Job matching methods in augmented reality space

Abstract

To provide a job matching method by which a talented individual can be predicted from among unspecified individuals.SOLUTION: A job matching method for evaluating individuals in an augmented reality space, includes steps of: receiving image data and / or voice data regarding an individual displayed in a captured real space S101; analyzing the received image data and / or voice data S102; generating evaluation information regarding the individual on the basis of the analyzed image data and / or voice data S103; and displaying the generated evaluation information along with the individual in the captured real space S104.SELECTED DRAWING: Figure 7

Description

Technical Field

[0001] The present invention relates to a job matching method in an extended reality space. Relates to a method.

Background Art

[0002] Conventionally, various methods have been used as human resource evaluation methods.

[0003] For example, in Patent Document 1, a method for predicting the performance of a human resource based on feature information such as aptitude test results and achievement information such as evaluations by superiors is disclosed.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, although the method disclosed in Patent Document 1 can realize predicting the performance of a specific human resource based on the information obtained in advance about that human resource, it is difficult to discover excellent human resources from among unspecified human resources.

[0006] Therefore, an object of the present invention is to provide a method for predicting excellent human resources from among unspecified human resources.

Means for Solving the Problems

[0007] In one embodiment of the present invention, a job matching method for evaluating personnel in an augmented reality space is provided, comprising: receiving image data and / or audio data of a person displayed in an captured real space; generating evaluation information of the person based on the received image data and / or audio data; and displaying the evaluation information together with the person in the captured real space. [Effects of the Invention]

[0008] According to the present invention, it is possible to provide a method for predicting outstanding individuals from an unspecified pool of people. [Brief explanation of the drawing]

[0009] [Figure 1] A system configuration diagram according to the first embodiment is shown. [Figure 2] A diagram showing the functional configuration of the server according to the first embodiment is shown. [Figure 3] A diagram showing the functional configuration of a user terminal according to the first embodiment is shown. [Figure 4] A diagram showing the functional configuration of the recruiter terminal according to the first embodiment is shown. [Figure 5] An example of user data according to the first embodiment is shown. [Figure 6] An example of job seeker data according to the first embodiment is shown. [Figure 7] An example of a flowchart for a job matching method according to the first embodiment is shown. [Figure 8] An example of a screen displayed on the recruiter's terminal according to the first embodiment is shown. [Figure 9] An example of a flowchart for a job matching method according to the second embodiment is shown. [Figure 10] An example of a screen displayed on the recruiter's terminal according to the second embodiment is shown.

[0010] <First Embodiment> Specific examples of the job matching method according to the first embodiment of the present invention will be described below with reference to the drawings. However, the present invention is not limited to these examples, and is intended to include all modifications within the meaning and scope of the claims, as indicated by the claims. In the following description, the same elements in the drawings are denoted by the same reference numerals, and redundant descriptions are omitted.

[0011] Figure 1 shows a system configuration diagram according to a first embodiment of the present invention. As shown in Figure 1, the system according to this embodiment includes a server terminal 100 and user terminals 200 and recruiter terminals 300 connected to the server terminal 100 via a network such as the Internet. For the sake of explanation, Figure 1 shows representative examples of user terminals 200 and recruiter terminals 300, but any number of user terminals and recruiter terminals can be connected to the network. In this embodiment, the recruiter terminal 300 is assumed to be a smart glasses worn by a recruiter user that displays an augmented reality space via a display, but is not limited to this, and may be an information terminal such as a head-mounted display or a smartphone.

[0012] The server terminal 100 can provide a service to recruiter users wearing the recruiter terminal 200 that enables the generation of evaluation information for specific users from among the unspecified users (hereinafter referred to as "personnel") displayed in the real world, and displays the evaluation information along with the personnel.

[0013] For example, a job seeker can view evaluation information for each candidate, captured by the camera built into the smart glasses, while walking outside, via the display built into the smart glasses.

[0014] For example, an employer user can download this service application to the employer terminal 300 from the server terminal 100 or another platform, and can transmit and receive data related to the server terminal 100 and this service via the application. Alternatively, the employer user can also transmit and receive data related to this service by accessing the web application stored in the server terminal 100 through the web browser built into the employer terminal 300. In the following embodiments, as an example, a method for providing this service via the downloaded application will be described.

[0015] The user terminal 200 is assumed to be a terminal related to potential job seekers (described as "personnel" in this embodiment), and may be, for example, a smartphone, a tablet, a mobile terminal, or other information terminals, or may be a general-purpose computer such as a workstation or a personal computer.

[0016] The user terminal 200 is assumed to be a terminal related to potential job seekers (described as "personnel" in this embodiment), and may be, for example, a wearable device such as smart glasses or a head-mounted display that can be worn on the user's body. Alternatively, it may be a smartphone, a tablet, a mobile terminal, or other information terminals, or may be a general-purpose computer such as a workstation or a personal computer.

[0017] FIG. 2 shows a functional configuration diagram of the server according to the first embodiment. Note that the illustrated configuration is an example, and other configurations may be used.

[0018] As shown in the figure, the server terminal 100 is connected to a database (not shown) and constitutes a part of the system. The server terminal 100 may be a general-purpose computer such as a workstation or a personal computer, or may be logically realized by cloud computing.

[0019] The server terminal 100 includes at least a communication unit 110, a storage unit 120, a control unit 130, etc., which are electrically connected to each other via a bus.

[0020] The control unit 130 is a computing device that controls the operation of the entire server terminal 100, controls the transmission and reception of data between each element, and performs information processing necessary for application execution and authentication processing. For example, the control unit 10 is a CPU (Central Processing Unit) and executes programs stored and unpacked in the memory unit 120 to perform various information processing tasks.

[0021] The control unit 130 further includes an information receiving unit 131 that receives requests or data from a user terminal 200 or a recruiter terminal 300, an evaluation information generation unit 132 that analyzes image data or voice data of personnel and generates evaluation information of those personnel based on the analyzed image data, etc., and a matching processing unit 133 that processes matching between recruiters and personnel.

[0022] The storage unit 120 includes main memory, which is composed of a volatile storage device such as DRAM (Dynamic Random Access Memory), and auxiliary memory, which is composed of a non-volatile storage device such as flash memory or HDD (Hard Disk Drive). Memory 11 is used as a work area for the processor 10, and also stores the BIOS (Basic Input / Output System) executed when the server terminal 100 starts up, as well as various setting information. A database (not shown) storing data used for each process may also be built in the storage unit 120 or outside the server terminal 100.

[0023] The memory unit 120 further includes a user data storage unit 121 for storing data related to personnel, a recruiter data storage unit 122 for storing data related to recruiters, and a learning model storage unit 123 for storing learning models generated based on facial or appearance images and / or voices obtained from users.

[0024] The communication unit 110 connects the server terminal 100 to the network. The transmitting / receiving unit 13 may also be equipped with Bluetooth® and BLE (Bluetooth Low Energy) short-range communication interfaces.

[0025] Furthermore, the data stored or functions implemented by the server terminal 100 can be stored or implemented locally by the storage unit or control unit of the job seeker terminal 300.

[0026] Figure 3 shows a functional configuration diagram of a user terminal according to the first embodiment. Note that the illustrated configuration is just one example, and other configurations may be available.

[0027] As mentioned above, the user terminal 200 can be various information terminals or general-purpose computers, but below we will explain using a smartphone as an example. The user terminal 200 is equipped with at least a communication unit 210, a display and operation unit 220, a storage unit 230, a control unit 240, etc., which are electrically connected to each other via a bus.

[0028] The control unit 240 is a computing device that controls the operation of the entire user terminal 200, controls the transmission and reception of data between each element, and performs information processing necessary for application execution and authentication. For example, the control unit 240 is a CPU (Central Processing Unit) and executes programs stored and unpacked in the memory unit 230 to perform various information processing tasks.

[0029] The storage unit 240 includes main memory, which is composed of a volatile storage device such as DRAM (Dynamic Random Access Memory), and auxiliary memory, which is composed of a non-volatile storage device such as flash memory or HDD (Hard Disk Drive). The storage unit 240 is used as a work area for the control unit 240, and also stores the BIOS (Basic Input / Output System) that is executed when the user terminal 2 is started, as well as various setting information.

[0030] Furthermore, the storage unit 230 stores various programs, such as application programs. A database (not shown) containing data used for each process may be constructed outside the storage unit 230.

[0031] The communication unit 210 connects the user terminal 200 to the network. The transmitting / receiving unit 23 may also be equipped with Bluetooth® and BLE (Bluetooth Low Energy) short-range communication interfaces.

[0032] The display operation unit 220 is a user interface used for displaying text, images, etc., in response to input data from the control unit 240, based on instructions given by the user. If the terminal is configured as a personal computer, it consists of a display and a keyboard or mouse; if it is configured as a smartphone or tablet, it consists of a touch panel, etc. Through the display operation unit, the user can input predetermined information by pressing keys on the keyboard, moving the cursor with the mouse, or performing taps, swipes, pinches, etc., on the touch panel.

[0033] Figure 4 shows a functional configuration diagram of the job seeker terminal according to the first embodiment. Note that the illustrated configuration is just one example, and other configurations may be available.

[0034] As mentioned above, the job seeker terminal 300 can be various information terminals or general-purpose computers. Below, we will describe it using smart glasses, a glasses-like device that can be worn by a job seeker user, as an example, with the glasses portion acting as a display to show an augmented reality space. The job seeker terminal 300 includes at least a communication unit 310, a display 320, a storage unit 330, a camera 350, a control unit 360, etc., which are electrically connected to each other via a bus.

[0035] The control unit 360 is a computing device that controls the overall operation of the job seeker terminal 300, controls the transmission and reception of data between each element, and performs information processing necessary for application execution and authentication. For example, the control unit 360 is a CPU (Central Processing Unit) and executes programs stored and unpacked in the memory unit 330 to perform various information processing tasks.

[0036] The storage unit 330 includes main memory, which is composed of a volatile storage device such as DRAM (Dynamic Random Access Memory), and auxiliary memory, which is composed of a non-volatile storage device such as flash memory or HDD (Hard Disk Drive). The storage unit 240 is used as a work area for the control unit 240, and also stores the BIOS (Basic Input / Output System) that is executed when the user terminal 2 is started, as well as various setting information.

[0037] Furthermore, the storage unit 330 stores various programs, such as application programs. A database (not shown) containing data used for each process may be constructed outside the storage unit 330.

[0038] The communication unit 310 connects the job seeker terminal 300 to the network. The transmitting / receiving unit 23 may also be equipped with Bluetooth® and BLE (Bluetooth Low Energy) short-range communication interfaces.

[0039] The display 320 is a user interface used to display the real space captured by the camera 350 (described later), and is capable of overlaying data such as text and images onto the real space. In the case of smart glasses, the display 320 can be, for example, an LCD or an organic EL display, and the display 320 can also function as a viewfinder for the camera 350.

[0040] Furthermore, the job seeker terminal 300 is equipped with a camera 350. The camera 26 is built into the job seeker terminal 300, captures images of the real world, and is typically positioned to coincide with the line of sight of the job seeker user wearing the job seeker terminal 300.

[0041] Images of the real world captured by the camera 350 are combined with data such as text and images by an image control unit (not shown), and the text and images are superimposed on the images of the real world on the display 320. The image control unit is, for example, a GPU (Graphics Processing Unit) and mainly performs calculations related to image processing. The job seeker terminal 300 is also equipped with a microphone 370. The microphone 370 is built into the job seeker terminal 300 and can collect sound from the area around the terminal 300.

[0042] In addition, although not shown in the diagram, the job seeker terminal 300 may be equipped with a GPS (Global Positioning System) to determine its current location. The GPS receives positioning radio waves from GPS satellites and can determine latitude and longitude information, which constitutes the absolute position. It can also receive communication radio waves from multiple mobile phone base stations and determine its current location using a multi-base station positioning function. In addition, the job seeker terminal may be equipped with sensors such as an accelerometer and a geomagnetic sensor, although these are not shown in the diagram.

[0043] Figure 5 shows an example of user data stored in the server terminal 100.

[0044] The user data 1000 shown in FIG. 5 stores various data related to human resources. In FIG. 5, for the sake of convenience of explanation, an example of one human resource (the human resource identified by the user ID "10001") is shown, but information on multiple human resources can be stored. As various data related to human resources, for example, image data associated with the human resource (hereinafter, "image data" also includes moving image data), voice data, etc., evaluation information (information related to an evaluation indicating the market value of the human resource in the employment or job-hopping market), and other additional information (the name, contact information, profile (hobbies, skills, preferences, etc.), annual income, performance (achievements) in the current or past workplace, work history, resume, employment or job-hopping activity status (in the process of employment or job-hopping, employed or job-hopped, etc.), information related to aptitude (vitality, per capita, teamwork, creative thinking ability, problem-solving ability, etc.)) can be included. The above additional information can be stored as user data 1000 when the server terminal 100 receives information input or selected by the human resource via the user terminal 200 or information managed by applications such as SNS. Also, the learning model generated as learning data from the input by image data or voice data such as a face image or a portrait image associated with a human resource, which is obtained as user data 1000 and / or input by a job seeker, and the output by information managed as evaluation information and / or additional information can be stored in the learning model storage unit 123. Based on this learning model, evaluation information can also be generated based on new image data and / or voice data associated with a human resource.

[0045] FIG. 6 is a diagram showing an example of job seeker data stored in the server terminal 100.

[0046] The recruiter data 2000 shown in Figure 6 stores various data related to recruiters. In Figure 6, for the sake of explanation, an example of one recruiter (a recruiter identified by recruiter ID "20001") is shown, but information for multiple users can be stored. Various data related to recruiters can be stored, for example, basic information of the recruiter (company name, industry, date of establishment, location, number of employees, company website URL, other company introduction text, etc.), and job information (desired candidate profile, working hours, number of annual holidays, treatment (salary, etc.), welfare benefits, work location, contract type (employment (regular employee, contract employee), outsourcing, etc.)). In addition, various test results and content can be stored, such as aptitude test scores (scores of aptitude tests for employees belonging to the recruiting company (company-wide, by department, etc.), scores for characteristics measured by aptitude tests (problem-solving ability, vitality, interpersonal skills, teamwork, management ability, stress factors, hierarchical relationships, etc.)). This information can be used for job matching based on more specific information related to personnel, such as the additional information mentioned above.

[0047] <Processing flow> Referring to Figure 7, the processing flow of the matching method between personnel and job seekers executed by System 1 of this embodiment will be described. Figure 7 is an example of a flowchart relating to the matching method according to the first embodiment of the present invention.

[0048] To use this system 1, at least the recruiter (or an employee of the recruiting company) must access the server terminal 100 using their respective web browser or application on the recruiter terminal 300 (or the terminal of each employee belonging to any department of the recruiting company). If it is the first time using the service, they must enter their basic recruiter information, etc. If they already have an account as a recruiter, they must log in after undergoing the prescribed authentication, such as entering their ID and password, to make the service available. After this authentication, a prescribed user interface is provided on the display of the recruiter terminal 300 via a website, application, etc., and the process proceeds to step S101 shown in Figure 7.

[0049] First, as part of step S101, the server terminal 100 receives image data and / or audio data from the recruiter terminal 300 via the communication unit 110. For example, when a recruiter user wears the recruiter terminal 300 and positions one or more candidates within their field of view via the display 320, image data captured by the camera 350 of the recruiter terminal 300 is transmitted to the server terminal 100. Additionally, audio data of the candidates collected by the microphone 370 built into the recruiter terminal 300 is transmitted to the server terminal 100.

[0050] Next, as part of step S102, the evaluation information generation unit 132 of the control unit 130 of the server terminal 100 analyzes the received image data and / or audio data. Specifically, the evaluation information generation unit 132 extracts the image or audio features of each individual contained in the image data and / or audio data. In extracting the features, known algorithms, such as SIFT (Scale-Invariant Feature Transform) and HOG (Histograms of Oriented Gradients), are used to detect feature points from the image data and / or audio data. In the case of images, the feature is calculated from the pixel values ​​or derivatives of the feature points, and in the case of audio, from the frequencies of the feature points.

[0051] Subsequently, as the process of step S103, the evaluation information generation unit 132 of the control unit 130 of the server terminal 100 generates evaluation information of human resources based on the analyzed image data and / or voice data. Specifically, the evaluation information generation unit 132 uses the calculated feature amount as input data, and based on the learning model generated with the input data of the image data or voice data associated with a plurality of human resources stored in the learning model storage unit 123 and the output data of the information managed as evaluation information and / or additional information, generates evaluation information. Here, the evaluation information refers to information for measuring the human resource value of that human resource in the employment or job transfer market. For example, based on annual income, it can be evaluation information such as "human resources in the 8.5 million yen class of annual income" or "human resources in the 10 million yen class of annual income", or based on performance, it can be evaluation information such as "high performer" or "low performer" based on human resources belonging to a department of a specific company. This system 1, in advance, uses, as learning data, data related to a plurality of sample human resources, for example, image data and / or voice data of human resources as input data, and information related to the evaluation of that human resource, for example, information such as the occupation of that human resource, the affiliated company, annual income, performance at the affiliated destination, job title, aptitude test results, etc. as output data to generate a learning model. Based on this learning model and the feature amounts of the image data of the newly captured human resource and / or the voice data of the collected human resource, it is possible to infer the evaluation information of that human resource, such as the expected annual income, performance, and / or job title. Thus, based on the height, appearance, movement, etc. of the human resource captured as image data, it is possible to infer evaluation information such as the annual income, performance, job title, etc. of similar human resources.

[0052] Furthermore, in this step, as another example, the facial image data and / or voice data of a person can be analyzed based on a learning model generated using facial image data and / or voice data of other users different from the person in question, such as high performers belonging to the recruiting company, and aptitude data such as competencies (e.g., vitality, interpersonal skills, teamwork, creative thinking ability, problem-solving ability, etc.) that have been acquired in advance. This allows for the estimation of the person's competencies (for example, by evaluating each item such as vitality, interpersonal skills, teamwork, creative thinking ability, problem-solving ability, etc., on a 10-point scale). Based on the estimated competencies, the degree of similarity can be determined by comparing them with the competencies of high performers belonging to the recruiting company, thereby calculating the degree of match with the recruiting company. The evaluation information for each item of the estimated competencies for the person can then be displayed on the display 320 of the recruiter terminal 300 along with the person, and the degree of match can also be displayed.

[0053] Next, in step S104, the evaluation information generation unit 132 processes the generated evaluation information to display it on the display 320 of the recruiter terminal 300. Specifically, the evaluation information generation unit transmits the generated evaluation information (for example, information such as "annual salary level is 8.5 million yen" as the market value of the person) to the recruiter terminal 300, and the recruiter terminal 320 processes the display of the evaluation information along with the person in the real world, which has been captured by the camera 350 and displayed on the display 320.

[0054] Figure 8 shows an example of evaluation information displayed on the recruiter terminal 300. The display 320 shows the real space as seen through the eyes of the recruiter user, captured by the camera 350 of the recruiter terminal 300. Near each candidate placed in the real space, evaluation information for that candidate, such as "Market value 10 million yen," is displayed.

[0055] As described above, according to this embodiment, job seekers can find candidates who match their desired conditions in everyday spaces where unspecified individuals come and go, such as street corners, and can approach potential candidates early on.

[0056] <Second Embodiment> Figure 9 shows an example of a flowchart of a job matching method according to the second embodiment. This embodiment relates to a function that stores information about personnel or job postings in advance, generates personnel evaluation information based on personnel image data or voice data, extracts personnel that match the job postings, and displays them in an identifiable manner to the job posting user. The functional configurations of the server terminal 100, user terminal 200, and job posting terminal 300 are substantially the same as those described in the first embodiment, so their description is omitted.

[0057] First, as part of step S201, the server terminal 100 receives image data and / or audio data from the recruiter terminal 300 via the communication unit 110. For example, when a recruiter user wears the recruiter terminal 300 and positions one or more candidates within their field of view via the display 320, image data captured by the camera 350 of the recruiter terminal 300 is transmitted to the server terminal 100. Additionally, audio data of the candidates collected by the microphone 370 built into the recruiter terminal 300 is transmitted to the server terminal 100.

[0058] Next, as part of step S202, the evaluation information generation unit 132 of the control unit 130 of the server terminal 100 analyzes the received image data and / or audio data. Specifically, the evaluation information generation unit 132 extracts the image or audio features of each individual contained in the image data and / or audio data. In extracting the features, known algorithms, such as SIFT (Scale-Invariant Feature Transform) or HOG (Histograms of Oriented Gradients), are used to detect feature points from the image data and / or audio data, and calculate the features from the pixel values ​​or derivatives of the feature points.

[0059] Subsequently, as the process of step S203, the evaluation information generation unit 132 of the control unit 130 of the server terminal 100 generates evaluation information on the human resources based on the analyzed image data and / or voice data. Specifically, the evaluation information generation unit 132 uses the calculated feature amount as input data, and based on the learning model generated with the input data of the image data or voice data associated with a plurality of human resources stored in the learning model storage unit 123 and the output data of the information managed as evaluation information and / or additional information, generates evaluation information. Here, the evaluation information refers to information for measuring the human value of the human resources in the employment or job transfer market. For example, based on annual income, it can be evaluation information such as "human resources in the 8.5 million yen class of annual income" or "human resources in the 10 million yen class of annual income", or based on performance, it can be evaluation information such as "high performance" or "low performance" based on the human resources belonging to a specific department of a company. This system 1 can, in advance, use data related to a plurality of human resources as samples, for example, the image data and / or voice data of the human resources as input data, and generate a learning model with information related to the evaluation of the human resources, such as the occupation, affiliated company, annual income, performance at the affiliated destination, position, etc. of the human resources as output data. Based on this learning model and the feature amounts of the image data of the newly imaged human resources and / or the voice data of the collected human resources, it is possible to infer the evaluation information of the human resources, such as the assumed annual income, performance, and / or position. In this way, based on the height, appearance, movement, etc. of the human resources captured as image data, it is possible to infer the evaluation information such as the annual income, performance, position, etc. of similar human resources.

[0060] Next, in step S204, the evaluation information generation unit 132 performs a matching process between personnel and employers based on the generated evaluation information and the information stored as user data 1000 or employer data 2000. For example, if the evaluation information generated in step S203 is "This person has an annual salary of 9.5 million yen or more" and "This person has an annual salary of 10 million yen or more," the evaluation information generation unit 132 refers to the employer data 2000 and extracts personnel that match the employer based on the expected annual salary (salary) included in the job information. For example, if the expected annual salary included in the job information is in the range of "9 million yen or more and 9.5 million yen or less," personnel with evaluation information in that range can be extracted. Alternatively, the evaluation information generation unit 132 can refer to the personnel's work history and job-hunting status included in the user data 1000, and also refer to the basic information and job information included in the employer data 2000 to extract personnel that match the employer. For example, if the industry listed in the basic information of the job seeker data 2000 is "IT, software," and the work history listed in the additional information of the user data 1000 shows that the individual has worked in the same industry, then such individuals can be extracted. In addition, the evaluation information generation unit 132 can refer to the job search status of the user data 2000 and extract only individuals who are "currently looking for a job."

[0061] Next, in step S205, the evaluation information generation unit 132 performs a process to display the results of the matching process on the display 320 of the job seeker terminal 300. Specifically, the evaluation information generation unit transmits evaluation information only for the personnel extracted as a result of the matching process (for example, information such as "annual salary level is 9.5 million yen" as the market value of the personnel) to the job seeker terminal 300, and the job seeker terminal 320 performs a process to display the evaluation information along with the personnel in the real world, which are captured by the camera 350 and displayed on the display 320.

[0062] Figure 10 shows an example of evaluation information displayed on the recruiter terminal 300. The display 320 shows the real space as seen through the eyes of the recruiter user, captured by the camera 350 of the recruiter terminal 300. Near each individual placed in the real space, evaluation information for that individual is displayed, such as "9.5 million yen," "IT consultant," and "currently seeking employment." Here, evaluation information is displayed only for individuals who match the recruiter, allowing the recruiter to easily find suitable candidates. Furthermore, by using predetermined icons (for example, the arrows shown in Figure 10), colors, and effects, suitable candidates can be displayed in a way that makes them easily identifiable.

[0063] As described above, according to this embodiment, by improving the matching accuracy between personnel and job seekers based on evaluation information and information about personnel and / or job seekers, job seeker users can more easily find personnel that match the job seeker's desired conditions and approach potential personnel earlier.

[0064] Furthermore, as a variation, this embodiment can also be applied by acquiring user face image data and / or voice data displayed via a video conferencing application or the like on a recruiter terminal 300 such as a PC or smartphone. Specifically, for candidate users in a setting such as a job interview, additional information such as name, profile, annual income, performance, work history, career, and aptitude is acquired in advance. By analyzing the candidate user's face image data and / or voice data based on the face images and / or voice data of other users and a learning model generated based on the additional information, evaluation information can be generated and matching can be performed with recruiters. In this way, evaluation information can be generated not only in augmented reality space, but also based on user face image data and / or voice data acquired through recruiter terminals such as PCs and smartphones.

[0065] The embodiments described above are merely illustrative to facilitate understanding of the present invention and are not intended to limit its interpretation. The present invention can be modified and improved without departing from its spirit, and it goes without saying that the present invention includes equivalents thereof. [Explanation of Symbols]

[0066] 100 server terminals 200 user terminals 300 Job Seeker Terminals

Claims

1. A method for evaluating candidates displayed via an application on a recruiter user's recruiter terminal, which is executed by a server terminal, The control unit of the server terminal is: The recruiter's terminal captures image data and / or audio data of the candidate, which is received from the recruiter's terminal. A method for generating evaluation information to measure the talent value of the candidate in the job or career change market based on the received image data and / or audio data of the candidate, by inferring the evaluation of the candidate based on a learned model, using image data and / or audio data of multiple other candidates different from the candidate as input data, and evaluation data including any of the annual income, performance, work history, or career history of the multiple candidates as output data.

2. The control unit, The method according to claim 1, comprising receiving information from the recruiter's terminal regarding the candidate's name, profile, annual income, performance, work history, career, and suitability, and inferring an evaluation of the candidate based on any of the aforementioned information.

3. The control unit, Receiving job information from the aforementioned recruiter terminal, The method according to claim 1, wherein a determination is made as to whether the candidate matches the conditions, based on the conditions included in the job information and the generated evaluation information.

4. The method according to claim 1, characterized in that the aforementioned evaluation information is based on annual income.

5. The method according to claim 1, characterized in that the evaluation information is performance-based information.

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