Method for job matching 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 of 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 predict the performance of a specific human resource based on 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, there is provided a job matching method for evaluating human resources in an extended reality space, which comprises receiving image data and / or audio data of human resources displayed in the captured real space, generating evaluation information of the human resources based on the received image data and / or audio data, and displaying the evaluation information together with the human resources in the captured real space.

Effect of the Invention

[0008] According to the present invention, it is possible to realize a method for predicting excellent human resources from among unspecified human resources.

Brief Description of the Drawings

[0009]

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[0010] <First Embodiment> A specific example of the job matching method according to the first embodiment of the present invention will be described below with reference to the drawings. Note that the present invention is not limited to these examples, but is defined by the claims, and is intended to include all modifications within the meaning and scope equivalent to the claims. In the following description, the same reference numerals are given to the same elements in the description of the drawings, and redundant descriptions are omitted.

[0011] FIG. 1 shows a system configuration diagram according to the first embodiment of the present invention. As shown in FIG. 1, the system according to the present embodiment includes a server terminal 100, a user terminal 200, and a job seeker terminal 300 that are connected to the server terminal 100 via a network such as the Internet. In FIG. 1, the user terminal 200 and the job seeker terminal 300 are exemplified as representative examples for convenience of explanation, but any number of user terminals and job seeker terminals can be connected to the network. Further, in the present embodiment, the job seeker terminal 300 is assumed to be worn by a job seeker user and display an extended reality space via a display. For example, the following description is made assuming smart glasses, but it is not limited thereto, and it may be an information terminal such as a head-mounted display or a smartphone.

[0012] The server terminal 100 can provide a service that enables a job seeker user wearing the job seeker terminal 200 to generate evaluation information of a specific user among unspecified users (hereinafter referred to as "human resources") displayed in the real space and display the evaluation information together with the human resources.

[0013] For example, while walking outside, the job seeker user can visually recognize the evaluation information of each human resource captured by the camera built into the smart glasses via the display built into the smart glasses.

[0014] For example, the employer user can download this service application to the employer terminal 300 from the server terminal 100 or another platform, and can send and receive data related to the server terminal 100 and this service via the application. Alternatively, the employer user can also send 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 "talents" 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 "talents" 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 provided.

[0018] As illustrated, 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 through a bus.

[0020] The control unit 130 is an arithmetic device that controls the overall operation of the server terminal 100, controls the transmission and reception of data between each element, and performs information processing necessary for the execution and authentication processing of applications. For example, the control unit 10 is a CPU (Central Processing Unit), and executes programs and the like stored and expanded in the storage unit 120 to perform each information processing.

[0021] The control unit 130 further includes an information reception unit 131 that receives information such as requests or data from the user terminal 200 or the job seeker terminal 300, an evaluation information generation unit 132 that analyzes the image data or voice data of the human resource and generates evaluation information of the human resource based on the analyzed image data, etc., and a matching processing unit 133 that processes the matching between the job seeker and the human resource.

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

[0023] The storage unit 120 further includes a user data storage unit 121 that stores data related to human resources, a job seeker data storage unit 122 that stores data related to job seekers, and a learning model storage unit 123 that stores a learning model generated based on the face or appearance image and / or voice obtained from the user.

[0024] The communication unit 110 connects the server terminal 100 to the network. Note that the transceiver unit 13 may be provided with a short-range communication interface for Bluetooth (registered trademark) and BLE (Bluetooth Low Energy).

[0025] Note that the data stored or the functions realized by the server terminal 100 can be locally stored or realized by the storage unit or the control unit of the job seeker terminal 300 or the like.

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

[0027] As described above, the user terminal 200 can be various information terminals or general-purpose computers. Hereinafter, a smartphone will be described as an example. The user terminal 200 includes at least a communication unit 210, a display operation unit 220, a storage unit 230, a control unit 240, etc., which are electrically connected to each other through a bus.

[0028] The control unit 240 is an arithmetic device that controls the overall operation of the user terminal 200, controls the transmission and reception of data between each element, and performs information processing necessary for the execution and authentication processing of applications. For example, the control unit 240 is a CPU (Central Processing Unit), and executes programs and the like stored and expanded in the storage unit 230 to perform each information processing.

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

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

[0031] The communication unit 210 connects the user terminal 200 to a network. Note that the transmission / reception unit 23 may be provided with a short-range communication interface for Bluetooth (registered trademark) and BLE (Bluetooth Low Energy).

[0032] The display operation unit 220 is a user interface used for a human operator to input instructions and display text, images, etc. according to input data from the control unit 240. When this terminal is configured as a personal computer, it is composed of a display, a keyboard, and a mouse. When it is configured as a smartphone or a tablet terminal, it is composed of a touch panel or the like. Through the display operation unit, for inputting predetermined information, in the case of a keyboard, the human operator can press a key; in the case of a mouse, the human operator can move the cursor with the mouse; in the case of a touch panel, the human operator can perform operations such as tapping, swiping, and pinching.

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

[0034] As described above, the job seeker terminal 300 can be various information terminals or general-purpose computers. Hereinafter, a glasses-shaped device wearable by a job seeker user will be taken as an example for explanation, specifically, a smart glass that uses the glass part as a display to display an extended 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., and these are electrically connected to each other through a bus.

[0035] The control unit 360 is an arithmetic unit that controls the operation of the job seeker terminal 300 as a whole, controls the transmission and reception of data between each element, and performs information processing necessary for the execution and authentication processing of applications. For example, the control unit 360 is a CPU (Central Processing Unit), and executes programs and the like stored and expanded in the storage unit 330 to perform each information processing.

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

[0037] In addition, the storage unit 330 stores various programs such as application programs. A database (not shown) storing 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 a network. Note that the transmission / reception unit 23 may be provided with a short-range communication interface for Bluetooth (registered trademark) and BLE (Bluetooth Low Energy).

[0039] The display 320 is a user interface used to display the real space imaged by the camera 350 described later, and can superimpose and display data such as text and images on the real space. In the case of smart glasses, the display 320 can be, for example, a display such as an LCD or an organic EL, and the display 320 can also function as a viewfinder of 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 the real space, and is usually provided to be consistent with the line-of-sight direction of the job seeker user wearing the job seeker terminal 300.

[0041] The image of the real space captured by the camera 350 is synthesized with data such as text and images by an image control unit (not shown), and the text, images, etc. are superimposed and displayed on the image of the real space by the display 320. The image control unit is, for example, a GPU (Graphics Processing Unit), and mainly executes arithmetic processing related to image processing. In addition, the job seeker terminal 300 is equipped with a microphone 370. The microphone 370 is built into the job seeker terminal 300 and can collect sounds around the terminal 300.

[0042] In addition, although not shown, the job seeker terminal 300 can be equipped with a GPS (Global Positioning System) for positioning the current position information. The GPS can receive positioning radio waves from GPS satellites and can position the latitude and longitude information that is the absolute position. Also, it is possible to receive communication radio waves from a plurality of base stations for mobile phones and position the current position information by the multi-base station positioning function. In addition, the job seeker terminal can also be equipped with sensors such as an acceleration sensor and a geomagnetic sensor (not shown).

[0043] Figure 5 is a diagram showing an example of user data stored in the server terminal 100.

[0044] The user data 1000 shown in Fig. 5 stores various types of 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 types of data related to human resources, for example, image data associated with the human resource (hereinafter, "image data" includes moving image data), audio data, etc., evaluation information (information related to the 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 by the server terminal 100 receiving the information input or selected by the human resource via the user terminal 200 and the information managed by applications such as SNS. Also, the learning model generated as learning data from the input by image data or audio data such as a face image or a portrait image associated with the human resource obtained as user data 1000 and / or input by the job seeker, and the output by the 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 the image data and / or audio data associated with a new human resource.

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

[0046] The job seeker data 2000 shown in FIG. 6 stores various data related to the job seeker. In FIG. 6, for the sake of convenience of explanation, an example of one job seeker (the job seeker identified by the job seeker ID "20001") is shown, but information of multiple users can be stored. As various data related to the job seeker, for example, basic information of the job seeker (company name, industry, establishment date, location, number of employees, URL of the company's HP, other company introduction texts, etc.), job information (desired person image, working hours, number of annual holidays, treatment (salary, etc.), welfare, work location, contract form (employment (regular employee, contract employee), business consignment, etc.), etc.) and other information can be stored. In addition, aptitude tests (scores of aptitude tests of employees belonging to the job seeker company (by the whole company, by department, etc.), scores for each characteristic (problem-solving ability, vitality, per capita, teamwork, management ability, stress factors, superior-subordinate relationship, etc.) measured by the aptitude test), various test results, contents, etc. can also be stored. These information can be used for job matching based on more specific information related to the human resources such as the above additional information related to the human resources.

[0047] <Flow of processing> With reference to FIG. 7, the flow of processing of the matching method between human resources and job seekers executed by the system 1 of the present embodiment will be described. FIG. 7 is an example of a flowchart related to the matching method according to the first embodiment of the present invention.

[0048] Here, in order to use this system 1, at least the job seeker (or an employee of the job seeker company) accesses the server terminal 100 using each web browser or application of the job seeker terminal 300 (or each terminal of an employee belonging to any department of the job seeker company). When using the service for the first time, the job seeker inputs basic information, etc. respectively. When the job seeker has already obtained an account, for example, by receiving a predetermined authentication such as inputting an ID and a password and logging in, the service becomes available. After this authentication, a predetermined user interface is provided on the display of the job seeker terminal 300 via a website, an application, etc., and the process proceeds to step S101 shown in FIG. 7.

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

[0050] Subsequently, as the process 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 feature amounts of the images or voices of each candidate included in the image data and / or audio data. When extracting the feature amounts, known algorithms, for example, 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 in the case of image data, the feature amounts are calculated from the pixel values and differential values of the feature points, and in the case of audio data, the feature amounts are calculated 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 on human resources based on the analyzed image data and / or audio data. Specifically, the evaluation information generation unit 132 uses the calculated feature amounts as input data, and based on a learning model generated using, as learning data, the input data of image data or audio data associated with a plurality of human resources stored in the learning model storage unit 123 and the output data of 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 could be evaluation information such as "human resources in the 8.5 million yen annual income class" or "human resources in the 10 million yen annual income class", or based on performance, it could be evaluation information such as "high performer" or "low performer" based on human resources belonging to a specific company's department. This system 1, in advance, uses, as learning data, data related to a plurality of sample human resources, such as image data and / or audio data of human resources as input data, and information related to the evaluation of that human resource, such as the occupation, affiliated company, annual income, performance at the affiliated destination, job title, aptitude test results, etc. of that human resource as output data, to generate a learning model. Based on this learning model and the feature amounts of the image data of the newly imaged human resource and / or the audio data of the human resource whose sound has been collected, it is possible to infer the evaluation information of that human resource, such as the expected annual income, performance, and / or job title. In this way, 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] Also, in this step, as another example, based on the face image data and / or voice data of other users different from the human resources, such as high performers belonging to the job seeking company, etc., which have been acquired in advance, and the aptitude data such as competencies (for example, vitality, interpersonal skills, teamwork, creative thinking ability, problem-solving ability, etc.) generated based on the learning model, by analyzing the face image data and / or voice data of the human resources, the evaluation of the competencies of the human resources can be inferred (for example, by performing a 10-level evaluation for each item such as vitality, interpersonal skills, teamwork, creative thinking ability, problem-solving ability, etc.), and based on the inferred competencies, compare with the competencies of the high performers belonging to the job seeking company, and determine the similarity to calculate the matching degree with the job seeking company. Then, the evaluation information of each item of the competencies inferred for the human resources can be displayed on the display 320 of the job seeker terminal 300 together with the human resources, and further, the matching degree can be displayed.

[0053] Subsequently, as step S104, the evaluation information generation unit 132 performs a process of displaying the generated evaluation information on the display 320 of the job seeker terminal 300. Specifically, the evaluation information generation unit transmits the generated evaluation information (for example, information such as "the annual income level is 8.5 million yen" as the market value of the human resources) to the job seeker terminal 300, and the job seeker terminal 320 performs a process of displaying the evaluation information together with the human resources in the real world captured by the camera 350 and displayed on the display 320.

[0054] FIG. 8 shows an example of the evaluation information displayed on the job seeker terminal 300. On the display 320, the real space captured as the field of view of the job seeker user by the camera 350 of the job seeker terminal 300 is displayed, and near each human resource arranged in the real space, the evaluation information of the human resource, such as information like "market value 10 million yen", is displayed.

[0055] As described above, according to the present embodiment, an employer user can find a talent that matches the employer's desired conditions in a daily space where unspecified talents come and go, such as a street corner, and can approach potential talents earlier.

[0056] <Second Embodiment> FIG. 9 shows an example of a flowchart of a job matching method according to the second embodiment. This embodiment relates to a function of storing information related to talents or job offers in advance, generating evaluation information of talents based on the image data or voice data of talents, extracting talents that match the job information, and displaying them in an identifiable manner to the employer user. The functional configurations of the server terminal 100, the user terminal 200, and the employer terminal 300 are substantially the same as those described in the first embodiment, and thus the description thereof is omitted.

[0057] First, as the process of step S201, the server terminal 100 receives image data and / or voice data from the employer terminal 300 via the communication unit 110. For example, when an employer user wears the employer terminal 300 and captures one or more talents in the field of view via the display 320, the image data captured by the camera 350 of the employer terminal 300 is transmitted to the server terminal 100. Also, the voice data of the talents collected by the microphone 370 built in the employer terminal 300 is transmitted to the server terminal 100.

[0058] Subsequently, as the process 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 feature amounts of the images or voices of each human resource included in the image data and / or audio data. When extracting the feature amounts, known algorithms, for example, 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 the feature amounts are calculated from the pixel values and differential values 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 of the human resources based on the analyzed image data and / or audio data. Specifically, the evaluation information generation unit 132 uses the calculated feature amounts as input data, and based on a learning model generated using, as learning data, the input data of the image data or audio 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 the human resources in the employment or job change market. For example, based on the annual income, it can be evaluation information such as "human resources in the 8.5 million yen class in terms of annual income" or "human resources in the 10 million yen class in terms of annual income", or based on performance, it can be evaluation information such as "high performer" or "low performer" based on the human resources belonging to a specific corporate department. The system 1 can, in advance, generate a learning model using, as learning data, data related to a plurality of sample human resources, for example, the image data and / or audio data of the human resources as input data, and information related to the evaluation of the human resources, for example, information such as the occupation, affiliated company, annual income, performance at the affiliated destination, and position of the human resources as output data. Based on this learning model and the feature amounts of the image data of the newly captured human resources and / or the audio data of the human resources collected, 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, and position of similar human resources.

[0060] Subsequently, as step S204, the evaluation information generation unit 132 performs a process of matching a human resource with a job seeker based on the generated evaluation information and the information stored as user data 1000 or job seeker data 2000. For example, when the evaluation information generated in step S203 is "This human resource has an annual income of 9.5 million yen or more" and "This human resource has an annual income of 10 million yen or more" respectively, the evaluation information generation unit 132 refers to the job seeker data 2000 and extracts the human resources that match the job seeker based on the assumed annual income (salary) included in the job information. For example, if the assumed annual income included in the job information is in the range of "9 million yen or more and 9.5 million yen or less", human resources with evaluation information in that range can be extracted. Alternatively, the evaluation information generation unit 132 can refer to the work history and job hunting status of the human resources included in the user data 1000, and also refer to the basic information and job information included in the job seeker data 2000, and extract the human resources that match the job seeker. For example, if the industry type included in the basic information of the job seeker data 2000 is "IT, software", and the work history of the human resource included in the additional information of the user data 1000 shows that the human resource has work experience in the same industry, such human resources can be extracted. Also, the evaluation information generation unit 132 can refer to the job hunting status of the user data 2000 and extract only the human resources who are "in the process of job hunting".

[0061] Subsequently, as step S205, the evaluation information generation unit 132 performs a process of displaying the result of the matching process on the display 320 of the job seeker terminal 300. Specifically, the evaluation information generation unit transmits only the evaluation information of the human resources extracted as the result of the matching process (for example, information such as "the annual income level is 9.5 million yen" as the market value of the human resource) to the job seeker terminal 300, and the job seeker terminal 320 performs a process of displaying the evaluation information together with the human resources in the real world imaged by the camera 350 and displayed on the display 320.

[0062] Fig. 10 shows an example of the evaluation information displayed on the job seeker terminal 300. On the display 320, a real space captured by the camera 350 of the job seeker terminal 300 and regarded as the field of view of the job seeker user is displayed. Near each talent placed in the real space, evaluation information of that talent, such as information like "9.5 million yen", "IT consultant", and "job hunting", is displayed. Here, only the talents that match the job seeker are displayed, and the job seeker can easily find the matching talents. Also, as a display method, by using a predetermined icon (for example, the arrow shown in Fig. 10), color, and effects, the matching talents can be displayed in a distinguishable manner.

[0063] As described above, according to this embodiment, while increasing the matching accuracy between talents and job seekers based on information regarding talents and / or job seekers together with the evaluation information, the job seeker user can more easily find talents that match the desired conditions of the job seeker and can approach potential talents earlier.

[0064] Also, as a modification, this embodiment can be applied by acquiring the face image data and / or voice data of the user displayed via a video conferencing application or the like on a job seeker terminal 300 such as a PC or a smartphone. Specifically, for candidate users in a job interview or the like, information such as name, profile, annual income, performance, work history, resume, and aptitude is acquired in advance as additional information, and based on the face image and / or voice data of other users and the learning model generated based on the additional information, the face image and / or voice data of the candidate user is analyzed to generate evaluation information and perform matching with the job seeker. In this way, evaluation information can be generated not only based on the extended reality space but also based on the face image data and / or voice data of the user acquired through a job seeker terminal such as a PC or a smartphone.

[0065] The above-described embodiments are merely examples for facilitating the understanding of the present invention and are not intended to limit the interpretation of the present invention. It goes without saying that the present invention can be changed and improved without departing from its gist, and equivalents thereof are included in the present invention.

Explanation of Signs

[0066] 100 Server terminal 200 User terminal 300 Job seeker terminal

Claims

1. A method for evaluating candidates displayed via an application on a recruiter terminal of a recruiter user, the method being executed by a server terminal, comprising: The control unit of the server terminal receiving image data and / or voice data of the candidate captured by the recruiting party terminal from the recruiting party terminal; A method for generating evaluation information that measures the human resource value of the candidate in the employment or job 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 learning model that uses 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, and career history of the multiple candidates as output data.

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

3. The control unit is Receiving job information from the job recruiter terminal; The method of claim 1 , further comprising determining whether the candidate matches the conditions based on conditions included in the job information and the generated evaluation information.

4. The method according to claim 1 , wherein the evaluation information is information based on annual income.

5. 2. The method of claim 1, wherein the evaluation information is performance-based information.

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