Engine

[0382] The collected biometric data is transmitted in real time to an emotion engine means, which analyzes the candidate's emotional state (e.g., nervous, relaxed) and provides the results to a data analysis means.

[0383] 5. Data analysis and matching

[0384] The server integrates the skill assessment results, biometric data, and emotional data, and uses data analysis means to evaluate the candidate's aptitude and personality. The assessment results are compared with the company's needs by a matching means to find the optimal match. The results are then notified to the user and the company.

[0385] Hardware and Software

[0386] Hardware:

[0387] Smartphone (e.g. iPhone, Android)

[0388] Smart glasses (e.g. Google Glass)

[0389] Wearable devices (e.g., Apple Watch)

[0390] software:

[0391] Frontend: React Native (smartphone app), WebRTC (video calling)

[0392] Backend: Node.js, Express.js

[0393] Database: MongoDB

[0394] Emotion engine: Affectiva SDK

[0395] Data analysis: Python (numpy, pandas, scikit-learn)

[0396] Examples and prompts

[0397] Specific examples

[0398] For example, when a user logs in and starts an interactive module, the following prompt is displayed:

[0399] "Please introduce yourself."

[0400] Please solve the following programming problems.

[0401] "Are you nervous? Just relax a bit."

[0402] While the user inputs and performs operations according to these prompts, the device collects the user's biometric information, which is then analyzed by the server in real time. This allows for a more comprehensive and accurate evaluation, and the results are used to match the user with the appropriate company.

[0403] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0404] Processing step details

[0405] Step 1:

[0406] The user enters their ID and password using a smartphone app or smart glasses to access the login screen. The server checks the authentication information against the database. The ID and password are required as input, and if authentication is successful by checking these data, the server generates a dashboard screen and sends it to the terminal. The dashboard screen is displayed to the user as output.

[0407] Step 2:

[0408] The user taps the "Start Dialogue" button on the dashboard screen. This causes the server to start the dialogue module means, generate the first question, and send it. The user's operation is input, and the server outputs the generated prompt sentence "Please introduce yourself," and displays it on the terminal.

[0409] Step 3:

[0410] The server uses the skill assessment means to present skill tests and tasks to candidates. As input, the server receives the information and requests provided by the user in the dialogue, and as output, it generates skill tests such as programming problems and logic puzzles and sends them to the terminal. The user works on these and enters the answers into the terminal.

[0411] Step 4:

[0412] While the user is taking the skill test, the device collects biometric data through a biometric collection means. For example, it uses smart glasses or a smartphone camera to monitor heart rate and facial expression changes. The input is real-time data from the camera or sensor, and the output is sent to a server.

[0413] Step 5:

[0414] The server sends the collected biometric data to the emotion engine means for real-time analysis. The input includes biometric information such as heart rate and facial expression changes, and the emotion engine analyzes the user's emotional state based on this data. The output is an analysis result (e.g., tension, relaxation).

[0415] Step 6:

[0416] The server integrates the analysis results from the emotion engine means, the answer data of the skill test, and the biometric data, and evaluates the aptitude and personality of the candidate using the data analysis means. All of these data are integrated as input, and a comprehensive evaluation result is generated as output.

[0417] Step 7:

[0418] The server assesses the candidate's potential and future potential using generative modeling tools, with the integrated data and generative AI model as inputs and a long-term candidate suitability assessment as output.

[0419] Step 8:

[0420] The server uses a matching method to compare the evaluation results with the needs of the company and perform optimal matching. The inputs are the candidate's overall evaluation results and the company's job information, and the output is a list of optimal candidates that is notified to the user and the company.

[0421] By following these steps, we can evaluate the candidate's emotional state and aptitude in real time, enabling more appropriate and efficient matching. Furthermore, by using generative models, we can evaluate the candidate's potential and future prospects and find the right fit for the company in the long term. Furthermore, by using dialogue generation, we can generate prompts to capture the candidate's true personality through more personalized dialogue.

[0422] 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.

[0423] 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.

[0424] 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.

[0425] [Second embodiment]

[0426] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0427] 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.

[0428] 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).

[0429] 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.

[0430] 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.

[0431] 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).

[0432] 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.

[0433] 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.

[0434] 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.

[0435] 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.

[0436] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0437] 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."

[0438] An embodiment of the present invention is a system for matching candidates with companies in a fairer and more efficient manner. This system includes the following elements.

[0439] 1. User Interface Methods

[0440] Users access the system using a web browser or a dedicated application and log in by entering their authentication information (ID and password).

[0441] The server checks the user's authentication information against a database, and if authentication is successful, displays the user's dashboard screen.

[0442] 2. Interaction Module Means

[0443] The device displays a "Start Dialogue" button on the dashboard screen, and when the user clicks it, the AI ​​dialogue module is launched.

[0444] The server sends the candidate an initial question (e.g., "Please tell us about yourself") and receives the user's answer.

[0445] 3. Skills Assessment Tools

[0446] The server presents candidates with skill tests and challenges through an interactive module, including programming problems and logic puzzles.

[0447] The user works on the displayed tasks and enters their answers.

[0448] The terminal transmits the user's answer to the server.

[0449] 4. Biometrics Collection Methods

[0450] The device collects biometric data from the user through wearable devices and cameras, including heart rate, facial expression changes, and reaction speed.

[0451] The server receives this data in real time and records it in a database.

[0452] 5. Data Analysis Methods

[0453] The server integrates the collected skill test answer data and biometric data and performs analysis using a data analysis module.

[0454] The data analysis module assesses candidates' skills, aptitudes, and personality, records the results, and also uses generative artificial intelligence (AI) to assess their potential and future prospects.

[0455] 6. Matching Methods

[0456] The matching module (server) compares the candidate evaluation results with the company's job information to make the best match.

[0457] The server notifies the user and the company of the matching results.

[0458] Specific examples

[0459] For example, when a user logs into the system, a dialogue module is launched and they are asked to introduce themselves. The user then takes a skill test and solves programming problems and logic puzzles. During this time, the device continues to collect the user's heart rate and facial expression changes. The data analysis module analyzes this data and provides an overall evaluation of the user. Finally, the matching module compares the evaluation results with the needs of companies and suggests the most suitable company to the user. This series of processes ensures bias-free and objective recruitment.

[0460] The above is an embodiment of the present invention, which enables companies to efficiently recruit suitable personnel for the long term.

[0461] The processing flow will be explained below.

[0462] Step 1:

[0463] Users access the system using a web browser or a dedicated application and log in by entering their ID and password.

[0464] Step 2:

[0465] The terminal transmits the input authentication information to the server.

[0466] Step 3:

[0467] The server checks the authentication information against a database, and if authentication is successful, generates a dashboard screen for the user and sends it to the terminal.

[0468] Step 4:

[0469] The terminal displays a dashboard screen to the user.

[0470] Step 5:

[0471] The user clicks the "Start conversation" button on the dashboard.

[0472] Step 6:

[0473] The server launches an AI dialogue module, generates an initial question for the candidate, and sends it to the terminal.

[0474] Step 7:

[0475] The terminal displays the initial question sent from the server (e.g., "Please introduce yourself") to the user.

[0476] Step 8:

[0477] The user inputs the answer to the question and sends it to the server via the terminal.

[0478] Step 9:

[0479] The server receives the user's answer, generates the next question or challenge, and sends it to the terminal.

[0480] Step 10:

[0481] The device displays the next question or challenge (e.g., a skills test question) to the user.

[0482] Step 11:

[0483] The user solves the problem and sends the answer to the server via the terminal.

[0484] Step 12:

[0485] The terminal transmits the user's answers to the server, and at the same time collects the user's biometric data (e.g., heart rate, facial expression changes) and transmits it to the server in real time.

[0486] Step 13:

[0487] The server records the received answer data and biometric data in a database.

[0488] Step 14:

[0489] The data analysis module (server) analyzes this data and makes a comprehensive assessment of the candidate's skills, aptitude, personality, potential, and future prospects.

[0490] Step 15:

[0491] The server generates and sends the evaluation results to the matching module.

[0492] Step 16:

[0493] The matching module (server) compares the evaluation results with company job information to make the best match.

[0494] Step 17:

[0495] The server generates data for notifying the user and the company of the matching results and transmits the data to the terminal.

[0496] Step 18:

[0497] The device displays the matching results to the user, and the results are also notified to the company's recruiting staff.

[0498] Example 1

[0499] 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."

[0500] In the modern recruitment process, matching between candidates and companies is often influenced by subjective factors, making it difficult to achieve fair and efficient matching. Furthermore, there is a need to evaluate not only candidates' skills and aptitude, but also their potential and future prospects. Current technology lacks a system that can comprehensively evaluate these factors and achieve optimal matching, so this problem needs to be solved.

[0501] 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.

[0502] In this invention, the server includes a user interface means, a dialogue module means for dialogue with candidates, a skill evaluation means for evaluating the skills of the candidates, a biometrics collection means for collecting biometric data of the candidates, a data analysis means for analyzing the collected biometric data and the skill evaluation results to evaluate the aptitude and personality of the candidates, and a matching means for matching the evaluation results with the needs of companies, thereby enabling fair and efficient matching of candidates and companies.

[0503] The "user interface means" is a means by which a user accesses the system, inputs authentication information, and performs various operations via the dashboard screen.

[0504] The "dialogue module means" is a module for dialogue with candidates, and is a means for presenting initial questions and skill test tasks and collecting responses from candidates.

[0505] A "skill assessment means" is a means for assessing the skills of a candidate, and is a means for presenting tasks such as programming problems and logic puzzles and accepting the candidate's answers.

[0506] "Biometrics collection means" means a means for collecting biometric data such as a candidate's heart rate, facial expression changes, reaction speed, etc. This includes wearable devices and cameras.

[0507] "Data Analysis Means" refers to means for integrating collected biometric data and skill assessment results to evaluate a candidate's aptitude and personality, including a data analysis module and a generative AI model.

[0508] "Matching methods" are methods for comparing candidate evaluation results with the needs of the company to achieve optimal matching. Based on the evaluation results, the company proposes the most suitable candidate.

[0509] A "generative artificial intelligence (AI) means" is a means that uses AI technology to assess a candidate's potential and future prospects.

[0510] An embodiment of the present invention is a system for matching candidates with companies in a fairer and more efficient manner. This system includes the following elements.

[0511] 1. User Interface Methods

[0512] A user accesses the system using a web browser or a dedicated application and enters authentication information (ID and password) to log in. The server checks the user's authentication information against a database (e.g., MySQL database), and if authentication is successful, displays the user's dashboard screen.

[0513] 2. Interaction Module Means

[0514] The terminal displays a "Start Dialogue" button on the dashboard screen, and when the user clicks it, the AI ​​dialogue module is launched. The server sends the first question to the candidate (e.g., "Please introduce yourself") and receives the user's answer.

[0515] 3. Skills Assessment Tools

[0516] The server presents skill tests and challenges to the candidate through the dialogue module, such as programming problems and logic puzzles. The user works through the challenges displayed and enters their answers. The terminal then transmits the user's answers to the server.

[0517] 4. Biometrics Collection Methods

[0518] The terminal collects biometric data from the user through a wearable device or camera, including heart rate, facial expression changes, reaction speed, etc. The server receives this data in real time and records it in a database.

[0519] 5. Data Analysis Methods

[0520] The server integrates the collected skill test answer data and biometric data and analyzes them using a data analysis module. The data analysis module evaluates the candidate's skills, aptitude, and personality, and records the evaluation results. It also evaluates the candidate's potential and future prospects using generative artificial intelligence (AI) methods. This data analysis module can be implemented using Python and the scikit-learn library.

[0521] 6. Matching Methods

[0522] The matching module (server) compares the candidate's evaluation results with the company's job information to find the best match. The server then notifies the user and the company of the matching results. Notification can be via email or in-system messages.

[0523] Specific examples

[0524] For example, when a user logs into the system, the server displays a dashboard screen after authentication. The terminal then displays a "Start Dialogue" button, and when the user clicks it, the server sends a message saying, "Please introduce yourself." When the user enters their answers to a skill test, the data is sent to the server. The terminal also collects the user's real-time biometric data and sends it to the server. Finally, the server analyzes this data, performs optimal matching with companies, and notifies the user and company of the results.

[0525] Prompt Sentence Examples

[0526] "Please introduce yourself."

[0527] "Solve a programming problem. Example: Predict the output of the following code."

[0528] "Please relax as we will be recording your heart rate and facial expressions."

[0529] The above is an embodiment of the present invention, which realizes fair and efficient matching between candidates and companies. Furthermore, the various means included in the system work in conjunction with each other to provide highly accurate evaluation and optimal matching.

[0530] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0531] Step 1:

[0532] A user accesses the system using a web browser or a dedicated application. As input, the user enters an ID and password and attempts to log in to the system. As output, an authentication request is generated and sent to the server.

[0533] Step 2:

[0534] The server compares the received authentication information with the information stored in a database (for example, a MySQL database). This process involves searching the database for the relevant user information and verifying that it matches the entered ID and password. The output is an authentication result (success or failure).

[0535] Step 3:

[0536] If authentication is successful, the server displays the user's dashboard screen. If there is an error message, it notifies the user. The server makes a decision based on the authentication result as input, and generates the next screen information to be displayed as output.

[0537] Step 4:

[0538] The terminal displays a "Start Interaction" button on the dashboard screen. The configuration information of the dashboard screen is read as input, and the "Start Interaction" button is displayed on the user interface as output.

[0539] Step 5:

[0540] The user clicks the "Start Interaction" button, which generates a click event as input and sends a request to the server to start an interaction as output.

[0541] Step 6:

[0542] The server starts the AI ​​dialogue module and sends the first question (e.g., "Please introduce yourself") to the user. It receives a click event as input and generates a prompt sentence as output, which is sent to the user's device.

[0543] Step 7:

[0544] The user answers the first question by entering the answer text as input, and the answer is sent to the server as output.

[0545] Step 8:

[0546] The server records the received answers in a database. It receives the candidate's answer data as input and generates a request to save the answer contents in a database as output.

[0547] Step 9:

[0548] The server presents the candidate with the next skill test or challenge through a dialogue module, which can include programming questions, logic puzzles, etc. It receives triggers from previous answers as input and generates the next challenge as output, which it then sends to the user.

[0549] Step 10:

[0550] The user works on the displayed assignment and inputs the answer. The assignment content is read as input, and the answer is generated as output and sent to the server.

[0551] Step 11:

[0552] The terminal sends the user's answer to the server, which takes the answer data as input and generates a request to send it as output.

[0553] Step 12:

[0554] The terminal collects biometric data through a wearable device or camera attached to the user, including heart rate, facial expression changes, reaction speed, etc. It receives sensor data as input and transmits it to a server in real time as output.

[0555] Step 13:

[0556] The server receives the collected biometric data in real time and records it in a database. It receives the biometric data stream as input and generates a request to store the data in a database as output.

[0557] Step 14:

[0558] The server integrates the collected skill test answer data and biometric data and performs analysis using a data analysis module. It reads the integrated data as input and generates evaluation results as output.

[0559] Step 15:

[0560] The data analysis module evaluates the candidate's skills, aptitude, and personality, and records the evaluation results. Furthermore, it uses a generative AI model to evaluate the candidate's potential and future prospects. Each piece of data is analyzed as input, and a comprehensive evaluation result is generated as output.

[0561] Step 16:

[0562] The matching module (server) compares the candidate evaluation results with the company's job information to make the best match. It receives the evaluation results and the company's needs as input, and generates and notifies the matching results as output.

[0563] Step 17:

[0564] The server notifies users and companies of the matching results via email or internal system messages. Based on the matching results as input, notifications are generated and sent as output.

[0565] Through the above processing steps, the present invention achieves fair and efficient matching between candidates and companies.

[0566] (Application example 1)

[0567] 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."

[0568] Traditional staff recruitment and evaluation processes in brick-and-mortar stores require a lot of time and effort, and are prone to subjective bias. Furthermore, it is often difficult to accurately assess candidates' skills and aptitude, making it difficult to efficiently hire the best talent. Furthermore, traditional methods make it difficult to utilize biometric data, such as a candidate's stress level or reaction speed.

[0569] 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.

[0570] In this invention, the server includes a dialogue module means for dialogue with candidates, a skill evaluation means for evaluating the skills of the candidates, a biometrics collection means for collecting biometric data of the candidates, a data analysis means for analyzing the collected biometric data and the skill evaluation results and evaluating the aptitude and personality of the candidates, a matching means for matching the evaluation results with the needs of the company, a means for streamlining the staff recruitment and evaluation process for the brick-and-mortar store, a means for collecting biometric data using a smartphone camera or a wearable device, and a means for collecting input from the candidates and providing a user interface. This enables an integrated evaluation of the skills and biometric data of candidates and enables efficient and fair hiring of the best talent.

[0571] An "interaction module" is a component that interacts with candidates, generates questions, and collects answers.

[0572] A "skills assessment tool" is a tool that presents tests or tasks to assess candidates' skills and collects the results.

[0573] "Biometrics collection means" refers to a device or system that collects biometric data such as a candidate's heart rate, facial expression changes, and reaction speed.

[0574] The "data analysis means" is a module that integrates the collected biometric data with the skill assessment results to evaluate the candidate's aptitude and personality.

[0575] A "matching method" is a system that compares the candidate evaluation results with the company's needs to make the optimal match.

[0576] "Means for streamlining the staff recruitment and evaluation process for brick-and-mortar stores" refers to tools and systems that automate and streamline the traditional staff recruitment and evaluation process.

[0577] "Means for collecting biometric data using a smartphone camera or a wearable device" refers to means for collecting biometric information such as heart rate, facial expression changes, and reaction speed using a smartphone camera or a wearable device.

[0578] The "means for providing a user interface" is a component that provides an interface for candidates to log in to the system and use various functions.

[0579] This invention is a system for making the staff recruitment and evaluation process in a brick-and-mortar store more efficient and fair. Below, we will explain in detail the program and processing method for realizing this system.

[0580] The server includes a dialogue module, a skill assessment unit, a biometrics collection unit, a data analysis unit, and a matching unit, which enable an integrated assessment of a candidate's skills and biometric data, thereby enabling efficient and fair recruitment of the most suitable personnel.

[0581] Hardware and software used

[0582] Smartphones: Use cameras and touchscreens to gather user input.

[0583] Wearable devices: Used to collect biometric data such as heart rate, facial expression changes, and reaction speed.

[0584] Server: Candidate data management and analysis is performed using the Django framework.

[0585] Client-side software: Building the user interface using React.

[0586] Processing Description

[0587] 1. Authentication and Login

[0588] Users access the system using their smartphones and enter their authentication information (ID and password) to log in. The server compares this information with the database, and if authentication is successful, displays the user's dashboard screen.

[0589] 2. Starting the dialogue module

[0590] When a user clicks the "Start Dialogue" button on the dashboard screen, the dialogue module is launched. The server uses the generative AI model to generate an initial question (e.g., "Please introduce yourself") and sends it to the user.

[0591] Example prompt sentence:

[0592] "Generate the best questions for candidates to introduce themselves."

[0593] 3. Skills Assessment

[0594] Through the dialogue module, the server presents the candidate with skill tests and assignments. The user enters their answers using their smartphone, and this data is sent to the server, which stores the data and prepares it for analysis.

[0595] 4. Biometric Data Collection

[0596] Candidates wear wearable devices that collect real-time data such as heart rate, facial expression changes, and reaction time. Smartphone cameras may also be used. This data is sent to a server and recorded in a database.

[0597] 5. Data Analysis

[0598] The server integrates the collected skill test answer data and biometric data and performs analysis using a data analysis module, which also uses generative AI models to evaluate the candidate's skills, aptitude, personality, and potential and future prospects.

[0599] Example prompt sentence:

[0600] "Please rate the candidate's skill level based on their answers."

[0601] "Assess the candidate's stress level based on heart rate and facial expression changes."

[0602] 6. Matching

[0603] Finally, the server uses a matching module to compare the evaluation results with the needs of the company and make the best match, which is then notified to the user and the company.

[0604] This system streamlines the hiring process for brick-and-mortar stores and ensures unbiased and fair evaluations.

[0605] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0606] Step 1:

[0607] Users access the system using their smartphones and log in by entering their authentication information (ID and password). The server checks the user's authentication information against the database, and if authentication is successful, displays the user's dashboard screen. The input here is the user's ID and password, and the output is the dashboard screen.

[0608] Step 2:

[0609] When a user clicks the "Start Dialogue" button on the dashboard screen, the server launches the dialogue module. The server uses a generative AI model to generate an initial question (e.g., "Please introduce yourself") and sends it to the user. The input here is the event of pressing the "Start Dialogue" button, and the output is the generated question.

[0610] Step 3:

[0611] The user uses a smartphone to input answers to questions sent from the server. The server receives the answers and stores them in a database. The input here is the user's answer, and the output is the saved answer data.

[0612] Step 4:

[0613] The server presents skill tests and assignments to the user through the dialogue module. The user answers these tests and assignments using their smartphone and sends the answers to the server, which receives them and stores them in a database. The input here is the answers to the skill tests and assignments, and the output is the stored skill assessment data.

[0614] Step 5:

[0615] The user wears a wearable device and uses the smartphone camera to collect biometric data. The collected data includes heart rate, facial expression changes, reaction speed, etc. The device transmits this biometric data to a server in real time. The input here is the collected biometric data, and the output is the data transmitted to the server.

[0616] Step 6:

[0617] The server integrates the collected skill assessment data and biometric data and performs analysis using a data analysis module. This analysis evaluates the candidate's skills, aptitude, and personality. It also evaluates the candidate's potential and future prospects using a generative AI model. The input here is the integrated skill assessment data and biometric data, and the output is the analysis results.

[0618] Step 7:

[0619] The server uses a matching module to compare the analysis results with the company's needs and make the best match. The matching results are notified to the user and the company. The input here is the analysis results and the company's needs, and the output is the matching results.

[0620] 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.

[0621] One embodiment of the present invention is a system for matching candidates with companies in a fairer and more efficient manner. The system incorporates an emotion engine that recognizes the user's emotions and can use emotion data to provide more accurate evaluations.

[0622] 1. User Interface Methods

[0623] Users access the system using a web browser or a dedicated application and log in by entering their ID and password.

[0624] The server checks the user's authentication information against a database, and if authentication is successful, generates a dashboard screen for the user and sends it to the terminal.

[0625] 2. Interaction Module Means

[0626] The device displays a "Start Dialogue" button on the dashboard screen, and when the user clicks it, the AI ​​dialogue module is launched.

[0627] The server generates an initial question for the candidate (e.g., "Please tell us about yourself") and sends it to the terminal.

[0628] 3. Skills Assessment Tools

[0629] The server presents candidates with skill tests and challenges through an interactive module, including programming problems and logic puzzles.

[0630] The user works on the displayed tasks and enters their answers.

[0631] The terminal transmits the user's answer to the server.

[0632] 4. Biometrics Collection Methods

[0633] The device collects biometric data from the user through wearable devices and cameras, including heart rate, facial expression changes, and reaction speed.

[0634] The server receives this data in real time and records it in a database.

[0635] 5. Emotional Engine Means

[0636] The terminal transmits the collected biometric data to the emotion engine.

[0637] The server analyzes the user's emotional state in real time using the emotion engine, and the resulting emotion data is provided to the data analysis means as part of the user's aptitude and personality evaluation.

[0638] 6. Data Analysis Methods

[0639] The server integrates the collected skill test answer data, biometric data, and emotion data provided by the emotion engine, and performs analysis using a data analysis module.

[0640] The data analysis module conducts a comprehensive assessment of the candidate's skills, aptitude, personality, potential and future prospects.

[0641] 7. Matching Methods

[0642] The matching module (server) compares the evaluation results with company job information to make the best match.

[0643] The server generates data for notifying the user and the company of the matching results and transmits the data to the terminal.

[0644] Specific examples

[0645] For example, when a user logs into the system, a dialogue module is launched and the user is asked to introduce themselves. The user then takes a skill test and solves programming problems and logic puzzles. During this time, the device continues to collect the user's heart rate and facial expression changes, and this data is analyzed in real time by the emotion engine. The emotion engine analyzes the user's emotional state (e.g., tension, relaxation) and provides the emotion data to the data analysis means. The data analysis module analyzes this data and performs an overall evaluation of the user. Finally, the matching module compares the evaluation results with the needs of companies and suggests the most suitable company to the user. Through this series of processes, bias-free and objective recruitment is achieved.

[0646] The above is an embodiment of the present invention, which enables companies to efficiently recruit suitable personnel for the long term.

[0647] The processing flow will be explained below.

[0648] Step 1:

[0649] Users access the system using a web browser or a dedicated application and log in by entering their ID and password.

[0650] Step 2:

[0651] The terminal transmits the input authentication information to the server.

[0652] Step 3:

[0653] The server checks the authentication information against a database, and if authentication is successful, generates a dashboard screen for the user and sends it to the terminal.

[0654] Step 4:

[0655] The terminal displays a dashboard screen to the user.

[0656] Step 5:

[0657] The user clicks the "Start conversation" button on the dashboard.

[0658] Step 6:

[0659] The server launches an AI dialogue module, generates an initial question for the candidate, and sends it to the terminal.

[0660] Step 7:

[0661] The terminal displays the initial question sent from the server (e.g., "Please introduce yourself") to the user.

[0662] Step 8:

[0663] The user inputs the answer to the question and sends it to the server via the terminal.

[0664] Step 9:

[0665] The server receives the user's answer, generates the next question or challenge, and sends it to the terminal.

[0666] Step 10:

[0667] The device displays the next question or challenge (e.g., a skills test question) to the user.

[0668] Step 11:

[0669] The user solves the problem and sends the answer to the server via the terminal.

[0670] Step 12:

[0671] The terminal transmits the user's answers to the server, and at the same time collects the user's biometric data (e.g., heart rate, facial expression changes) and transmits it to the server in real time.

[0672] Step 13:

[0673] The server records the received answer data and biometric data in a database.

[0674] Step 14:

[0675] The terminal transmits the collected biometric data to the emotion engine.

[0676] Step 15:

[0677] The emotion engine (server) analyzes the user's emotional state in real time based on biometric data and generates emotion data.

[0678] Step 16:

[0679] The server transmits the emotion data and the answer data of the skill test to the data analysis module.

[0680] Step 17:

[0681] The data analysis module (server) analyzes this data and makes a comprehensive assessment of the candidate's skills, aptitude, personality, potential, and future prospects.

[0682] Step 18:

[0683] The server sends the evaluation results to the matching module.

[0684] Step 19:

[0685] The matching module (server) compares the evaluation results with company job information to make the best match.

[0686] Step 20:

[0687] The server generates data for notifying the user and the company of the matching results and transmits the data to the terminal.

[0688] Step 21:

[0689] The device displays the matching results to the user, and the results are also notified to the company's recruiting staff.

[0690] Example 2

[0691] 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."

[0692] In conventional recruitment systems, matching candidates with companies relied on subjective evaluations, making it difficult to efficiently find the best talent. Furthermore, aptitude assessment based not only on the content of candidates' responses, but also on their emotional state and biometric data was not adequately conducted. Therefore, there was a need for a system that comprehensively evaluates candidates' potential and future prospects, and matches them fairly and efficiently with the needs of companies.

[0693] 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.

[0694] In this invention, the server includes authentication means for verifying authentication information, dialogue means for dialogue with the candidate, ability evaluation means for evaluating the candidate's abilities, biometric information collection means for collecting the candidate's biometric information, information analysis means for analyzing the collected biometric information and the ability evaluation results to evaluate the candidate's aptitude and personality, and matching means for matching the evaluation results with job requirements. This enables bias-free evaluation that eliminates subjectivity and realizes optimal matching between candidates and companies.

[0695] The "authentication means" is a function for verifying the user's authentication information and confirming legitimate access rights.

[0696] "Interaction means" refers to an interface for exchanging information between candidates and the system.

[0697] "Competency assessment tools" are functions for assessing candidates' skills and knowledge.

[0698] "Biometric information collection means" is a function for collecting biometric data such as the candidate's heart rate and facial expression changes.

[0699] "Information analysis means" is a function that integrates collected biometric information with the results of ability assessments to evaluate the suitability and personality of candidates.

[0700] "Matching methods" are functions that use evaluation results to compare candidates with the needs of companies and make optimal matches.

[0701] The present invention relates to a system for matching candidates with companies in a fair and efficient manner. The system incorporates an emotion engine that recognizes the emotions of candidates and can provide more accurate evaluations by utilizing emotion data.

[0702] The system is implemented using the following hardware and software:

[0703] Hardware

[0704] Server: A cloud-based server (e.g., AWS, Google Cloud) can be used. The server includes functions for user authentication, database management, execution of AI dialogue modules, and execution of data analysis.

[0705] Terminal: This refers to a user's PC, tablet, smartphone, etc. The system is accessed through a web browser or dedicated application.

[0706] Wearable device: A device used to collect biometric data about a user (e.g., smartwatch, fitness tracker).

[0707] software

[0708] Sentiment engine: AI tools and libraries for sentiment analysis (e.g., TensorFlow, PyTorch).

[0709] Data Analysis Module: Analysis software for integrating multiple data sets and evaluating candidates.

[0710] Specific operating procedures for the system

[0711] 1. User authentication: A user accesses the system using a web browser or a dedicated app and logs in by entering their ID and password. The server receives this authentication information and compares it with the data stored in the database. If authentication is successful, the user's dashboard screen is generated and sent to the terminal.

[0712] 2. Starting a conversation: The terminal displays a "Start conversation" button on the dashboard screen, and when the user clicks it, the conversation module starts. The server generates an initial question (e.g., "Please introduce yourself") and sends it to the terminal. The terminal displays the received question to the user.

[0713] 3. Skill Assessment: The server presents skill tests and challenges to the user through the dialogue module. The user tackles the problems and enters the answers, which are then sent to the server. The server stores the answers in a database and begins analyzing them as part of the skill assessment.

[0714] 4. Biometric data collection: The terminal collects biometric data such as heart rate, facial expression changes, and reaction speed through the wearable device and camera attached to the user. The server receives this data in real time and records it in a database.

[0715] 5. Emotion Analysis: The terminal sends the collected biometric data to the emotion engine. The server uses the emotion engine to analyze the user's emotional state in real time. The resulting emotion data is provided to the data analysis means as part of the user's aptitude and personality assessment.

[0716] 6. Data integration and analysis: The server integrates the collected skill test answer data, biometric data, and emotional data provided by the emotion engine and records them in a database. The data analysis module comprehensively analyzes this data and performs a subjective evaluation of the candidate, including an evaluation of skills, aptitude, personality, potential, and future prospects.

[0717] 7. Matching: The matching module compares the evaluation results with the company's job information and proposes the most suitable candidates to the company. The server generates data to notify the user and the company of the matching results and sends it to the terminal. The terminal displays the received matching results to the user.

[0718] Examples of concrete examples and prompts

[0719] For example, when a user logs into the system, the dialogue module is activated and the first question displayed is, "Please introduce yourself." The user then attempts skill tests such as programming problems and logic puzzles. In parallel, the device continues to collect the user's heart rate and facial expression changes, and this data is analyzed in real time by the emotion engine. The emotion data is provided to the data analysis means, which performs a comprehensive evaluation. Finally, the matching module compares the needs of companies with the evaluation results and suggests the most suitable companies to the user.

[0720] Example prompt sentence:

[0721] "Please explain the process by which a user logs in and an interaction module is initiated."

[0722] "Please explain with examples how the system works when a user completes a skills test."

[0723] "Please explain how the emotion engine analyzes biometric data and how the results of this analysis are used in the evaluation."

[0724] "Please explain how the matching module uses the assessment results to match with company job openings."

[0725] The above is an embodiment of the present invention, and this system makes it possible to optimally match companies with suitable candidates in a fair and efficient manner.

[0726] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0727] Step 1:

[0728] User authentication: The user accesses the system using a web browser or a dedicated app and logs in by entering their ID and password. The server receives this authentication information and compares it with the authentication information stored in the database. If authentication is successful, the server generates the user's dashboard screen and sends it to the terminal. The terminal displays the dashboard screen received from the server to the user.

[0729] Input: User ID and password

[0730] Data processing: Verification against the server database

[0731] Output: Dashboard screen

[0732] Step 2:

[0733] Activating the dialogue module: The terminal displays a "Start dialogue" button on the dashboard screen. When the user clicks the "Start dialogue" button, the server's dialogue module is activated, which generates the first question (e.g., "Please introduce yourself") and sends it to the terminal. The terminal then displays the received question to the user.

[0734] Input: User clicks

[0735] Data processing: The server generates the initial question

[0736] Output: Question

[0737] Step 3:

[0738] Skill assessment: The server presents skill tests and challenges (e.g., programming problems, logic puzzles) to the user through the dialogue module. The user works on the challenges and enters their answers. The device sends the user's answers to the server. The server stores the received answers in a database and begins analyzing them as part of the skill assessment.

[0739] Input: User's answer

[0740] Data processing: The server evaluates the answers

[0741] Output: Evaluation result

[0742] Step 4:

[0743] Biometric data collection: The terminal collects biometric data such as heart rate, facial expression changes, and reaction speed through a wearable device or camera attached to the user. The server receives this data in real time and records it in a database.

[0744] Input: Data from wearable devices and cameras

[0745] Data processing: The server records the data

[0746] Output: Recorded biometric data

[0747] Step 5:

[0748] Emotion analysis: The terminal sends the collected biometric data to the emotion engine on the server. The server uses the emotion engine to analyze the user's emotional state (e.g., tension, relaxation). The resulting emotion data is provided to the data analysis means as part of the user's aptitude and personality assessment.

[0749] Input: Biometric data

[0750] Data processing: Data analysis using emotion engines

[0751] Output: Emotion data

[0752] Step 6:

[0753] Data integration and analysis: The server integrates the collected skill test answer data, biometric data, and emotion data provided by the emotion engine, and records them in a database. The data analysis module comprehensively analyzes this data and makes a comprehensive evaluation of the candidate's skills, aptitude, personality, potential, and future prospects.

[0754] Input: Skill test answer data, biometric data, emotion data

[0755] Data processing: Comprehensive data analysis

[0756] Output: Overall evaluation result

[0757] Step 7:

[0758] Matching: The server's matching module compares the evaluation results with the company's job information to make the best match. The server generates data to notify the user and the company of the matching results and sends it to the device. The device then displays the received matching results to the user.

[0759] Input: Overall evaluation results, company job information

[0760] Data processing: Matching algorithm

[0761] Output: Matching results

[0762] Through these steps, a fair and efficient matching system will be realized, which will enable optimal matching between companies and suitable candidates.

[0763] (Application example 2)

[0764] 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."

[0765] Traditional candidate-to-company matching systems rely on superficial skills and resume information, failing to fully grasp a candidate's emotional state, aptitude, or personality. Furthermore, it's difficult to assess a candidate's potential through skill assessment alone, making it difficult to find the best candidate who best meets a company's needs. Furthermore, candidate authentication and dialogue based on fixed questions fail to capture the candidate's true character, potentially resulting in mismatches.

[0766] 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.

[0767] In this invention, the server includes a dialogue module means for dialogue with candidates, a skill assessment means for assessing the candidates' skills, a biometrics collection means for collecting the candidates' biometric data, a data analysis means for analyzing the collected biometric data and the skill assessment results to assess the candidates' aptitude and personality, a matching means for matching the assessment results with the company's needs, and an emotion engine means for analyzing the collected biometric data in real time and assessing the candidates' emotional state. This enables real-time assessment of the candidates' emotional state and aptitude, enabling more appropriate and efficient matching. Furthermore, by using a generative model means, it is possible to evaluate the candidates' potential and future potential and find talent that is suitable for the company in the long term. Furthermore, a dialogue generation means is used to generate prompt sentences, allowing the candidate's true character to be captured through more personalized dialogue.

[0768] The "interaction module means" is a means for providing an interface and functionality for a candidate to interact with the system.

[0769] A "skills assessment instrument" is an instrument that has the means and function to assess a candidate's technical and professional competence.

[0770] "Biometrics collection means" refers to means including devices and technologies for collecting biometric information such as a candidate's heart rate and facial expression changes.

[0771] "Data analysis means" refers to means having algorithms and functions for analyzing collected biometric data and skill assessment results and evaluating the aptitude and personality of candidates.

[0772] A "matching tool" is a tool that has the method and function to compare the evaluation results with the needs of the company and select the most suitable candidate.

[0773] "Emotion engine means" means means having algorithms and techniques for analyzing collected biometric data in real time and assessing the emotional state of a candidate.

[0774] A "generative modeling tool" is a tool that uses generative artificial intelligence (AI) to assess a candidate's potential and future prospects.

[0775] "User Interface Means" means means for obtaining candidate authentication information and providing an interface for enabling access and operation of the system.

[0776] A "dialogue generation means" is a means having a language model and technology for generating appropriate questions and responses when a candidate and the system interact.

[0777] The present invention provides a system for matching candidates with companies more fairly and efficiently, which includes a dialogue module, a skill assessment means, a biometrics collection means, a data analysis means, a matching means, an emotion engine means, a generative model means, a user interface means, and a dialogue generation means.

[0778] System Program

[0779] 1. Log in and create a dashboard

[0780] The user logs in using a smartphone app or smart glasses with an ID and password. The server checks the authentication information against a database, and if authentication is successful, a dashboard screen is generated and sent to the user's device.

[0781] 2. Starting a dialogue

[0782] When the user taps the "Start Dialogue" button on the dashboard screen, the server starts the dialogue module means, generates an initial question, and sends it to the user. For example, a prompt such as "Please introduce yourself" is presented.

[0783] 3. Skills Assessment and Biometrics Collection

[0784] The server uses the skill assessment tool to present skill tests and tasks (e.g., programming problems and logic puzzles) to the candidates, while collecting biometric data (e.g., heart rate, facial expression changes) from the user's device (e.g., smart glasses or smartphone camera).

[0785] 4. Analysis by Emotion Engine

[0786] The collected biometric data is transmitted in real time to an emotion engine means, which analyzes the candidate's emotional state (e.g., nervous, relaxed) and provides the results to a data analysis means.

[0787] 5. Data analysis and matching

[0788] The server integrates the skill assessment results, biometric data, and emotional data, and uses data analysis means to evaluate the candidate's aptitude and personality. The assessment results are compared with the company's needs by a matching means to find the optimal match. The results are then notified to the user and the company.

[0789] Hardware and Software

[0790] Hardware:

[0791] Smartphone (e.g. iPhone, Android)

[0792] Smart glasses (e.g. Google Glass)

[0793] Wearable devices (e.g., Apple Watch)

[0794] software:

[0795] Frontend: React Native (smartphone app), WebRTC (video calling)

[0796] Backend: Node.js, Express.js

[0797] Database: MongoDB

[0798] Emotion engine: Affectiva SDK

[0799] Data analysis: Python (numpy, pandas, scikit-learn)

[0800] Examples and prompts

[0801] Specific examples

[0802] For example, when a user logs in and starts an interactive module, the following prompt is displayed:

[0803] "Please introduce yourself."

[0804] Please solve the following programming problems.

[0805] "Are you nervous? Just relax a bit."

[0806] While the user inputs and performs operations according to these prompts, the device collects the user's biometric information, which is then analyzed by the server in real time. This allows for a more comprehensive and accurate evaluation, and the results are used to match the user with the appropriate company.

[0807] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0808] Processing step details

[0809] Step 1:

[0810] The user enters their ID and password using a smartphone app or smart glasses to access the login screen. The server checks the authentication information against the database. The ID and password are required as input, and if authentication is successful by checking these data, the server generates a dashboard screen and sends it to the terminal. The dashboard screen is displayed to the user as output.

[0811] Step 2:

[0812] The user taps the "Start Dialogue" button on the dashboard screen. This causes the server to start the dialogue module means, generate the first question, and send it. The user's operation is input, and the server outputs the generated prompt sentence "Please introduce yourself," and displays it on the terminal.

[0813] Step 3:

[0814] The server uses the skill assessment means to present skill tests and tasks to candidates. As input, the server receives the information and requests provided by the user in the dialogue, and as output, it generates skill tests such as programming problems and logic puzzles and sends them to the terminal. The user works on these and enters the answers into the terminal.

[0815] Step 4:

[0816] While the user is taking the skill test, the device collects biometric data through a biometric collection means. For example, it uses smart glasses or a smartphone camera to monitor heart rate and facial expression changes. The input is real-time data from the camera or sensor, and the output is sent to a server.

[0817] Step 5:

[0818] The server sends the collected biometric data to the emotion engine means for real-time analysis. The input includes biometric information such as heart rate and facial expression changes, and the emotion engine analyzes the user's emotional state based on this data. The output is an analysis result (e.g., tension, relaxation).

[0819] Step 6:

[0820] The server integrates the analysis results from the emotion engine means, the answer data of the skill test, and the biometric data, and evaluates the aptitude and personality of the candidate using the data analysis means. All of these data are integrated as input, and a comprehensive evaluation result is generated as output.

[0821] Step 7:

[0822] The server assesses the candidate's potential and future potential using generative modeling tools, with the integrated data and generative AI model as inputs and a long-term candidate suitability assessment as output.

[0823] Step 8:

[0824] The server uses a matching method to compare the evaluation results with the needs of the company and perform optimal matching. The inputs are the candidate's overall evaluation results and the company's job information, and the output is a list of optimal candidates that is notified to the user and the company.

[0825] By following these steps, we can evaluate the candidate's emotional state and aptitude in real time, enabling more appropriate and efficient matching. Furthermore, by using generative models, we can evaluate the candidate's potential and future prospects and find the right fit for the company in the long term. Furthermore, by using dialogue generation, we can generate prompts to capture the candidate's true personality through more personalized dialogue.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] [Third embodiment]

[0830] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0831] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0832] 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).

[0833] 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.

[0834] 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.

[0835] 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).

[0836] 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.

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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."

[0842] An embodiment of the present invention is a system for matching candidates with companies in a fairer and more efficient manner. This system includes the following elements.

[0843] 1. User Interface Methods

[0844] Users access the system using a web browser or a dedicated application and log in by entering their authentication information (ID and password).

[0845] The server checks the user's authentication information against a database, and if authentication is successful, displays the user's dashboard screen.

[0846] 2. Interaction Module Means

[0847] The device displays a "Start Dialogue" button on the dashboard screen, and when the user clicks it, the AI ​​dialogue module is launched.

[0848] The server sends the candidate an initial question (e.g., "Please tell us about yourself") and receives the user's answer.

[0849] 3. Skills Assessment Tools

[0850] The server presents candidates with skill tests and challenges through an interactive module, including programming problems and logic puzzles.

[0851] The user works on the displayed tasks and enters their answers.

[0852] The terminal transmits the user's answer to the server.

[0853] 4. Biometrics Collection Methods

[0854] The device collects biometric data from the user through wearable devices and cameras, including heart rate, facial expression changes, and reaction speed.

[0855] The server receives this data in real time and records it in a database.

[0856] 5. Data Analysis Methods

[0857] The server integrates the collected skill test answer data and biometric data and performs analysis using a data analysis module.

[0858] The data analysis module assesses candidates' skills, aptitudes, and personality, records the results, and also uses generative artificial intelligence (AI) to assess their potential and future prospects.

[0859] 6. Matching Methods

[0860] The matching module (server) compares the candidate evaluation results with the company's job information to make the best match.

[0861] The server notifies the user and the company of the matching results.

[0862] Specific examples

[0863] For example, when a user logs into the system, a dialogue module is launched and they are asked to introduce themselves. The user then takes a skill test and solves programming problems and logic puzzles. During this time, the device continues to collect the user's heart rate and facial expression changes. The data analysis module analyzes this data and provides an overall evaluation of the user. Finally, the matching module compares the evaluation results with the needs of companies and suggests the most suitable company to the user. This series of processes ensures bias-free and objective recruitment.

[0864] The above is an embodiment of the present invention, which enables companies to efficiently recruit suitable personnel for the long term.

[0865] The processing flow will be explained below.

[0866] Step 1:

[0867] Users access the system using a web browser or a dedicated application and log in by entering their ID and password.

[0868] Step 2:

[0869] The terminal transmits the input authentication information to the server.

[0870] Step 3:

[0871] The server checks the authentication information against a database, and if authentication is successful, generates a dashboard screen for the user and sends it to the terminal.

[0872] Step 4:

[0873] The terminal displays a dashboard screen to the user.

[0874] Step 5:

[0875] The user clicks the "Start conversation" button on the dashboard.

[0876] Step 6:

[0877] The server launches an AI dialogue module, generates an initial question for the candidate, and sends it to the terminal.

[0878] Step 7:

[0879] The terminal displays the initial question sent from the server (e.g., "Please introduce yourself") to the user.

[0880] Step 8:

[0881] The user inputs the answer to the question and sends it to the server via the terminal.

[0882] Step 9:

[0883] The server receives the user's answer, generates the next question or challenge, and sends it to the terminal.

[0884] Step 10:

[0885] The device displays the next question or challenge (e.g., a skills test question) to the user.

[0886] Step 11:

[0887] The user solves the problem and sends the answer to the server via the terminal.

[0888] Step 12:

[0889] The terminal transmits the user's answers to the server, and at the same time collects the user's biometric data (e.g., heart rate, facial expression changes) and transmits it to the server in real time.

[0890] Step 13:

[0891] The server records the received answer data and biometric data in a database.

[0892] Step 14:

[0893] The data analysis module (server) analyzes this data and makes a comprehensive assessment of the candidate's skills, aptitude, personality, potential, and future prospects.

[0894] Step 15:

[0895] The server generates and sends the evaluation results to the matching module.

[0896] Step 16:

[0897] The matching module (server) compares the evaluation results with company job information to make the best match.

[0898] Step 17:

[0899] The server generates data for notifying the user and the company of the matching results and transmits the data to the terminal.

[0900] Step 18:

[0901] The device displays the matching results to the user, and the results are also notified to the company's recruiting staff.

[0902] Example 1

[0903] 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."

[0904] In the modern recruitment process, matching between candidates and companies is often influenced by subjective factors, making it difficult to achieve fair and efficient matching. Furthermore, there is a need to evaluate not only candidates' skills and aptitude, but also their potential and future prospects. Current technology lacks a system that can comprehensively evaluate these factors and achieve optimal matching, so this problem needs to be solved.

[0905] 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.

[0906] In this invention, the server includes a user interface means, a dialogue module means for dialogue with candidates, a skill evaluation means for evaluating the skills of the candidates, a biometrics collection means for collecting biometric data of the candidates, a data analysis means for analyzing the collected biometric data and the skill evaluation results to evaluate the aptitude and personality of the candidates, and a matching means for matching the evaluation results with the needs of companies, thereby enabling fair and efficient matching of candidates and companies.

[0907] The "user interface means" is a means by which a user accesses the system, inputs authentication information, and performs various operations via the dashboard screen.

[0908] The "dialogue module means" is a module for dialogue with candidates, and is a means for presenting initial questions and skill test tasks and collecting responses from candidates.

[0909] A "skill assessment means" is a means for assessing the skills of a candidate, and is a means for presenting tasks such as programming problems and logic puzzles and accepting the candidate's answers.

[0910] "Biometrics collection means" means a means for collecting biometric data such as a candidate's heart rate, facial expression changes, reaction speed, etc. This includes wearable devices and cameras.

[0911] "Data Analysis Means" refers to means for integrating collected biometric data and skill assessment results to evaluate a candidate's aptitude and personality, including a data analysis module and a generative AI model.

[0912] "Matching methods" are methods for comparing candidate evaluation results with the needs of the company to achieve optimal matching. Based on the evaluation results, the company proposes the most suitable candidate.

[0913] A "generative artificial intelligence (AI) means" is a means that uses AI technology to assess a candidate's potential and future prospects.

[0914] An embodiment of the present invention is a system for matching candidates with companies in a fairer and more efficient manner. This system includes the following elements.

[0915] 1. User Interface Methods

[0916] A user accesses the system using a web browser or a dedicated application and enters authentication information (ID and password) to log in. The server checks the user's authentication information against a database (e.g., MySQL database), and if authentication is successful, displays the user's dashboard screen.

[0917] 2. Interaction Module Means

[0918] The terminal displays a "Start Dialogue" button on the dashboard screen, and when the user clicks it, the AI ​​dialogue module is launched. The server sends the first question to the candidate (e.g., "Please introduce yourself") and receives the user's answer.

[0919] 3. Skills Assessment Tools

[0920] The server presents skill tests and challenges to the candidate through the dialogue module, such as programming problems and logic puzzles. The user works through the challenges displayed and enters their answers. The terminal then transmits the user's answers to the server.

[0921] 4. Biometrics Collection Methods

[0922] The terminal collects biometric data from the user through a wearable device or camera, including heart rate, facial expression changes, reaction speed, etc. The server receives this data in real time and records it in a database.

[0923] 5. Data Analysis Methods

[0924] The server integrates the collected skill test answer data and biometric data and analyzes them using a data analysis module. The data analysis module evaluates the candidate's skills, aptitude, and personality, and records the evaluation results. It also evaluates the candidate's potential and future prospects using generative artificial intelligence (AI) methods. This data analysis module can be implemented using Python and the scikit-learn library.

[0925] 6. Matching Methods

[0926] The matching module (server) compares the candidate's evaluation results with the company's job information to find the best match. The server then notifies the user and the company of the matching results. Notification can be via email or in-system messages.

[0927] Specific examples

[0928] For example, when a user logs into the system, the server displays a dashboard screen after authentication. The terminal then displays a "Start Dialogue" button, and when the user clicks it, the server sends a message saying, "Please introduce yourself." When the user enters their answers to a skill test, the data is sent to the server. The terminal also collects the user's real-time biometric data and sends it to the server. Finally, the server analyzes this data, performs optimal matching with companies, and notifies the user and company of the results.

[0929] Prompt Sentence Examples

[0930] "Please introduce yourself."

[0931] "Solve a programming problem. Example: Predict the output of the following code."

[0932] "Please relax as we will be recording your heart rate and facial expressions."

[0933] The above is an embodiment of the present invention, which realizes fair and efficient matching between candidates and companies. Furthermore, the various means included in the system work in conjunction with each other to provide highly accurate evaluation and optimal matching.

[0934] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0935] Step 1:

[0936] A user accesses the system using a web browser or a dedicated application. As input, the user enters an ID and password and attempts to log in to the system. As output, an authentication request is generated and sent to the server.

[0937] Step 2:

[0938] The server compares the received authentication information with the information stored in a database (for example, a MySQL database). This process involves searching the database for the relevant user information and verifying that it matches the entered ID and password. The output is an authentication result (success or failure).

[0939] Step 3:

[0940] If authentication is successful, the server displays the user's dashboard screen. If there is an error message, it notifies the user. The server makes a decision based on the authentication result as input, and generates the next screen information to be displayed as output.

[0941] Step 4:

[0942] The terminal displays a "Start Interaction" button on the dashboard screen. The configuration information of the dashboard screen is read as input, and the "Start Interaction" button is displayed on the user interface as output.

[0943] Step 5:

[0944] The user clicks the "Start Interaction" button, which generates a click event as input and sends a request to the server to start an interaction as output.

[0945] Step 6:

[0946] The server starts the AI ​​dialogue module and sends the first question (e.g., "Please introduce yourself") to the user. It receives a click event as input and generates a prompt sentence as output, which is sent to the user's device.

[0947] Step 7:

[0948] The user answers the first question by entering the answer text as input, and the answer is sent to the server as output.

[0949] Step 8:

[0950] The server records the received answers in a database. It receives the candidate's answer data as input and generates a request to save the answer contents in a database as output.

[0951] Step 9:

[0952] The server presents the candidate with the next skill test or challenge through a dialogue module, which can include programming questions, logic puzzles, etc. It receives triggers from previous answers as input and generates the next challenge as output, which it then sends to the user.

[0953] Step 10:

[0954] The user works on the displayed assignment and inputs the answer. The assignment content is read as input, and the answer is generated as output and sent to the server.

[0955] Step 11:

[0956] The terminal sends the user's answer to the server, which takes the answer data as input and generates a request to send it as output.

[0957] Step 12:

[0958] The terminal collects biometric data through a wearable device or camera attached to the user, including heart rate, facial expression changes, reaction speed, etc. It receives sensor data as input and transmits it to a server in real time as output.

[0959] Step 13:

[0960] The server receives the collected biometric data in real time and records it in a database. It receives the biometric data stream as input and generates a request to store the data in a database as output.

[0961] Step 14:

[0962] The server integrates the collected skill test answer data and biometric data and performs analysis using a data analysis module. It reads the integrated data as input and generates evaluation results as output.

[0963] Step 15:

[0964] The data analysis module evaluates the candidate's skills, aptitude, and personality, and records the evaluation results. Furthermore, it uses a generative AI model to evaluate the candidate's potential and future prospects. Each piece of data is analyzed as input, and a comprehensive evaluation result is generated as output.

[0965] Step 16:

[0966] The matching module (server) compares the candidate evaluation results with the company's job information to make the best match. It receives the evaluation results and the company's needs as input, and generates and notifies the matching results as output.

[0967] Step 17:

[0968] The server notifies users and companies of the matching results via email or internal system messages. Based on the matching results as input, notifications are generated and sent as output.

[0969] Through the above processing steps, the present invention achieves fair and efficient matching between candidates and companies.

[0970] (Application example 1)

[0971] 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."

[0972] Traditional staff recruitment and evaluation processes in brick-and-mortar stores require a lot of time and effort, and are prone to subjective bias. Furthermore, it is often difficult to accurately assess candidates' skills and aptitude, making it difficult to efficiently hire the best talent. Furthermore, traditional methods make it difficult to utilize biometric data, such as a candidate's stress level or reaction speed.

[0973] 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.

[0974] In this invention, the server includes a dialogue module means for dialogue with candidates, a skill evaluation means for evaluating the skills of the candidates, a biometrics collection means for collecting biometric data of the candidates, a data analysis means for analyzing the collected biometric data and the skill evaluation results and evaluating the aptitude and personality of the candidates, a matching means for matching the evaluation results with the needs of the company, a means for streamlining the staff recruitment and evaluation process for the brick-and-mortar store, a means for collecting biometric data using a smartphone camera or a wearable device, and a means for collecting input from the candidates and providing a user interface. This enables an integrated evaluation of the skills and biometric data of candidates and enables efficient and fair hiring of the best talent.

[0975] An "interaction module" is a component that interacts with candidates, generates questions, and collects answers.

[0976] A "skills assessment tool" is a tool that presents tests or tasks to assess candidates' skills and collects the results.

[0977] "Biometrics collection means" refers to a device or system that collects biometric data such as a candidate's heart rate, facial expression changes, and reaction speed.

[0978] The "data analysis means" is a module that integrates the collected biometric data with the skill assessment results to evaluate the candidate's aptitude and personality.

[0979] A "matching method" is a system that compares the candidate evaluation results with the company's needs to make the optimal match.

[0980] "Means for streamlining the staff recruitment and evaluation process for brick-and-mortar stores" refers to tools and systems that automate and streamline the traditional staff recruitment and evaluation process.

[0981] "Means for collecting biometric data using a smartphone camera or a wearable device" refers to means for collecting biometric information such as heart rate, facial expression changes, and reaction speed using a smartphone camera or a wearable device.

[0982] The "means for providing a user interface" is a component that provides an interface for candidates to log in to the system and use various functions.

[0983] This invention is a system for making the staff recruitment and evaluation process in a brick-and-mortar store more efficient and fair. Below, we will explain in detail the program and processing method for realizing this system.

[0984] The server includes a dialogue module, a skill assessment unit, a biometrics collection unit, a data analysis unit, and a matching unit, which enable an integrated assessment of a candidate's skills and biometric data, thereby enabling efficient and fair recruitment of the most suitable personnel.

[0985] Hardware and software used

[0986] Smartphones: Use cameras and touchscreens to gather user input.

[0987] Wearable devices: Used to collect biometric data such as heart rate, facial expression changes, and reaction speed.

[0988] Server: Candidate data management and analysis is performed using the Django framework.

[0989] Client-side software: Building the user interface using React.

[0990] Processing Description

[0991] 1. Authentication and Login

[0992] Users access the system using their smartphones and enter their authentication information (ID and password) to log in. The server compares this information with the database, and if authentication is successful, displays the user's dashboard screen.

[0993] 2. Starting the dialogue module

[0994] When a user clicks the "Start Dialogue" button on the dashboard screen, the dialogue module is launched. The server uses the generative AI model to generate an initial question (e.g., "Please introduce yourself") and sends it to the user.

[0995] Example prompt sentence:

[0996] "Generate the best questions for candidates to introduce themselves."

[0997] 3. Skills Assessment

[0998] Through the dialogue module, the server presents the candidate with skill tests and assignments. The user enters their answers using their smartphone, and this data is sent to the server, which stores the data and prepares it for analysis.

[0999] 4. Biometric Data Collection

[1000] Candidates wear wearable devices that collect real-time data such as heart rate, facial expression changes, and reaction time. Smartphone cameras may also be used. This data is sent to a server and recorded in a database.

[1001] 5. Data Analysis

[1002] The server integrates the collected skill test answer data and biometric data and performs analysis using a data analysis module, which also uses generative AI models to evaluate the candidate's skills, aptitude, personality, and potential and future prospects.

[1003] Example prompt sentence:

[1004] "Please rate the candidate's skill level based on their answers."

[1005] "Assess the candidate's stress level based on heart rate and facial expression changes."

[1006] 6. Matching

[1007] Finally, the server uses a matching module to compare the evaluation results with the needs of the company and make the best match, which is then notified to the user and the company.

[1008] This system streamlines the hiring process for brick-and-mortar stores and ensures unbiased and fair evaluations.

[1009] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1010] Step 1:

[1011] Users access the system using their smartphones and log in by entering their authentication information (ID and password). The server checks the user's authentication information against the database, and if authentication is successful, displays the user's dashboard screen. The input here is the user's ID and password, and the output is the dashboard screen.

[1012] Step 2:

[1013] When a user clicks the "Start Dialogue" button on the dashboard screen, the server launches the dialogue module. The server uses a generative AI model to generate an initial question (e.g., "Please introduce yourself") and sends it to the user. The input here is the event of pressing the "Start Dialogue" button, and the output is the generated question.

[1014] Step 3:

[1015] The user uses a smartphone to input answers to questions sent from the server. The server receives the answers and stores them in a database. The input here is the user's answer, and the output is the saved answer data.

[1016] Step 4:

[1017] The server presents skill tests and assignments to the user through the dialogue module. The user answers these tests and assignments using their smartphone and sends the answers to the server, which receives them and stores them in a database. The input here is the answers to the skill tests and assignments, and the output is the stored skill assessment data.

[1018] Step 5:

[1019] The user wears a wearable device and uses the smartphone camera to collect biometric data. The collected data includes heart rate, facial expression changes, reaction speed, etc. The device transmits this biometric data to a server in real time. The input here is the collected biometric data, and the output is the data transmitted to the server.

[1020] Step 6:

[1021] The server integrates the collected skill assessment data and biometric data and performs analysis using a data analysis module. This analysis evaluates the candidate's skills, aptitude, and personality. It also evaluates the candidate's potential and future prospects using a generative AI model. The input here is the integrated skill assessment data and biometric data, and the output is the analysis results.

[1022] Step 7:

[1023] The server uses a matching module to compare the analysis results with the company's needs and make the best match. The matching results are notified to the user and the company. The input here is the analysis results and the company's needs, and the output is the matching results.

[1024] 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.

[1025] One embodiment of the present invention is a system for matching candidates with companies in a fairer and more efficient manner. The system incorporates an emotion engine that recognizes the user's emotions and can use emotion data to provide more accurate evaluations.

[1026] 1. User Interface Methods

[1027] Users access the system using a web browser or a dedicated application and log in by entering their ID and password.

[1028] The server checks the user's authentication information against a database, and if authentication is successful, generates a dashboard screen for the user and sends it to the terminal.

[1029] 2. Interaction Module Means

[1030] The device displays a "Start Dialogue" button on the dashboard screen, and when the user clicks it, the AI ​​dialogue module is launched.

[1031] The server generates an initial question for the candidate (e.g., "Please tell us about yourself") and sends it to the terminal.

[1032] 3. Skills Assessment Tools

[1033] The server presents candidates with skill tests and challenges through an interactive module, including programming problems and logic puzzles.

[1034] The user works on the displayed tasks and enters their answers.

[1035] The terminal transmits the user's answer to the server.

[1036] 4. Biometrics Collection Methods

[1037] The device collects biometric data from the user through wearable devices and cameras, including heart rate, facial expression changes, and reaction speed.

[1038] The server receives this data in real time and records it in a database.

[1039] 5. Emotional Engine Means

[1040] The terminal transmits the collected biometric data to the emotion engine.

[1041] The server analyzes the user's emotional state in real time using the emotion engine, and the resulting emotion data is provided to the data analysis means as part of the user's aptitude and personality evaluation.

[1042] 6. Data Analysis Methods

[1043] The server integrates the collected skill test answer data, biometric data, and emotion data provided by the emotion engine, and performs analysis using a data analysis module.

[1044] The data analysis module conducts a comprehensive assessment of the candidate's skills, aptitude, personality, potential and future prospects.

[1045] 7. Matching Methods

[1046] The matching module (server) compares the evaluation results with company job information to make the best match.

[1047] The server generates data for notifying the user and the company of the matching results and transmits the data to the terminal.

[1048] Specific examples

[1049] For example, when a user logs into the system, a dialogue module is launched and the user is asked to introduce themselves. The user then takes a skill test and solves programming problems and logic puzzles. During this time, the device continues to collect the user's heart rate and facial expression changes, and this data is analyzed in real time by the emotion engine. The emotion engine analyzes the user's emotional state (e.g., tension, relaxation) and provides the emotion data to the data analysis means. The data analysis module analyzes this data and performs an overall evaluation of the user. Finally, the matching module compares the evaluation results with the needs of companies and suggests the most suitable company to the user. Through this series of processes, bias-free and objective recruitment is achieved.

[1050] The above is an embodiment of the present invention, which enables companies to efficiently recruit suitable personnel for the long term.

[1051] The processing flow will be explained below.

[1052] Step 1:

[1053] Users access the system using a web browser or a dedicated application and log in by entering their ID and password.

[1054] Step 2:

[1055] The terminal transmits the input authentication information to the server.

[1056] Step 3:

[1057] The server checks the authentication information against a database, and if authentication is successful, generates a dashboard screen for the user and sends it to the terminal.

[1058] Step 4:

[1059] The terminal displays a dashboard screen to the user.

[1060] Step 5:

[1061] The user clicks the "Start conversation" button on the dashboard.

[1062] Step 6:

[1063] The server launches an AI dialogue module, generates an initial question for the candidate, and sends it to the terminal.

[1064] Step 7:

[1065] The terminal displays the initial question sent from the server (e.g., "Please introduce yourself") to the user.

[1066] Step 8:

[1067] The user inputs the answer to the question and sends it to the server via the terminal.

[1068] Step 9:

[1069] The server receives the user's answer, generates the next question or challenge, and sends it to the terminal.

[1070] Step 10:

[1071] The device displays the next question or challenge (e.g., a skills test question) to the user.

[1072] Step 11:

[1073] The user solves the problem and sends the answer to the server via the terminal.

[1074] Step 12:

[1075] The terminal transmits the user's answers to the server, and at the same time collects the user's biometric data (e.g., heart rate, facial expression changes) and transmits it to the server in real time.

[1076] Step 13:

[1077] The server records the received answer data and biometric data in a database.

[1078] Step 14:

[1079] The terminal transmits the collected biometric data to the emotion engine.

[1080] Step 15:

[1081] The emotion engine (server) analyzes the user's emotional state in real time based on biometric data and generates emotion data.

[1082] Step 16:

[1083] The server transmits the emotion data and the answer data of the skill test to the data analysis module.

[1084] Step 17:

[1085] The data analysis module (server) analyzes this data and makes a comprehensive assessment of the candidate's skills, aptitude, personality, potential, and future prospects.

[1086] Step 18:

[1087] The server sends the evaluation results to the matching module.

[1088] Step 19:

[1089] The matching module (server) compares the evaluation results with company job information to make the best match.

[1090] Step 20:

[1091] The server generates data for notifying the user and the company of the matching results and transmits the data to the terminal.

[1092] Step 21:

[1093] The device displays the matching results to the user, and the results are also notified to the company's recruiting staff.

[1094] Example 2

[1095] 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."

[1096] In conventional recruitment systems, matching candidates with companies relied on subjective evaluations, making it difficult to efficiently find the best talent. Furthermore, aptitude assessment based not only on the content of candidates' responses, but also on their emotional state and biometric data was not adequately conducted. Therefore, there was a need for a system that comprehensively evaluates candidates' potential and future prospects, and matches them fairly and efficiently with the needs of companies.

[1097] 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.

[1098] In this invention, the server includes authentication means for verifying authentication information, dialogue means for dialogue with the candidate, ability evaluation means for evaluating the candidate's abilities, biometric information collection means for collecting the candidate's biometric information, information analysis means for analyzing the collected biometric information and the ability evaluation results to evaluate the candidate's aptitude and personality, and matching means for matching the evaluation results with job requirements. This enables bias-free evaluation that eliminates subjectivity and realizes optimal matching between candidates and companies.

[1099] The "authentication means" is a function for verifying the user's authentication information and confirming legitimate access rights.

[1100] "Interaction means" refers to an interface for exchanging information between candidates and the system.

[1101] "Competency assessment tools" are functions for assessing candidates' skills and knowledge.

[1102] "Biometric information collection means" is a function for collecting biometric data such as the candidate's heart rate and facial expression changes.

[1103] "Information analysis means" is a function that integrates collected biometric information with the results of ability assessments to evaluate the suitability and personality of candidates.

[1104] "Matching methods" are functions that use evaluation results to compare candidates with the needs of companies and make optimal matches.

[1105] The present invention relates to a system for matching candidates with companies in a fair and efficient manner. The system incorporates an emotion engine that recognizes the emotions of candidates and can provide more accurate evaluations by utilizing emotion data.

[1106] The system is implemented using the following hardware and software:

[1107] Hardware

[1108] Server: A cloud-based server (e.g., AWS, Google Cloud) can be used. The server includes functions for user authentication, database management, execution of AI dialogue modules, and execution of data analysis.

[1109] Terminal: This refers to a user's PC, tablet, smartphone, etc. The system is accessed through a web browser or dedicated application.

[1110] Wearable device: A device used to collect biometric data about a user (e.g., smartwatch, fitness tracker).

[1111] software

[1112] Sentiment engine: AI tools and libraries for sentiment analysis (e.g., TensorFlow, PyTorch).

[1113] Data Analysis Module: Analysis software for integrating multiple data sets and evaluating candidates.

[1114] Specific operating procedures for the system

[1115] 1. User authentication: A user accesses the system using a web browser or a dedicated app and logs in by entering their ID and password. The server receives this authentication information and compares it with the data stored in the database. If authentication is successful, the user's dashboard screen is generated and sent to the terminal.

[1116] 2. Starting a conversation: The terminal displays a "Start conversation" button on the dashboard screen, and when the user clicks it, the conversation module starts. The server generates an initial question (e.g., "Please introduce yourself") and sends it to the terminal. The terminal displays the received question to the user.

[1117] 3. Skill Assessment: The server presents skill tests and challenges to the user through the dialogue module. The user tackles the problems and enters the answers, which are then sent to the server. The server stores the answers in a database and begins analyzing them as part of the skill assessment.

[1118] 4. Biometric data collection: The terminal collects biometric data such as heart rate, facial expression changes, and reaction speed through the wearable device and camera attached to the user. The server receives this data in real time and records it in a database.

[1119] 5. Emotion Analysis: The terminal sends the collected biometric data to the emotion engine. The server uses the emotion engine to analyze the user's emotional state in real time. The resulting emotion data is provided to the data analysis means as part of the user's aptitude and personality assessment.

[1120] 6. Data integration and analysis: The server integrates the collected skill test answer data, biometric data, and emotional data provided by the emotion engine and records them in a database. The data analysis module comprehensively analyzes this data and performs a subjective evaluation of the candidate, including an evaluation of skills, aptitude, personality, potential, and future prospects.

[1121] 7. Matching: The matching module compares the evaluation results with the company's job information and proposes the most suitable candidates to the company. The server generates data to notify the user and the company of the matching results and sends it to the terminal. The terminal displays the received matching results to the user.

[1122] Examples of concrete examples and prompts

[1123] For example, when a user logs into the system, the dialogue module is activated and the first question displayed is, "Please introduce yourself." The user then attempts skill tests such as programming problems and logic puzzles. In parallel, the device continues to collect the user's heart rate and facial expression changes, and this data is analyzed in real time by the emotion engine. The emotion data is provided to the data analysis means, which performs a comprehensive evaluation. Finally, the matching module compares the needs of companies with the evaluation results and suggests the most suitable companies to the user.

[1124] Example prompt sentence:

[1125] "Please explain the process by which a user logs in and an interaction module is initiated."

[1126] "Please explain with examples how the system works when a user completes a skills test."

[1127] "Please explain how the emotion engine analyzes biometric data and how the results of this analysis are used in the evaluation."

[1128] "Please explain how the matching module uses the assessment results to match with company job openings."

[1129] The above is an embodiment of the present invention, and this system makes it possible to optimally match companies with suitable candidates in a fair and efficient manner.

[1130] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1131] Step 1:

[1132] User authentication: The user accesses the system using a web browser or a dedicated app and logs in by entering their ID and password. The server receives this authentication information and compares it with the authentication information stored in the database. If authentication is successful, the server generates the user's dashboard screen and sends it to the terminal. The terminal displays the dashboard screen received from the server to the user.

[1133] Input: User ID and password

[1134] Data processing: Verification against the server database

[1135] Output: Dashboard screen

[1136] Step 2:

[1137] Activating the dialogue module: The terminal displays a "Start dialogue" button on the dashboard screen. When the user clicks the "Start dialogue" button, the server's dialogue module is activated, which generates the first question (e.g., "Please introduce yourself") and sends it to the terminal. The terminal then displays the received question to the user.

[1138] Input: User clicks

[1139] Data processing: The server generates the initial question

[1140] Output: Question

[1141] Step 3:

[1142] Skill assessment: The server presents skill tests and challenges (e.g., programming problems, logic puzzles) to the user through the dialogue module. The user works on the challenges and enters their answers. The device sends the user's answers to the server. The server stores the received answers in a database and begins analyzing them as part of the skill assessment.

[1143] Input: User's answer

[1144] Data processing: The server evaluates the answers

[1145] Output: Evaluation result

[1146] Step 4:

[1147] Biometric data collection: The terminal collects biometric data such as heart rate, facial expression changes, and reaction speed through a wearable device or camera attached to the user. The server receives this data in real time and records it in a database.

[1148] Input: Data from wearable devices and cameras

[1149] Data processing: The server records the data

[1150] Output: Recorded biometric data

[1151] Step 5:

[1152] Emotion analysis: The terminal sends the collected biometric data to the emotion engine on the server. The server uses the emotion engine to analyze the user's emotional state (e.g., tension, relaxation). The resulting emotion data is provided to the data analysis means as part of the user's aptitude and personality assessment.

[1153] Input: Biometric data

[1154] Data processing: Data analysis using emotion engines

[1155] Output: Emotion data

[1156] Step 6:

[1157] Data integration and analysis: The server integrates the collected skill test answer data, biometric data, and emotion data provided by the emotion engine, and records them in a database. The data analysis module comprehensively analyzes this data and makes a comprehensive evaluation of the candidate's skills, aptitude, personality, potential, and future prospects.

[1158] Input: Skill test answer data, biometric data, emotion data

[1159] Data processing: Comprehensive data analysis

[1160] Output: Overall evaluation result

[1161] Step 7:

[1162] Matching: The server's matching module compares the evaluation results with the company's job information to make the best match. The server generates data to notify the user and the company of the matching results and sends it to the device. The device then displays the received matching results to the user.

[1163] Input: Overall evaluation results, company job information

[1164] Data processing: Matching algorithm

[1165] Output: Matching results

[1166] Through these steps, a fair and efficient matching system will be realized, which will enable optimal matching between companies and suitable candidates.

[1167] (Application example 2)

[1168] 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."

[1169] Traditional candidate-to-company matching systems rely on superficial skills and resume information, failing to fully grasp a candidate's emotional state, aptitude, or personality. Furthermore, it's difficult to assess a candidate's potential through skill assessment alone, making it difficult to find the best candidate who best meets a company's needs. Furthermore, candidate authentication and dialogue based on fixed questions fail to capture the candidate's true character, potentially resulting in mismatches.

[1170] 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.

[1171] In this invention, the server includes a dialogue module means for dialogue with candidates, a skill assessment means for assessing the candidates' skills, a biometrics collection means for collecting the candidates' biometric data, a data analysis means for analyzing the collected biometric data and the skill assessment results to assess the candidates' aptitude and personality, a matching means for matching the assessment results with the company's needs, and an emotion engine means for analyzing the collected biometric data in real time and assessing the candidates' emotional state. This enables real-time assessment of the candidates' emotional state and aptitude, enabling more appropriate and efficient matching. Furthermore, by using a generative model means, it is possible to evaluate the candidates' potential and future potential and find talent that is suitable for the company in the long term. Furthermore, a dialogue generation means is used to generate prompt sentences, allowing the candidate's true character to be captured through more personalized dialogue.

[1172] The "interaction module means" is a means for providing an interface and functionality for a candidate to interact with the system.

[1173] A "skills assessment instrument" is an instrument that has the means and function to assess a candidate's technical and professional competence.

[1174] "Biometrics collection means" refers to means including devices and technologies for collecting biometric information such as a candidate's heart rate and facial expression changes.

[1175] "Data analysis means" refers to means having algorithms and functions for analyzing collected biometric data and skill assessment results and evaluating the aptitude and personality of candidates.

[1176] A "matching tool" is a tool that has the method and function to compare the evaluation results with the needs of the company and select the most suitable candidate.

[1177] "Emotion engine means" means means having algorithms and techniques for analyzing collected biometric data in real time and assessing the emotional state of a candidate.

[1178] A "generative modeling tool" is a tool that uses generative artificial intelligence (AI) to assess a candidate's potential and future prospects.

[1179] "User Interface Means" means means for obtaining candidate authentication information and providing an interface for enabling access and operation of the system.

[1180] A "dialogue generation means" is a means having a language model and technology for generating appropriate questions and responses when a candidate and the system interact.

[1181] The present invention provides a system for matching candidates with companies more fairly and efficiently, which includes a dialogue module, a skill assessment means, a biometrics collection means, a data analysis means, a matching means, an emotion engine means, a generative model means, a user interface means, and a dialogue generation means.

[1182] System Program

[1183] 1. Log in and create a dashboard

[1184] The user logs in using a smartphone app or smart glasses with an ID and password. The server checks the authentication information against a database, and if authentication is successful, a dashboard screen is generated and sent to the user's device.

[1185] 2. Starting a dialogue

[1186] When the user taps the "Start Dialogue" button on the dashboard screen, the server starts the dialogue module means, generates an initial question, and sends it to the user. For example, a prompt such as "Please introduce yourself" is presented.

[1187] 3. Skills Assessment and Biometrics Collection

[1188] The server uses the skill assessment tool to present skill tests and tasks (e.g., programming problems and logic puzzles) to the candidates, while collecting biometric data (e.g., heart rate, facial expression changes) from the user's device (e.g., smart glasses or smartphone camera).

[1189] 4. Analysis by Emotion Engine

[1190] The collected biometric data is transmitted in real time to an emotion engine means, which analyzes the candidate's emotional state (e.g., nervous, relaxed) and provides the results to a data analysis means.

[1191] 5. Data analysis and matching

[1192] The server integrates the skill assessment results, biometric data, and emotional data, and uses data analysis means to evaluate the candidate's aptitude and personality. The assessment results are compared with the company's needs by a matching means to find the optimal match. The results are then notified to the user and the company.

[1193] Hardware and Software

[1194] Hardware:

[1195] Smartphone (e.g. iPhone, Android)

[1196] Smart glasses (e.g. Google Glass)

[1197] Wearable devices (e.g., Apple Watch)

[1198] software:

[1199] Frontend: React Native (smartphone app), WebRTC (video calling)

[1200] Backend: Node.js, Express.js

[1201] Database: MongoDB

[1202] Emotion engine: Affectiva SDK

[1203] Data analysis: Python (numpy, pandas, scikit-learn)

[1204] Examples and prompts

[1205] Specific examples

[1206] For example, when a user logs in and starts an interactive module, the following prompt is displayed:

[1207] "Please introduce yourself."

[1208] Please solve the following programming problems.

[1209] "Are you nervous? Just relax a bit."

[1210] While the user inputs and performs operations according to these prompts, the device collects the user's biometric information, which is then analyzed by the server in real time. This allows for a more comprehensive and accurate evaluation, and the results are used to match the user with the appropriate company.

[1211] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1212] Processing step details

[1213] Step 1:

[1214] The user enters their ID and password using a smartphone app or smart glasses to access the login screen. The server checks the authentication information against the database. The ID and password are required as input, and if authentication is successful by checking these data, the server generates a dashboard screen and sends it to the terminal. The dashboard screen is displayed to the user as output.

[1215] Step 2:

[1216] The user taps the "Start Dialogue" button on the dashboard screen. This causes the server to start the dialogue module means, generate the first question, and send it. The user's operation is input, and the server outputs the generated prompt sentence "Please introduce yourself," and displays it on the terminal.

[1217] Step 3:

[1218] The server uses the skill assessment means to present skill tests and tasks to candidates. As input, the server receives the information and requests provided by the user in the dialogue, and as output, it generates skill tests such as programming problems and logic puzzles and sends them to the terminal. The user works on these and enters the answers into the terminal.

[1219] Step 4:

[1220] While the user is taking the skill test, the device collects biometric data through a biometric collection means. For example, it uses smart glasses or a smartphone camera to monitor heart rate and facial expression changes. The input is real-time data from the camera or sensor, and the output is sent to a server.

[1221] Step 5:

[1222] The server sends the collected biometric data to the emotion engine means for real-time analysis. The input includes biometric information such as heart rate and facial expression changes, and the emotion engine analyzes the user's emotional state based on this data. The output is an analysis result (e.g., tension, relaxation).

[1223] Step 6:

[1224] The server integrates the analysis results from the emotion engine means, the answer data of the skill test, and the biometric data, and evaluates the aptitude and personality of the candidate using the data analysis means. All of these data are integrated as input, and a comprehensive evaluation result is generated as output.

[1225] Step 7:

[1226] The server assesses the candidate's potential and future potential using generative modeling tools, with the integrated data and generative AI model as inputs and a long-term candidate suitability assessment as output.

[1227] Step 8:

[1228] The server uses a matching method to compare the evaluation results with the needs of the company and perform optimal matching. The inputs are the candidate's overall evaluation results and the company's job information, and the output is a list of optimal candidates that is notified to the user and the company.

[1229] By following these steps, we can evaluate the candidate's emotional state and aptitude in real time, enabling more appropriate and efficient matching. Furthermore, by using generative models, we can evaluate the candidate's potential and future prospects and find the right fit for the company in the long term. Furthermore, by using dialogue generation, we can generate prompts to capture the candidate's true personality through more personalized dialogue.

[1230] 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.

[1231] 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.

[1232] 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.

[1233] [Fourth embodiment]

[1234] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1235] 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.

[1236] 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).

[1237] 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.

[1238] 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.

[1239] 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).

[1240] 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.

[1241] 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.

[1242] 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.

[1243] 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.

[1244] 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.

[1245] 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.

[1246] 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."

[1247] An embodiment of the present invention is a system for matching candidates with companies in a fairer and more efficient manner. This system includes the following elements.

[1248] 1. User Interface Methods

[1249] Users access the system using a web browser or a dedicated application and log in by entering their authentication information (ID and password).

[1250] The server checks the user's authentication information against a database, and if authentication is successful, displays the user's dashboard screen.

[1251] 2. Interaction Module Means

[1252] The device displays a "Start Dialogue" button on the dashboard screen, and when the user clicks it, the AI ​​dialogue module is launched.

[1253] The server sends the candidate an initial question (e.g., "Please tell us about yourself") and receives the user's answer.

[1254] 3. Skills Assessment Tools

[1255] The server presents candidates with skill tests and challenges through an interactive module, including programming problems and logic puzzles.

[1256] The user works on the displayed tasks and enters their answers.

[1257] The terminal transmits the user's answer to the server.

[1258] 4. Biometrics Collection Methods

[1259] The device collects biometric data from the user through wearable devices and cameras, including heart rate, facial expression changes, and reaction speed.

[1260] The server receives this data in real time and records it in a database.

[1261] 5. Data Analysis Methods

[1262] The server integrates the collected skill test answer data and biometric data and performs analysis using a data analysis module.

[1263] The data analysis module assesses candidates' skills, aptitudes, and personality, records the results, and also uses generative artificial intelligence (AI) to assess their potential and future prospects.

[1264] 6. Matching Methods

[1265] The matching module (server) compares the candidate evaluation results with the company's job information to make the best match.

[1266] The server notifies the user and the company of the matching results.

[1267] Specific examples

[1268] For example, when a user logs into the system, a dialogue module is launched and they are asked to introduce themselves. The user then takes a skill test and solves programming problems and logic puzzles. During this time, the device continues to collect the user's heart rate and facial expression changes. The data analysis module analyzes this data and provides an overall evaluation of the user. Finally, the matching module compares the evaluation results with the needs of companies and suggests the most suitable company to the user. This series of processes ensures bias-free and objective recruitment.

[1269] The above is an embodiment of the present invention, which enables companies to efficiently recruit suitable personnel for the long term.

[1270] The processing flow will be explained below.

[1271] Step 1:

[1272] Users access the system using a web browser or a dedicated application and log in by entering their ID and password.

[1273] Step 2:

[1274] The terminal transmits the input authentication information to the server.

[1275] Step 3:

[1276] The server checks the authentication information against a database, and if authentication is successful, generates a dashboard screen for the user and sends it to the terminal.

[1277] Step 4:

[1278] The terminal displays a dashboard screen to the user.

[1279] Step 5:

[1280] The user clicks the "Start conversation" button on the dashboard.

[1281] Step 6:

[1282] The server launches an AI dialogue module, generates an initial question for the candidate, and sends it to the terminal.

[1283] Step 7:

[1284] The terminal displays the initial question sent from the server (e.g., "Please introduce yourself") to the user.

[1285] Step 8:

[1286] The user inputs the answer to the question and sends it to the server via the terminal.

[1287] Step 9:

[1288] The server receives the user's answer, generates the next question or challenge, and sends it to the terminal.

[1289] Step 10:

[1290] The device displays the next question or challenge (e.g., a skills test question) to the user.

[1291] Step 11:

[1292] The user solves the problem and sends the answer to the server via the terminal.

[1293] Step 12:

[1294] The terminal transmits the user's answers to the server, and at the same time collects the user's biometric data (e.g., heart rate, facial expression changes) and transmits it to the server in real time.

[1295] Step 13:

[1296] The server records the received answer data and biometric data in a database.

[1297] Step 14:

[1298] The data analysis module (server) analyzes this data and makes a comprehensive assessment of the candidate's skills, aptitude, personality, potential, and future prospects.

[1299] Step 15:

[1300] The server generates and sends the evaluation results to the matching module.

[1301] Step 16:

[1302] The matching module (server) compares the evaluation results with company job information to make the best match.

[1303] Step 17:

[1304] The server generates data for notifying the user and the company of the matching results and transmits the data to the terminal.

[1305] Step 18:

[1306] The device displays the matching results to the user, and the results are also notified to the company's recruiting staff.

[1307] Example 1

[1308] 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."

[1309] In the modern recruitment process, matching between candidates and companies is often influenced by subjective factors, making it difficult to achieve fair and efficient matching. Furthermore, there is a need to evaluate not only candidates' skills and aptitude, but also their potential and future prospects. Current technology lacks a system that can comprehensively evaluate these factors and achieve optimal matching, so this problem needs to be solved.

[1310] 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.

[1311] In this invention, the server includes a user interface means, a dialogue module means for dialogue with candidates, a skill evaluation means for evaluating the skills of the candidates, a biometrics collection means for collecting biometric data of the candidates, a data analysis means for analyzing the collected biometric data and the skill evaluation results to evaluate the aptitude and personality of the candidates, and a matching means for matching the evaluation results with the needs of companies, thereby enabling fair and efficient matching of candidates and companies.

[1312] The "user interface means" is a means by which a user accesses the system, inputs authentication information, and performs various operations via the dashboard screen.

[1313] The "dialogue module means" is a module for dialogue with candidates, and is a means for presenting initial questions and skill test tasks and collecting responses from candidates.

[1314] A "skill assessment means" is a means for assessing the skills of a candidate, and is a means for presenting tasks such as programming problems and logic puzzles and accepting the candidate's answers.

[1315] "Biometrics collection means" means a means for collecting biometric data such as a candidate's heart rate, facial expression changes, reaction speed, etc. This includes wearable devices and cameras.

[1316] "Data Analysis Means" refers to means for integrating collected biometric data and skill assessment results to evaluate a candidate's aptitude and personality, including a data analysis module and a generative AI model.

[1317] "Matching methods" are methods for comparing candidate evaluation results with the needs of the company to achieve optimal matching. Based on the evaluation results, the company proposes the most suitable candidate.

[1318] A "generative artificial intelligence (AI) means" is a means that uses AI technology to assess a candidate's potential and future prospects.

[1319] An embodiment of the present invention is a system for matching candidates with companies in a fairer and more efficient manner. This system includes the following elements.

[1320] 1. User Interface Methods

[1321] A user accesses the system using a web browser or a dedicated application and enters authentication information (ID and password) to log in. The server checks the user's authentication information against a database (e.g., MySQL database), and if authentication is successful, displays the user's dashboard screen.

[1322] 2. Interaction Module Means

[1323] The terminal displays a "Start Dialogue" button on the dashboard screen, and when the user clicks it, the AI ​​dialogue module is launched. The server sends the first question to the candidate (e.g., "Please introduce yourself") and receives the user's answer.

[1324] 3. Skills Assessment Tools

[1325] The server presents skill tests and challenges to the candidate through the dialogue module, such as programming problems and logic puzzles. The user works through the challenges displayed and enters their answers. The terminal then transmits the user's answers to the server.

[1326] 4. Biometrics Collection Methods

[1327] The terminal collects biometric data from the user through a wearable device or camera, including heart rate, facial expression changes, reaction speed, etc. The server receives this data in real time and records it in a database.

[1328] 5. Data Analysis Methods

[1329] The server integrates the collected skill test answer data and biometric data and analyzes them using a data analysis module. The data analysis module evaluates the candidate's skills, aptitude, and personality, and records the evaluation results. It also evaluates the candidate's potential and future prospects using generative artificial intelligence (AI) methods. This data analysis module can be implemented using Python and the scikit-learn library.

[1330] 6. Matching Methods

[1331] The matching module (server) compares the candidate's evaluation results with the company's job information to find the best match. The server then notifies the user and the company of the matching results. Notification can be via email or in-system messages.

[1332] Specific examples

[1333] For example, when a user logs into the system, the server displays a dashboard screen after authentication. The terminal then displays a "Start Dialogue" button, and when the user clicks it, the server sends a message saying, "Please introduce yourself." When the user enters their answers to a skill test, the data is sent to the server. The terminal also collects the user's real-time biometric data and sends it to the server. Finally, the server analyzes this data, performs optimal matching with companies, and notifies the user and company of the results.

[1334] Prompt Sentence Examples

[1335] "Please introduce yourself."

[1336] "Solve a programming problem. Example: Predict the output of the following code."

[1337] "Please relax as we will be recording your heart rate and facial expressions."

[1338] The above is an embodiment of the present invention, which realizes fair and efficient matching between candidates and companies. Furthermore, the various means included in the system work in conjunction with each other to provide highly accurate evaluation and optimal matching.

[1339] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1340] Step 1:

[1341] A user accesses the system using a web browser or a dedicated application. As input, the user enters an ID and password and attempts to log in to the system. As output, an authentication request is generated and sent to the server.

[1342] Step 2:

[1343] The server compares the received authentication information with the information stored in a database (for example, a MySQL database). This process involves searching the database for the relevant user information and verifying that it matches the entered ID and password. The output is an authentication result (success or failure).

[1344] Step 3:

[1345] If authentication is successful, the server displays the user's dashboard screen. If there is an error message, it notifies the user. The server makes a decision based on the authentication result as input, and generates the next screen information to be displayed as output.

[1346] Step 4:

[1347] The terminal displays a "Start Interaction" button on the dashboard screen. The configuration information of the dashboard screen is read as input, and the "Start Interaction" button is displayed on the user interface as output.

[1348] Step 5:

[1349] The user clicks the "Start Interaction" button, which generates a click event as input and sends a request to the server to start an interaction as output.

[1350] Step 6:

[1351] The server starts the AI ​​dialogue module and sends the first question (e.g., "Please introduce yourself") to the user. It receives a click event as input and generates a prompt sentence as output, which is sent to the user's device.

[1352] Step 7:

[1353] The user answers the first question by entering the answer text as input, and the answer is sent to the server as output.

[1354] Step 8:

[1355] The server records the received answers in a database. It receives the candidate's answer data as input and generates a request to save the answer contents in a database as output.

[1356] Step 9:

[1357] The server presents the candidate with the next skill test or challenge through a dialogue module, which can include programming questions, logic puzzles, etc. It receives triggers from previous answers as input and generates the next challenge as output, which it then sends to the user.

[1358] Step 10:

[1359] The user works on the displayed assignment and inputs the answer. The assignment content is read as input, and the answer is generated as output and sent to the server.

[1360] Step 11:

[1361] The terminal sends the user's answer to the server, which takes the answer data as input and generates a request to send it as output.

[1362] Step 12:

[1363] The terminal collects biometric data through a wearable device or camera attached to the user, including heart rate, facial expression changes, reaction speed, etc. It receives sensor data as input and transmits it to a server in real time as output.

[1364] Step 13:

[1365] The server receives the collected biometric data in real time and records it in a database. It receives the biometric data stream as input and generates a request to store the data in a database as output.

[1366] Step 14:

[1367] The server integrates the collected skill test answer data and biometric data and performs analysis using a data analysis module. It reads the integrated data as input and generates evaluation results as output.

[1368] Step 15:

[1369] The data analysis module evaluates the candidate's skills, aptitude, and personality, and records the evaluation results. Furthermore, it uses a generative AI model to evaluate the candidate's potential and future prospects. Each piece of data is analyzed as input, and a comprehensive evaluation result is generated as output.

[1370] Step 16:

[1371] The matching module (server) compares the candidate evaluation results with the company's job information to make the best match. It receives the evaluation results and the company's needs as input, and generates and notifies the matching results as output.

[1372] Step 17:

[1373] The server notifies users and companies of the matching results via email or internal system messages. Based on the matching results as input, notifications are generated and sent as output.

[1374] Through the above processing steps, the present invention achieves fair and efficient matching between candidates and companies.

[1375] (Application example 1)

[1376] 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."

[1377] Traditional staff recruitment and evaluation processes in brick-and-mortar stores require a lot of time and effort, and are prone to subjective bias. Furthermore, it is often difficult to accurately assess candidates' skills and aptitude, making it difficult to efficiently hire the best talent. Furthermore, traditional methods make it difficult to utilize biometric data, such as a candidate's stress level or reaction speed.

[1378] 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.

[1379] In this invention, the server includes a dialogue module means for dialogue with candidates, a skill evaluation means for evaluating the skills of the candidates, a biometrics collection means for collecting biometric data of the candidates, a data analysis means for analyzing the collected biometric data and the skill evaluation results and evaluating the aptitude and personality of the candidates, a matching means for matching the evaluation results with the needs of the company, a means for streamlining the staff recruitment and evaluation process for the brick-and-mortar store, a means for collecting biometric data using a smartphone camera or a wearable device, and a means for collecting input from the candidates and providing a user interface. This enables an integrated evaluation of the skills and biometric data of candidates and enables efficient and fair hiring of the best talent.

[1380] An "interaction module" is a component that interacts with candidates, generates questions, and collects answers.

[1381] A "skills assessment tool" is a tool that presents tests or tasks to assess candidates' skills and collects the results.

[1382] "Biometrics collection means" refers to a device or system that collects biometric data such as a candidate's heart rate, facial expression changes, and reaction speed.

[1383] The "data analysis means" is a module that integrates the collected biometric data with the skill assessment results to evaluate the candidate's aptitude and personality.

[1384] A "matching method" is a system that compares the candidate evaluation results with the company's needs to make the optimal match.

[1385] "Means for streamlining the staff recruitment and evaluation process for brick-and-mortar stores" refers to tools and systems that automate and streamline the traditional staff recruitment and evaluation process.

[1386] "Means for collecting biometric data using a smartphone camera or a wearable device" refers to means for collecting biometric information such as heart rate, facial expression changes, and reaction speed using a smartphone camera or a wearable device.

[1387] The "means for providing a user interface" is a component that provides an interface for candidates to log in to the system and use various functions.

[1388] This invention is a system for making the staff recruitment and evaluation process in a brick-and-mortar store more efficient and fair. Below, we will explain in detail the program and processing method for realizing this system.

[1389] The server includes a dialogue module, a skill assessment unit, a biometrics collection unit, a data analysis unit, and a matching unit, which enable an integrated assessment of a candidate's skills and biometric data, thereby enabling efficient and fair recruitment of the most suitable personnel.

[1390] Hardware and software used

[1391] Smartphones: Use cameras and touchscreens to gather user input.

[1392] Wearable devices: Used to collect biometric data such as heart rate, facial expression changes, and reaction speed.

[1393] Server: Candidate data management and analysis is performed using the Django framework.

[1394] Client-side software: Building the user interface using React.

[1395] Processing Description

[1396] 1. Authentication and Login

[1397] Users access the system using their smartphones and enter their authentication information (ID and password) to log in. The server compares this information with the database, and if authentication is successful, displays the user's dashboard screen.

[1398] 2. Starting the dialogue module

[1399] When a user clicks the "Start Dialogue" button on the dashboard screen, the dialogue module is launched. The server uses the generative AI model to generate an initial question (e.g., "Please introduce yourself") and sends it to the user.

[1400] Example prompt sentence:

[1401] "Generate the best questions for candidates to introduce themselves."

[1402] 3. Skills Assessment

[1403] Through the dialogue module, the server presents the candidate with skill tests and assignments. The user enters their answers using their smartphone, and this data is sent to the server, which stores the data and prepares it for analysis.

[1404] 4. Biometric Data Collection

[1405] Candidates wear wearable devices that collect real-time data such as heart rate, facial expression changes, and reaction time. Smartphone cameras may also be used. This data is sent to a server and recorded in a database.

[1406] 5. Data Analysis

[1407] The server integrates the collected skill test answer data and biometric data and performs analysis using a data analysis module, which also uses generative AI models to evaluate the candidate's skills, aptitude, personality, and potential and future prospects.

[1408] Example prompt sentence:

[1409] "Please rate the candidate's skill level based on their answers."

[1410] "Assess the candidate's stress level based on heart rate and facial expression changes."

[1411] 6. Matching

[1412] Finally, the server uses a matching module to compare the evaluation results with the needs of the company and make the best match, which is then notified to the user and the company.

[1413] This system streamlines the hiring process for brick-and-mortar stores and ensures unbiased and fair evaluations.

[1414] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1415] Step 1:

[1416] Users access the system using their smartphones and log in by entering their authentication information (ID and password). The server checks the user's authentication information against the database, and if authentication is successful, displays the user's dashboard screen. The input here is the user's ID and password, and the output is the dashboard screen.

[1417] Step 2:

[1418] When a user clicks the "Start Dialogue" button on the dashboard screen, the server launches the dialogue module. The server uses a generative AI model to generate an initial question (e.g., "Please introduce yourself") and sends it to the user. The input here is the event of pressing the "Start Dialogue" button, and the output is the generated question.

[1419] Step 3:

[1420] The user uses a smartphone to input answers to questions sent from the server. The server receives the answers and stores them in a database. The input here is the user's answer, and the output is the saved answer data.

[1421] Step 4:

[1422] The server presents skill tests and assignments to the user through the dialogue module. The user answers these tests and assignments using their smartphone and sends the answers to the server, which receives them and stores them in a database. The input here is the answers to the skill tests and assignments, and the output is the stored skill assessment data.

[1423] Step 5:

[1424] The user wears a wearable device and uses the smartphone camera to collect biometric data. The collected data includes heart rate, facial expression changes, reaction speed, etc. The device transmits this biometric data to a server in real time. The input here is the collected biometric data, and the output is the data transmitted to the server.

[1425] Step 6:

[1426] The server integrates the collected skill assessment data and biometric data and performs analysis using a data analysis module. This analysis evaluates the candidate's skills, aptitude, and personality. It also evaluates the candidate's potential and future prospects using a generative AI model. The input here is the integrated skill assessment data and biometric data, and the output is the analysis results.

[1427] Step 7:

[1428] The server uses a matching module to compare the analysis results with the company's needs and make the best match. The matching results are notified to the user and the company. The input here is the analysis results and the company's needs, and the output is the matching results.

[1429] 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.

[1430] One embodiment of the present invention is a system for matching candidates with companies in a fairer and more efficient manner. The system incorporates an emotion engine that recognizes the user's emotions and can use emotion data to provide more accurate evaluations.

[1431] 1. User Interface Methods

[1432] Users access the system using a web browser or a dedicated application and log in by entering their ID and password.

[1433] The server checks the user's authentication information against a database, and if authentication is successful, generates a dashboard screen for the user and sends it to the terminal.

[1434] 2. Interaction Module Means

[1435] The device displays a "Start Dialogue" button on the dashboard screen, and when the user clicks it, the AI ​​dialogue module is launched.

[1436] The server generates an initial question for the candidate (e.g., "Please tell us about yourself") and sends it to the terminal.

[1437] 3. Skills Assessment Tools

[1438] The server presents candidates with skill tests and challenges through an interactive module, including programming problems and logic puzzles.

[1439] The user works on the displayed tasks and enters their answers.

[1440] The terminal transmits the user's answer to the server.

[1441] 4. Biometrics Collection Methods

[1442] The device collects biometric data from the user through wearable devices and cameras, including heart rate, facial expression changes, and reaction speed.

[1443] The server receives this data in real time and records it in a database.

[1444] 5. Emotional Engine Means

[1445] The terminal transmits the collected biometric data to the emotion engine.

[1446] The server analyzes the user's emotional state in real time using the emotion engine, and the resulting emotion data is provided to the data analysis means as part of the user's aptitude and personality evaluation.

[1447] 6. Data Analysis Methods

[1448] The server integrates the collected skill test answer data, biometric data, and emotion data provided by the emotion engine, and performs analysis using a data analysis module.

[1449] The data analysis module conducts a comprehensive assessment of the candidate's skills, aptitude, personality, potential and future prospects.

[1450] 7. Matching Methods

[1451] The matching module (server) compares the evaluation results with company job information to make the best match.

[1452] The server generates data for notifying the user and the company of the matching results and transmits the data to the terminal.

[1453] Specific examples

[1454] For example, when a user logs into the system, a dialogue module is launched and the user is asked to introduce themselves. The user then takes a skill test and solves programming problems and logic puzzles. During this time, the device continues to collect the user's heart rate and facial expression changes, and this data is analyzed in real time by the emotion engine. The emotion engine analyzes the user's emotional state (e.g., tension, relaxation) and provides the emotion data to the data analysis means. The data analysis module analyzes this data and performs an overall evaluation of the user. Finally, the matching module compares the evaluation results with the needs of companies and suggests the most suitable company to the user. Through this series of processes, bias-free and objective recruitment is achieved.

[1455] The above is an embodiment of the present invention, which enables companies to efficiently recruit suitable personnel for the long term.

[1456] The processing flow will be explained below.

[1457] Step 1:

[1458] Users access the system using a web browser or a dedicated application and log in by entering their ID and password.

[1459] Step 2:

[1460] The terminal transmits the input authentication information to the server.

[1461] Step 3:

[1462] The server checks the authentication information against a database, and if authentication is successful, generates a dashboard screen for the user and sends it to the terminal.

[1463] Step 4:

[1464] The terminal displays a dashboard screen to the user.

[1465] Step 5:

[1466] The user clicks the "Start conversation" button on the dashboard.

[1467] Step 6:

[1468] The server launches an AI dialogue module, generates an initial question for the candidate, and sends it to the terminal.

[1469] Step 7:

[1470] The terminal displays the initial question sent from the server (e.g., "Please introduce yourself") to the user.

[1471] Step 8:

[1472] The user inputs the answer to the question and sends it to the server via the terminal.

[1473] Step 9:

[1474] The server receives the user's answer, generates the next question or challenge, and sends it to the terminal.

[1475] Step 10:

[1476] The device displays the next question or challenge (e.g., a skills test question) to the user.

[1477] Step 11:

[1478] The user solves the problem and sends the answer to the server via the terminal.

[1479] Step 12:

[1480] The terminal transmits the user's answers to the server, and at the same time collects the user's biometric data (e.g., heart rate, facial expression changes) and transmits it to the server in real time.

[1481] Step 13:

[1482] The server records the received answer data and biometric data in a database.

[1483] Step 14:

[1484] The terminal transmits the collected biometric data to the emotion engine.

[1485] Step 15:

[1486] The emotion engine (server) analyzes the user's emotional state in real time based on biometric data and generates emotion data.

[1487] Step 16:

[1488] The server transmits the emotion data and the answer data of the skill test to the data analysis module.

[1489] Step 17:

[1490] The data analysis module (server) analyzes this data and makes a comprehensive assessment of the candidate's skills, aptitude, personality, potential, and future prospects.

[1491] Step 18:

[1492] The server sends the evaluation results to the matching module.

[1493] Step 19:

[1494] The matching module (server) compares the evaluation results with company job information to make the best match.

[1495] Step 20:

[1496] The server generates data for notifying the user and the company of the matching results and transmits the data to the terminal.

[1497] Step 21:

[1498] The device displays the matching results to the user, and the results are also notified to the company's recruiting staff.

[1499] Example 2

[1500] 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."

[1501] In conventional recruitment systems, matching candidates with companies relied on subjective evaluations, making it difficult to efficiently find the best talent. Furthermore, aptitude assessment based not only on the content of candidates' responses, but also on their emotional state and biometric data was not adequately conducted. Therefore, there was a need for a system that comprehensively evaluates candidates' potential and future prospects, and matches them fairly and efficiently with the needs of companies.

[1502] 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.

[1503] In this invention, the server includes authentication means for verifying authentication information, dialogue means for dialogue with the candidate, ability evaluation means for evaluating the candidate's abilities, biometric information collection means for collecting the candidate's biometric information, information analysis means for analyzing the collected biometric information and the ability evaluation results to evaluate the candidate's aptitude and personality, and matching means for matching the evaluation results with job requirements. This enables bias-free evaluation that eliminates subjectivity and realizes optimal matching between candidates and companies.

[1504] The "authentication means" is a function for verifying the user's authentication information and confirming legitimate access rights.

[1505] "Interaction means" refers to an interface for exchanging information between candidates and the system.

[1506] "Competency assessment tools" are functions for assessing candidates' skills and knowledge.

[1507] "Biometric information collection means" is a function for collecting biometric data such as the candidate's heart rate and facial expression changes.

[1508] "Information analysis means" is a function that integrates collected biometric information with the results of ability assessments to evaluate the suitability and personality of candidates.

[1509] "Matching methods" are functions that use evaluation results to compare candidates with the needs of companies and make optimal matches.

[1510] The present invention relates to a system for matching candidates with companies in a fair and efficient manner. The system incorporates an emotion engine that recognizes the emotions of candidates and can provide more accurate evaluations by utilizing emotion data.

[1511] The system is implemented using the following hardware and software:

[1512] Hardware

[1513] Server: A cloud-based server (e.g., AWS, Google Cloud) can be used. The server includes functions for user authentication, database management, execution of AI dialogue modules, and execution of data analysis.

[1514] Terminal: This refers to a user's PC, tablet, smartphone, etc. The system is accessed through a web browser or dedicated application.

[1515] Wearable device: A device used to collect biometric data about a user (e.g., smartwatch, fitness tracker).

[1516] software

[1517] Sentiment engine: AI tools and libraries for sentiment analysis (e.g., TensorFlow, PyTorch).

[1518] Data Analysis Module: Analysis software for integrating multiple data sets and evaluating candidates.

[1519] Specific operating procedures for the system

[1520] 1. User authentication: A user accesses the system using a web browser or a dedicated app and logs in by entering their ID and password. The server receives this authentication information and compares it with the data stored in the database. If authentication is successful, the user's dashboard screen is generated and sent to the terminal.

[1521] 2. Starting a conversation: The terminal displays a "Start conversation" button on the dashboard screen, and when the user clicks it, the conversation module starts. The server generates an initial question (e.g., "Please introduce yourself") and sends it to the terminal. The terminal displays the received question to the user.

[1522] 3. Skill Assessment: The server presents skill tests and challenges to the user through the dialogue module. The user tackles the problems and enters the answers, which are then sent to the server. The server stores the answers in a database and begins analyzing them as part of the skill assessment.

[1523] 4. Biometric data collection: The terminal collects biometric data such as heart rate, facial expression changes, and reaction speed through the wearable device and camera attached to the user. The server receives this data in real time and records it in a database.

[1524] 5. Emotion Analysis: The terminal sends the collected biometric data to the emotion engine. The server uses the emotion engine to analyze the user's emotional state in real time. The resulting emotion data is provided to the data analysis means as part of the user's aptitude and personality assessment.

[1525] 6. Data integration and analysis: The server integrates the collected skill test answer data, biometric data, and emotional data provided by the emotion engine and records them in a database. The data analysis module comprehensively analyzes this data and performs a subjective evaluation of the candidate, including an evaluation of skills, aptitude, personality, potential, and future prospects.

[1526] 7. Matching: The matching module compares the evaluation results with the company's job information and proposes the most suitable candidates to the company. The server generates data to notify the user and the company of the matching results and sends it to the terminal. The terminal displays the received matching results to the user.

[1527] Examples of concrete examples and prompts

[1528] For example, when a user logs into the system, the dialogue module is activated and the first question displayed is, "Please introduce yourself." The user then attempts skill tests such as programming problems and logic puzzles. In parallel, the device continues to collect the user's heart rate and facial expression changes, and this data is analyzed in real time by the emotion engine. The emotion data is provided to the data analysis means, which performs a comprehensive evaluation. Finally, the matching module compares the needs of companies with the evaluation results and suggests the most suitable companies to the user.

[1529] Example prompt sentence:

[1530] "Please explain the process by which a user logs in and an interaction module is initiated."

[1531] "Please explain with examples how the system works when a user completes a skills test."

[1532] "Please explain how the emotion engine analyzes biometric data and how the results of this analysis are used in the evaluation."

[1533] "Please explain how the matching module uses the assessment results to match with company job openings."

[1534] The above is an embodiment of the present invention, and this system makes it possible to optimally match companies with suitable candidates in a fair and efficient manner.

[1535] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1536] Step 1:

[1537] User authentication: The user accesses the system using a web browser or a dedicated app and logs in by entering their ID and password. The server receives this authentication information and compares it with the authentication information stored in the database. If authentication is successful, the server generates the user's dashboard screen and sends it to the terminal. The terminal displays the dashboard screen received from the server to the user.

[1538] Input: User ID and password

[1539] Data processing: Verification against the server database

[1540] Output: Dashboard screen

[1541] Step 2:

[1542] Activating the dialogue module: The terminal displays a "Start dialogue" button on the dashboard screen. When the user clicks the "Start dialogue" button, the server's dialogue module is activated, which generates the first question (e.g., "Please introduce yourself") and sends it to the terminal. The terminal then displays the received question to the user.

[1543] Input: User clicks

[1544] Data processing: The server generates the initial question

[1545] Output: Question

[1546] Step 3:

[1547] Skill assessment: The server presents skill tests and challenges (e.g., programming problems, logic puzzles) to the user through the dialogue module. The user works on the challenges and enters their answers. The device sends the user's answers to the server. The server stores the received answers in a database and begins analyzing them as part of the skill assessment.

[1548] Input: User's answer

[1549] Data processing: The server evaluates the answers

[1550] Output: Evaluation result

[1551] Step 4:

[1552] Biometric data collection: The terminal collects biometric data such as heart rate, facial expression changes, and reaction speed through a wearable device or camera attached to the user. The server receives this data in real time and records it in a database.

[1553] Input: Data from wearable devices and cameras

[1554] Data processing: The server records the data

[1555] Output: Recorded biometric data

[1556] Step 5:

[1557] Emotion analysis: The terminal sends the collected biometric data to the emotion engine on the server. The server uses the emotion engine to analyze the user's emotional state (e.g., tension, relaxation). The resulting emotion data is provided to the data analysis means as part of the user's aptitude and personality assessment.

[1558] Input: Biometric data

[1559] Data processing: Data analysis using emotion engines

[1560] Output: Emotion data

[1561] Step 6:

[1562] Data integration and analysis: The server integrates the collected skill test answer data, biometric data, and emotion data provided by the emotion engine, and records them in a database. The data analysis module comprehensively analyzes this data and makes a comprehensive evaluation of the candidate's skills, aptitude, personality, potential, and future prospects.

[1563] Input: Skill test answer data, biometric data, emotion data

[1564] Data processing: Comprehensive data analysis

[1565] Output: Overall evaluation result

[1566] Step 7:

[1567] Matching: The server's matching module compares the evaluation results with the company's job information to make the best match. The server generates data to notify the user and the company of the matching results and sends it to the device. The device then displays the received matching results to the user.

[1568] Input: Overall evaluation results, company job information

[1569] Data processing: Matching algorithm

[1570] Output: Matching results

[1571] Through these steps, a fair and efficient matching system will be realized, which will enable optimal matching between companies and suitable candidates.

[1572] (Application example 2)

[1573] 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."

[1574] Traditional candidate-to-company matching systems rely on superficial skills and resume information, failing to fully grasp a candidate's emotional state, aptitude, or personality. Furthermore, it's difficult to assess a candidate's potential through skill assessment alone, making it difficult to find the best candidate who best meets a company's needs. Furthermore, candidate authentication and dialogue based on fixed questions fail to capture the candidate's true character, potentially resulting in mismatches.

[1575] 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.

[1576] In this invention, the server includes a dialogue module means for dialogue with candidates, a skill assessment means for assessing the candidates' skills, a biometrics collection means for collecting the candidates' biometric data, a data analysis means for analyzing the collected biometric data and the skill assessment results to assess the candidates' aptitude and personality, a matching means for matching the assessment results with the company's needs, and an emotion engine means for analyzing the collected biometric data in real time and assessing the candidates' emotional state. This enables real-time assessment of the candidates' emotional state and aptitude, enabling more appropriate and efficient matching. Furthermore, by using a generative model means, it is possible to evaluate the candidates' potential and future potential and find talent that is suitable for the company in the long term. Furthermore, a dialogue generation means is used to generate prompt sentences, allowing the candidate's true character to be captured through more personalized dialogue.

[1577] The "interaction module means" is a means for providing an interface and functionality for a candidate to interact with the system.

[1578] A "skills assessment instrument" is an instrument that has the means and function to assess a candidate's technical and professional competence.

[1579] "Biometrics collection means" refers to means including devices and technologies for collecting biometric information such as a candidate's heart rate and facial expression changes.

[1580] "Data analysis means" refers to means having algorithms and functions for analyzing collected biometric data and skill assessment results and evaluating the aptitude and personality of candidates.

[1581] A "matching tool" is a tool that has the method and function to compare the evaluation results with the needs of the company and select the most suitable candidate.

[1582] "Emotion engine means" means means having algorithms and techniques for analyzing collected biometric data in real time and assessing the emotional state of a candidate.

[1583] A "generative modeling tool" is a tool that uses generative artificial intelligence (AI) to assess a candidate's potential and future prospects.

[1584] "User Interface Means" means means for obtaining candidate authentication information and providing an interface for enabling access and operation of the system.

[1585] A "dialogue generation means" is a means having a language model and technology for generating appropriate questions and responses when a candidate and the system interact.

[1586] The present invention provides a system for matching candidates with companies more fairly and efficiently, which includes a dialogue module, a skill assessment means, a biometrics collection means, a data analysis means, a matching means, an emotion engine means, a generative model means, a user interface means, and a dialogue generation means.

[1587] System Program

[1588] 1. Log in and create a dashboard

[1589] The user logs in using a smartphone app or smart glasses with an ID and password. The server checks the authentication information against a database, and if authentication is successful, a dashboard screen is generated and sent to the user's device.

[1590] 2. Starting a dialogue

[1591] When the user taps the "Start Dialogue" button on the dashboard screen, the server starts the dialogue module means, generates an initial question, and sends it to the user. For example, a prompt such as "Please introduce yourself" is presented.

[1592] 3. Skills Assessment and Biometrics Collection

[1593] The server uses the skill assessment tool to present skill tests and tasks (e.g., programming problems and logic puzzles) to the candidates, while collecting biometric data (e.g., heart rate, facial expression changes) from the user's device (e.g., smart glasses or smartphone camera).

[1594] 4. Analysis by Emotion Engine

[1595] The collected biometric data is transmitted in real time to an emotion engine means, which analyzes the candidate's emotional state (e.g., nervous, relaxed) and provides the results to a data analysis means.

[1596] 5. Data analysis and matching

[1597] The server integrates the skill assessment results, biometric data, and emotional data, and uses data analysis means to evaluate the candidate's aptitude and personality. The assessment results are compared with the company's needs by a matching means to find the optimal match. The results are then notified to the user and the company.

[1598] Hardware and Software

[1599] Hardware:

[1600] Smartphone (e.g. iPhone, Android)

[1601] Smart glasses (e.g. Google Glass)

[1602] Wearable devices (e.g., Apple Watch)

[1603] software:

[1604] Frontend: React Native (smartphone app), WebRTC (video calling)

[1605] Backend: Node.js, Express.js

[1606] Database: MongoDB

[1607] Emotion engine: Affectiva SDK

[1608] Data analysis: Python (numpy, pandas, scikit-learn)

[1609] Examples and prompts

[1610] Specific examples

[1611] For example, when a user logs in and starts an interactive module, the following prompt is displayed:

[1612] "Please introduce yourself."

[1613] Please solve the following programming problems.

[1614] "Are you nervous? Just relax a bit."

[1615] While the user inputs and performs operations according to these prompts, the device collects the user's biometric information, which is then analyzed by the server in real time. This allows for a more comprehensive and accurate evaluation, and the results are used to match the user with the appropriate company.

[1616] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1617] Processing step details

[1618] Step 1:

[1619] The user enters their ID and password using a smartphone app or smart glasses to access the login screen. The server checks the authentication information against the database. The ID and password are required as input, and if authentication is successful by checking these data, the server generates a dashboard screen and sends it to the terminal. The dashboard screen is displayed to the user as output.

[1620] Step 2:

[1621] The user taps the "Start Dialogue" button on the dashboard screen. This causes the server to start the dialogue module means, generate the first question, and send it. The user's operation is input, and the server outputs the generated prompt sentence "Please introduce yourself," and displays it on the terminal.

[1622] Step 3:

[1623] The server uses the skill assessment means to present skill tests and tasks to candidates. As input, the server receives the information and requests provided by the user in the dialogue, and as output, it generates skill tests such as programming problems and logic puzzles and sends them to the terminal. The user works on these and enters the answers into the terminal.

[1624] Step 4:

[1625] While the user is taking the skill test, the device collects biometric data through a biometric collection means. For example, it uses smart glasses or a smartphone camera to monitor heart rate and facial expression changes. The input is real-time data from the camera or sensor, and the output is sent to a server.

[1626] Step 5:

[1627] The server sends the collected biometric data to the emotion engine means for real-time analysis. The input includes biometric information such as heart rate and facial expression changes, and the emotion engine analyzes the user's emotional state based on this data. The output is an analysis result (e.g., tension, relaxation).

[1628] Step 6:

[1629] The server integrates the analysis results from the emotion engine means, the answer data of the skill test, and the biometric data, and evaluates the aptitude and personality of the candidate using the data analysis means. All of these data are integrated as input, and a comprehensive evaluation result is generated as output.

[1630] Step 7:

[1631] The server assesses the candidate's potential and future potential using generative modeling tools, with the integrated data and generative AI model as inputs and a long-term candidate suitability assessment as output.

[1632] Step 8:

[1633] The server uses a matching method to compare the evaluation results with the needs of the company and perform optimal matching. The inputs are the candidate's overall evaluation results and the company's job information, and the output is a list of optimal candidates that is notified to the user and the company.

[1634] By following these steps, we can evaluate the candidate's emotional state and aptitude in real time, enabling more appropriate and efficient matching. Furthermore, by using generative models, we can evaluate the candidate's potential and future prospects and find the right fit for the company in the long term. Furthermore, by using dialogue generation, we can generate prompts to capture the candidate's true personality through more personalized dialogue.

[1635] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1636] 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.

[1637] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1638] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1639] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1640] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1641] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1642] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1643] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1644] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1645] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1646] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1647] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1648] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1649] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1650] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1651] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1652] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1653] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1654] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1655] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1656] The following is further disclosed regarding the above embodiment.

[1657] (Claim 1)

[1658] a dialogue module means for dialogue with the candidate;

[1659] a skills assessment instrument for assessing the skills of candidates;

[1660] a biometric collection means for collecting biometric data of the candidate;

[1661] a data analysis means for analyzing the collected biometric data and the skill assessment results to evaluate the aptitude and personality of the candidate;

[1662] A system that includes a matching tool to match assessment results with the needs of companies.

[1663] (Claim 2)

[1664] 10. The system of claim 1, further comprising a generative artificial intelligence (AI) means for assessing the potential and prospects of the candidate.

[1665] (Claim 3)

[1666] 10. The system of claim 1, further comprising user interface means for obtaining candidate authentication information and providing a dashboard view.

[1667] "Example 1"

[1668] (Claim 1)

[1669] user interface means;

[1670] a dialogue module means for dialogue with the candidate;

[1671] a skills assessment instrument for assessing the skills of candidates;

[1672] a biometric collection means for collecting biometric data of the candidate;

[1673] a data analysis means for analyzing the collected biometric data and the skill assessment results to evaluate the aptitude and personality of the candidate;

[1674] A system that includes a matching tool to match assessment results with the needs of companies.

[1675] (Claim 2)

[1676] 10. The system of claim 1, further comprising a generative artificial intelligence (AI) means for assessing the potential and prospects of the candidate.

[1677] (Claim 3)

[1678] 10. The system of claim 1, further comprising user interface means for obtaining candidate authentication information and providing a dashboard view.

[1679] "Application Example 1"

[1680] (Claim 1)

[1681] a dialogue module means for dialogue with the candidate;

[1682] a skills assessment instrument for assessing the skills of candidates;

[1683] a biometric collection means for collecting biometric data of the candidate;

[1684] a data analysis means for analyzing the collected biometric data and the skill assessment results to evaluate the aptitude and personality of the candidate;

[1685] A matching method for matching the evaluation results with the needs of the company;

[1686] Measures to streamline the hiring and evaluation process for brick-and-mortar staff;

[1687] A means for collecting biometric data using a smartphone camera or a wearable device;

[1688] A system including means for collecting input from candidates and providing a user interface.

[1689] (Claim 2)

[1690] 10. The system of claim 1, further comprising a generative artificial intelligence (AI) means for assessing the potential and prospects of the candidate.

[1691] (Claim 3)

[1692] 10. The system of claim 1, further comprising user interface means for obtaining candidate authentication information and providing a dashboard view.

[1693] "Example 2: Combining Emotion Engines"

[1694] (Claim 1)

[1695] an authentication means for verifying the authentication information;

[1696] A means of dialogue to engage in dialogue with candidates;

[1697] a competency assessment instrument for assessing the candidate's competency;

[1698] a biometric information collection means for collecting biometric information of the candidate;

[1699] an information analysis means for analyzing the collected biometric information and ability assessment results and evaluating the aptitude and personality of the candidate;

[1700] A system including a matching means for matching assessment results with job requirements.

[1701] (Claim 2)

[1702] 10. The system of claim 1, further comprising a generative artificial intelligence (AI) means for assessing the potential and prospects of candidates.

[1703] (Claim 3)

[1704] 10. The system of claim 1, further comprising user interface means for providing a candidate dashboard view.

[1705] "Application example 2 when combining emotion engines"

[1706] (Claim 1)

[1707] a dialogue module means for dialogue with the candidate;

[1708] a skills assessment instrument for assessing the skills of candidates;

[1709] a biometric collection means for collecting biometric data of the candidate;

[1710] a data analysis means for analyzing the collected biometric data and the skill assessment results to evaluate the aptitude and personality of the candidate;

[1711] A matching method for matching the evaluation results with the needs of the company;

[1712] The system includes an emotion engine means for analyzing collected biometric data in real time to assess emotional state.

[1713] (Claim 2)

[1714] 10. The system of claim 1, further comprising generative model means for assessing the potential and prospects of candidates.

[1715] (Claim 3)

[1716] 10. The system of claim 1, further comprising: a user interface means for acquiring candidate authentication information and providing a dashboard screen; and a dialogue generation means for generating prompt sentences during dialogue with the candidate. [Explanation of symbols]

[1717] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a dialogue module means for dialogue with the candidate; a skills assessment instrument for assessing the skills of candidates; a biometric collection means for collecting biometric data of the candidate; a data analysis means for analyzing the collected biometric data and the skill assessment results to evaluate the aptitude and personality of the candidate; A system that includes a matching tool to match assessment results with the needs of companies.

2. 10. The system of claim 1, further comprising a generative artificial intelligence (AI) means for assessing the potential and prospects of candidates.

3. 10. The system of claim 1, further comprising user interface means for obtaining candidate authentication information and providing a dashboard view.

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