KR102507164B1 - Method for providing compensation for headhunting service using artificial intelligence model - Google Patents

Abstract

Disclosed is a headhunting service providing method which allows a computing device of a headhunting service providing server to read a headhunting service program and perform a headhunting service while communicating with a user terminal, comprising the steps of: receiving a job application request and compensation list information for an employment notice from a recommender or an applicant terminal; transmitting the compensation list to the applicant terminal, a recruiter terminal, and a headhunting company; receiving, from the applicant, the recruiter, and the headhunting company, a signal about whether to accept the compensation list; if at least one among the applicant, the recruiter, and the headhunting company rejects the compensation list, determining the compensation list as recruitment compensation using a compensation list optimization model stored in the headhunting service providing server; receiving information on a recruitment result from the recruiter terminal; notifying the applicant terminal of information on whether the applicant is recruited according to the information on the recruitment result; and providing the recruitment compensation to the applicant, the recommender, and the headhunting company based on the compensation list. A profit for the headhunting can be obtained.

Description

A method of providing headhunting service compensation using artificial intelligence {METHOD FOR PROVIDING COMPENSATION FOR HEADHUNTING SERVICE USING ARTIFICIAL INTELLIGENCE MODEL}

The present invention relates to a method for providing a headhunting service that proposes a bid for a reward and an optimal reward using an artificial intelligence model.

Due to the recent rapid development of the industry, domestic companies are investing huge amounts of money to recruit talented people. According to the survey, the size of the domestic recruitment advertising/agency market is equivalent to KRW 1.4 trillion. Online recruitment is still only 9% compared to offline recruitment, but it is clear that the online recruitment market will grow rapidly with the development of smart phones and the advent of the IT era. In the offline recruitment market, the recruitment market through headhunting is worth 400 billion won (28%), but companies using headhunting are dissatisfied with problems such as failure to secure talent, lack of job suitability, difficulty in finding urgent jobs, and high brokerage fees. Also, from a job seeker's point of view, when entering a company through headhunting, there is a burden of having to pay a high brokerage fee equivalent to about 15 to 30% of the annual salary.

On the other hand, most of the online recruitment market is conducted through recruitment portal sites. These recruitment portal sites mainly seek jobs for members who have not been verified or have low job suitability, so they are focused on hiring new employees or in industries with low expertise. There is a problem with this happening. Therefore, in the online recruitment market, there is a need to use a headhunting service that can employ highly reliable talents through primary verification such as headhunters. Patent Document 1, which is a prior art related thereto, discloses an online recommendation-based recruitment service providing method and apparatus using the same. However, since the method of providing a recruitment service in Patent Document 1 clearly distinguishes recommenders and applicants and provides a recruitment service, it is difficult for general users who have a burden on headhunting expertise to approach as a headhunter.

In addition, the method of providing a recruitment service in Patent Document 1 provides compensation only to the recommenders of the finally hired applicant, so that users are highly likely to withdraw from the service if the recommenders do not receive compensation due to initial failure in recommendation. In particular, in the existing recruitment service provision method such as Patent Document 1, headhunters can recommend talents suitable for recruitment according to the characteristics of the company, recruitment conditions, etc., but cannot consider variables such as interviews. has a problem of losing the motivation to make a recommendation because the probability of passing the applicant recommended by the candidate is low in a competition rate of tens to several hundred to one. In addition, in the method of providing a recruitment service in Patent Document 1, when headhunters who have joined at an early stage indiscriminately recommend job seekers, a problem in which the recruitment service is monopolized by a small number of headhunters may occur.

In addition, when a successful applicant occurs, the recruiting company pays a fee (compensation) to the headhunt company, and the headhunt company provides some of the fee (compensation) to the recommender or direct applicant, but the headhunt company pays a fixed amount to the recommender or direct applicant. In terms of determining the amount, there was a problem that the motivation of applicants and recommenders was not encouraged when the amount was small.

KR 10-2016-0142253 A

In order to solve the above problems, the present invention intends to provide a headhunting service providing method and a system for executing the same, in which even ordinary people without expertise in headhunting can easily check job postings, directly apply for employment, or recommend acquaintances.

In detail, an object of the present invention is to provide a system through which general job seekers can easily headhunt acquaintances suitable for job postings while checking their own job postings.

In addition, the present invention is intended to provide a compensation design process using an artificial intelligence model in order to operate an optimal compensation system.

The present invention is a method for providing a headhunting service in which a computing device of a headhunting service providing server communicates with a user's terminal and reads a headhunting service program to perform the headhunting service. Posting a job announcement in response to the job posting registration request from the job posting registration request, receiving a job application request for the job posting and compensation list information from the recommender or the applicant's terminal, the compensation money Transmitting a list to the applicant's terminal, the recruiter's terminal, and the headhunting company; Receiving a signal from the applicant, the recruiter, and the headhunting company whether or not to accept the reward list; The applicant, the recruiter, and the headhunting company. If at least one of the headhunting companies rejects the reward list, determining the reward list as a hiring reward using a reward list optimization model stored in the headhunting service providing server; If the reward list is accepted, determining the reward list as the recruitment reward, transmitting the job application information to the recruiter's terminal, receiving information on the hiring result from the recruiter's terminal, Disclosed is a headhunting service providing method, including notifying whether or not the applicant has been hired to a terminal of the applicant according to information about the applicant, and providing the recruitment reward to the applicant, the recommender, and the headhunting company based on the reward list. .

In addition, the reward list optimization model may include a regression model that performs an operation of optimizing the reward list using a neural network that outputs a reward list when recruitment information is input.

In addition, the employment information may include at least one or more information of the detailed information of the employment announcement corresponding to the size of the company, industry group, employment field, employment position, and employment type.

In addition, when at least one of the applicant, the recruiter, and the headhunting company rejects the reward list, a reward negotiation operation of receiving a reward negotiation list from at least one terminal among the recommender, the applicant, the recruiter, and the headhunting company. and when a signal that the recommender, the applicant, the recruiter, and the headhunting company all accept in the received compensation negotiation list is received by the headhunting service providing server, the compensation negotiation list is converted into the compensation list optimization model. Setting as learning data, and updating a reward list optimization model using the learning data may be further included.

In addition, when the acceptance of the compensation negotiation list is lacking, receiving feedback data of the compensation negotiation list from a person who lacks acceptance of the compensation negotiation list, and updating the compensation list optimization model using the feedback data can include more.

The method may further include providing, by the applicant, a recommendation cancellation service through a terminal of the applicant, in which the recommendation of the recommender is canceled, wherein the providing of the recommendation cancellation service may include canceling the recommendation of the recommender by the applicant. Receiving a request, charging a release fee to the applicant based on the recruiting compensation of the recommender, and granting the applicant a recommender status, and receiving primary successful candidate information about the applicants If so, the method may further include providing a heading insurance service for sharing compensation to recommenders of the first successful applicants.

In the headhunting service providing method of the present invention, the headhunting service providing server performs a process requiring expertise or cumbersome process in the headhunting process, and recommenders select only applicants according to recruitment, so that even ordinary users can easily perform headhunting and participate in headhunting. income can be earned.

In addition, according to various embodiments of the present invention, the present invention provides a reward design process using an artificial intelligence model in order to operate an optimal reward system, so that recommenders, applicants, corporate members, and headhunt companies can accept the optimal reward. can be set.

1 relates to a headhunting service providing system according to an embodiment of the present invention.
2 is a flowchart illustrating a process of providing a headhunting service in a service providing server according to an embodiment of the present invention.
3 is a diagram showing an artificial intelligence model according to an embodiment of the present invention.

Since the technology to be described below can have various changes and various embodiments, specific embodiments will be illustrated in the drawings and described in detail. However, this is not intended to limit the technology described below to specific embodiments, and it should be understood to include all modifications, equivalents, or substitutes included in the spirit and scope of the technology described below.

Terms such as first, second, A, B, etc. may be used to describe various elements, but the elements are not limited by the above terms, and are merely used to distinguish one element from another. used only as For example, without departing from the scope of the technology described below, a first element may be referred to as a second element, and similarly, the second element may be referred to as a first element. The terms and/or include any combination of a plurality of related recited items or any of a plurality of related recited items.

In terms used in this specification, singular expressions should be understood to include plural expressions unless clearly interpreted differently in context, and terms such as “comprising” refer to the described features, numbers, steps, operations, and components. , parts or combinations thereof, but it should be understood that it does not exclude the possibility of the presence or addition of one or more other features or numbers, step-action components, parts or combinations thereof.

Prior to a detailed description of the drawings, it is to be clarified that the classification of components in the present specification is merely a classification for each main function in charge of each component. That is, two or more components to be described below may be combined into one component, or one component may be divided into two or more for each more subdivided function. In addition, each component to be described below may additionally perform some or all of the functions of other components in addition to its main function, and some of the main functions of each component may be performed by other components. Of course, it may be dedicated and performed by .

In addition, in performing a method or method of operation, each process constituting the method may occur in a different order from the specified order unless a specific order is clearly described in context. That is, each process may occur in the same order as specified, may be performed substantially simultaneously, or may be performed in the reverse order.

Hereinafter, it will be described that the headhunting service providing server provides the headhunting service. The headhunt service providing server is a device that processes input data constantly and performs calculations necessary for building design according to a specific model or algorithm. For example, the building design device may be implemented in the form of a PC, a server on a network, a smart device, a chipset in which a design program is embedded, and the like.

1 relates to a headhunting service providing system according to an embodiment of the present invention.

Referring to FIG. 1 , a headhunting service providing system according to an embodiment may include a user terminal 100, a recruiter terminal 300, and a headhunting service providing server 400. In detail, the user terminal 100 includes a recommender terminal 102 that recommends acquaintances suitable for online job postings as applicants and receives compensation according to hiring relay, and an applicant terminal 101 that applies through recommendation or directly to online job postings. ) can be included.

The user terminal 100 may be a terminal in which a web browser or a headhunting application is installed to provide a headhunting service, and for example, a smart phone, a mobile phone, a personal digital assistant (PDA), a portable multimedia player (PMP), It may be at least one of a terminal such as a tablet PC, an ultrabook, a wearable device, or a smart glass terminal. Hereinafter, in the embodiment, the user terminal 100 will be described as a smart phone on which a headhunting application is installed or a computer using a headhunting service using a web page.

In the embodiment, the recommender terminal 102 and the applicant terminal 101 are distinguished in terms of whether a user who is a terminal user directly applies for a job posting or recommends an acquaintance, and may be the same terminal on which the same headhunting application is installed. .

That is, the headhunting service providing system of the present invention is a system in which a user can be both a recommender and an applicant, and the headhunting service providing server 400 performs a process requiring expertise or hassle in the headhunting process, and the recommender is hired. By selecting only applicants according to, the purpose is to make it easy for general users to conduct headhunting and earn profits.

In detail, the recommender terminal 102 can display a job posting so that the user can easily check the job posting through a terminal having a limited size and an input method limited to touch input, and a social network service (SNS) installed in the terminal. In conjunction with the application, it is possible to provide a headhunting service that can easily recommend acquaintances. Furthermore, the recommender terminal 102 provides to check the recommendation status or results according to the recommendation at a glance, and can provide a headhunting service that can generate revenue through various channels, not only when the applicant is finally hired. .

In addition, the applicant terminal 101 can provide an interface through which an applicant can easily apply for a job posting through a terminal having a touch input method on a screen of a limited size.

In addition, the applicant terminal 101 may provide a recommender release function capable of rejecting the recommendation of an unwanted recommender, and may provide a headhunting service capable of receiving compensation to be provided to the recommender if the applicant directly applies without going through the recommender. can

Also, the recruiter terminal 300 is a terminal of a human resources manager of a company, and may be a terminal in which a headhunting application is installed.

Since the human resources manager uses the headhunting service to recruit employees, and the function to be used in the headhunting service is different from that of the user terminal 100, a headhunting application of a different version from the headhunting application of the user terminal 100 may be installed. there is.

In the embodiment, the recruiter terminal 300 is a terminal in which a headhunting application is executed in a recruitment mode after a human resources manager signs up as a corporate member and logs in, and can upload a job announcement by inputting job information, and can communicate with applicants according to the job announcement A headhunting service can be provided that identifies recommenders and proceeds with the hiring process.

Finally, the headhunting service providing server 400 may be a server that assists the headhunting application in providing the headhunting service to the user by transmitting and receiving data with the terminal.

2 is a flowchart illustrating a process of providing a headhunting service by a service providing server according to an embodiment of the present invention.

Referring to FIG. 2, the headhunting service providing server 400 includes a step of registering member information of a user through simple membership registration (S101), receiving job announcement information from the recruiter terminal 300, and publishing it on a bulletin board. Step (S102), receiving a job application request through a recommender (S103, S104, S105), receiving a job application request through the applicant's direct application (S103, S106, S107), job application information Receiving (S108), providing header insurance service according to pass (S109), and providing compensation according to final pass (S110) may be performed.

In detail, the headhunting service providing server 400 may register a user as a member through simple member registration. (S101)

When the headhunting service is performed through the above process, the headhunting service providing server 400 may assign a grade to users registered as general members according to the degree of recommendation contribution, and may grant different heading authority according to the assigned grade.

In detail, the headhunting service providing server 400 may assign grades to users based on the number of recommendations, the number of successful recommendations, or the degree of success (eg, low difficulty in Korea, high difficulty in foreign countries), and the like. That is, the headhunting service providing server 400 may improve the user's rating as the heading activities of users increase, and increase the heading authority as the rating increases.

Here, the heading authority may be associated with a restriction on the number of recommendations for each grade, the number of times of using the heading insurance service, a restriction on viewing job postings, or a commission rate for exchanging employment compensation. That is, as the level goes up, the limit on the number of recommendations increases, the limit on the number of times of using the heading insurance service can be lifted, it is possible to view job postings open only in high levels, and the exchange rate can be reduced.

In addition, the headhunting service providing server 400 may directly register other heading companies among general members as users. The subscribing heading company can conduct heading business using the heading service provided by the headhunting service providing server 400. may be deducted from fees.

Thereafter, when receiving job announcement information from the recruiter terminal 300 of a recruiter registered as a corporate member, the headhunting service providing server 400 may register and post the job announcement. (S102)

In detail, the headhunting service providing server 400 may receive a job posting registration request from the recruiter terminal 300, and at this time, company information, employment field, application conditions, employment conditions, recruitment compensation or recruitment compensation to be provided to the recommender. At least one of the job announcement information may be received.

Further, when selecting a job posting, the headhunting service providing server 400 may provide a headhunting service in which a user directly applies for the job posting or recommends an acquaintance to apply for the job posting.

Specifically, after the job posting is posted, the headhunting service providing server 400 may receive a job recommendation request of the applicant from the recommender terminal 102 . (S103) Then, the headhunting service providing server 400 may transmit an inquiry message confirming support to the applicant's terminal and receive a response thereto. (S104)

Further, the headhunting service providing server 400 may determine the applicant as an applicant and request input of job application information when the applicant accesses the job posting support page or accepts the application based on the recommendation through the headhunting application.

However, if the applicant does not like the recommender, there is a problem that the applicant may not apply for employment because he or she does not want the recommender to receive employment compensation due to his/her employment.

In order to prevent such a problem, the headhunting service providing server 400 may provide a recommendation cancellation function in which an applicant cancels recommendation of a recommender. (S105)

In detail, the headhunting service providing server 400 may provide a recommendation deactivation service in which a recommender's recommendation is canceled by paying a predetermined deactivation fee when the applicant wants to directly apply for the recommended job posting without recommendation.

At this time, in order to minimize dissatisfaction due to the recommender's recommendation cancellation during the promotion period, the headhunting service providing server 400, when there is a recommendation cancellation request from the applicant, the headhunting service providing server 400 transfers at least a portion of the cancellation fee to the recommender. can also be provided to

Thereafter, the headhunting service providing server 400 regards the applicant as an applicant who has directly applied for the job posting, and may distribute up to the recommender hiring reward to the applicant when hiring is confirmed.

In this way, the headhunting service providing server 400 provides a recommendation cancellation function capable of canceling the recommendation of recommenders, thereby suppressing indiscriminate recruitment recommendations and inducing applicants who have canceled the recommendation and applied to act as new headhunters. can

Meanwhile, after the job announcement is posted, the headhunting service providing server 400 may directly receive a job application request from the applicant terminal 101 . (S103) At this time, the applicant may request the headhunting service providing server 400 to recommend candidate recommenders in order to increase the probability of employment. (S106)

The headhunting service providing server 400 that has received a request for recommendation of a candidate recommender may provide a list of candidate recommenders after charging the applicant a predetermined cost, and if the applicant selects a recommender and the recommender approves, the applicant is selected by the recommended recommender. It can be set as an applicant who applied for a job posting. (S107)

Thereafter, the headhunting service providing server 400 may receive job application information of the applicant. (S108)

In detail, the headhunting service providing server 400 may provide an application input form for inputting job application information through the applicant terminal 101 and may receive the job application information input in the application input form.

Here, the job application information may include a profile, a job application comment, and an attached file such as a resume or portfolio.

Upon completion of receiving the job application information through the above-described processes, the headhunting service providing server 400 may transmit the received job application information to the recruiter terminal 300 in real time.

Within a predetermined period of time, the recruiter terminal 300 selects received job application information to hire an applicant, and transmits the recruited information to the headhunting service providing server 400 .

At this time, the recruiter terminal 300 transmits first successful candidate information, not the final hiring, to the headhunting service providing server 400, and the headhunting service providing server 400 may receive it. Further, the headhunting service providing server 400 receiving the first successful candidate information may provide a header insurance service for sharing compensation to recommenders of the first successful candidate. (S109)

In detail, the recruiter may review only the job application information through the recruiter terminal 300 and select the first passer as the document passer.

The headhunting service providing server 400 that has received the information on the first successful applicant may provide a header insurance service that allows the recommender who recommended the first successful candidate (the successful candidate himself/herself if there is no recommender) to select whether or not to share the recruitment compensation.

Finally, the headhunting service providing server 400 may provide recruitment compensation money to the recommender or direct applicant when receiving information on the final successful candidate from the recruiter. (S110)

In detail, the headhunting service providing server 400 may provide the recruiter with the recruiting compensation money set by the recruiter to the recommender, and when the applicant directly applies without the recommender, the headhunting service providing server 400 may consider the recommender as the applicant and provide the recruiting compensation money to the applicant himself/herself.

At this time, the headhunting service providing server 400 may also provide a predetermined congratulatory money to the applicant through a promotion in order to induce the applicant to actively use the service.

In addition, the headhunting service providing server 400 may provide the applicant with a recruitment reward allocated to the recommender when the applicant cancels the recommendation of the recommender.

In addition, the headhunting service providing server 400 may divide the recommender hiring reward money by N when the number of recommended recommenders subscribed to the headhunting service is employed, and may provide each recommender.

Through such a headhunting service provision, the headhunting service providing server 400 enables ordinary people without expertise in headhunting to easily check job postings, directly apply for employment, or recommend acquaintances, and limit indiscriminate recommendations to provide accessibility for new users. It is possible to provide a headhunting service with a system in which the applicant can receive various rewards as well as when the applicant is finally hired.

Meanwhile, in general, when a headhunting service is provided as described above, when a successful candidate occurs, the recruiting company pays a fee to the headhunting company (headhunting service providing server operator), and the headhunting company distributes some of it to recommenders and applicants. (If the applicant applies directly without a referral, it will be distributed to the applicant).

At this time, a problem arises in that the headhunting company sets a predetermined amount for the recommender and the applicant.

As an actual example, when the recruitment compensation set by the headhunting company is small, there is a problem in that the motivation of applicants and recommenders is not encouraged.

In order to solve this problem, the headhunting service providing server 400 according to an embodiment of the present invention prevents indiscriminate recommendation due to the characteristics of a headhunting service in which a plurality of potential applicants exist and a plurality of recommenders exist, and a corporate member's In order to enhance the ability of the recommender to select the best applicant from the job posting, the recommender may provide support to provide a reward list to be rewarded to corporate members, headhunting service providing server operators, and applicants, respectively.

The headhunting service providing server may receive a job application request for the job posting and reward list information from the terminal of the recommender or the applicant.

When the headhunting service providing server 400 provides a headhunting service in which an applicant directly applies for the job posting or applies for the job posting through a recommender, the headhunting service providing server 400 lists rewards for each of the corporate member, the headhunting service providing server operator, the recommender, and the applicant. can be sent to corporate members, headhunting companies, recommenders, and applicants respectively.

For example, the user of the recommender terminal 102 transmits a job application request of a recommender/applicant to the headhunting service providing server 400, and the corporate member (recruiter), the headhunting service providing server operator (headhunting company), the recommender and the applicant, respectively. A list of rewards can be additionally entered.

In detail, the headhunting service providing server 400 uses the screen of the application or web page where the headhunting service is provided, so that the recommender inputs the reward list for each of the corporate member, the headhunting service providing server operator, the recommender and the applicant. A signal for outputting the window' to the recommender terminal may be transmitted, and the recommender terminal may output the corresponding 'compensation list input window' upon receiving the signal for outputting the 'compensation list input window'. Meanwhile, it is also possible to output the 'compensation list input window' as a separate pop-up according to an implementation example.

For example, an example of a 'compensation list' may be set as follows.

Corporate Member: 20% of the recruiter's annual salary is compensated to the headhunt company.

Referrer: 10% of the reward amount received from the corporate member / or a specific amount

Applicant: A specific amount or a specific % of the applicant's annual salary

Headhunt company: Compensate the difference after paying the referral and applicant compensation

On the other hand, the compensation list is only an example and does not limit the embodiments of the present invention.

Thereafter, when the recommender completes inputting the reward money list through the recommender's terminal, the headhunting service providing server may transmit an inquiry message confirming support or not to the applicant's terminal and receive a response thereto. (S104)

That is, the headhunting service providing server may receive a signal about whether to accept the reward list from the applicant, the recruiter, and the headhunting company.

For example, the headhunting service providing server may additionally receive information on whether or not to accept the reward list proposed by the recommender through the applicant's terminal.

The applicant may transmit information on whether or not to apply and whether or not to accept the reward list to the headhunting service providing server through the applicant terminal.

Similarly, the headhunting company may input whether or not to accept the reward list received from the recommender terminal using the headhunting service providing server. In addition, the corporate member may transmit to the headhunting service providing server whether or not to accept the reward list received from the headhunting service providing server using the recruiter's terminal.

Through this, the headhunting service providing server receives whether or not to accept the reward list from recommenders, applicants, corporate members, and headhunting companies, and when each of the terminals 'accepts' the reward list, the final successful person according to the information included in the corresponding reward list. Compensation can be distributed in case of occurrence.

Meanwhile, according to an embodiment of the present invention, the headhunting service providing server performs 'compensation negotiation operation' when it does not receive 'acceptance' from at least one of recommenders, applicants, corporate members, and headhunting companies as a result of receiving whether or not to accept the reward list. can be performed.

Specifically, the compensation negotiation operation may be performed by providing a 'compensation negotiation list' from at least one of recommenders, applicants, corporate members (recruiters), and headhunting companies. If at least one of the recommenders, applicants, corporate members, and headhunting companies provides a reward negotiation list to the headhunting service providing server, the recommenders, applicants, corporate members, and headhunting companies use their respective terminals to pay for the compensation included in the compensation negotiation list. You can decide whether to accept or not.

In this case, when a signal accepting all of the compensation negotiation list is received by the headhunting service providing server, the compensation money may be distributed based on the compensation money included in the compensation negotiation list.

On the other hand, if compensation negotiations have not been made according to the compensation negotiation list (a signal not accepting the compensation negotiation list is transmitted to the headhunting service providing server), the headhunting service providing server may provide the final compensation negotiation list using an artificial intelligence model. there is.

3 is a diagram illustrating a reward list optimization model according to an embodiment of the present invention. Hereinafter, an artificial intelligence model will be described based on the illustrated diagram of FIG. 3 .

According to an embodiment of the present invention, the artificial intelligence model may be a reward list optimization model, and the model may be a model that performs an operation of optimizing a reward list using a neural network. The reward list optimization model may be implemented using a conventionally known regression model.

The artificial intelligence model may be stored and updated by a headhunting service providing server. The headhunting service providing server may set the embedding layer constituting the artificial intelligence model, model parameters and hyperparameters of the convolutional network.

Model parameters refer to parameters determined through learning, and may include weights of layer connections and biases of neurons. A hyperparameter means a parameter that must be set before learning in an artificial intelligence algorithm, and may include the number of network layers, the number of training data, a loss function (optimizer), and the like.

After the structure and parameter values of the artificial intelligence model are determined, the headhunting service providing server uses the information stored in the recruitment information DB and the corresponding type of data to form the embedding layer constituting the compensation list optimization model and the weights constituting the convolutional networks. A learning process of updating the in-model parameters may be performed. In addition, weights can be learned to generate a final reward list as an output value in the correlation of data input to the artificial intelligence model.

According to an embodiment of the present invention, the reward list optimization model may be an artificial intelligence model that outputs a reward list when recruitment information is input.

Specifically, the recruitment information corresponding to the input value of the artificial intelligence model is the size of the company (small and medium-sized enterprises, large corporations, etc.), industry group (law, manufacturing, service IT, etc.), employment field (eg, HR, distribution, production, R&D, etc.) etc.), job position (employee, assistant manager, manager, deputy manager, etc.) and employment type (part-time job, professional job, freelancer, full-time job, contract worker, etc.)

The reward list optimization model may be learned based on an actual recruitment database previously collected from a headhunting service providing server.

For example, there may be a history in which the following list of rewards has been distributed based on job postings corresponding to 'conglomerate, manufacturing, R&D, deputy manager, and full-time job' in the headhunting service providing server.

Corporate Membership: 20% (20 million won) of 100 million of the applicant's annual salary is compensated to the headhunt company.

Referrer: 10% (2 million won) of the reward amount (20 million won) received from the corporate member.

Applicant: Compensation of 10% (2 million won) of the applicant's annual salary (100 million won).

Headhunt Company: Compensation for the difference (20 million won - 2 million won - 2 million won) after payment of compensation to recommenders and applicants.

The headhunting service providing server may form and store the recruitment information and reward list into a database and learn a reward optimization model later.

According to an embodiment of the present invention, the reward optimization model may be stored in a headhunting service providing server, and may be periodically updated based on a reward list database for recruitment information.

For example, even if there is a lack of acceptance of the list of rewards suggested by the recommender, if a signal accepting all of the list of compensations proposed by the recommender is received by the headhunting service providing server, the artificial intelligence model may be updated using the corresponding data.

In addition, when there is a lack of acceptance of the compensation negotiation list, compensation list feedback data may be received from a person who lacks acceptance of the compensation negotiation list, and the artificial intelligence model may be updated using the corresponding compensation list.

Through the configuration of updating the artificial intelligence model, even if the compensation list is not negotiated, optimization of the compensation list using artificial intelligence is performed, and as the artificial intelligence model is advanced, the satisfaction level is higher for corporate members, recommenders, applicants, and headhunt companies. You may be able to suggest a list of rewards.

On the other hand, based on another embodiment of the present invention, the headhunting service providing method of the present invention can provide a recommender release function capable of rejecting the recommendation of an unwanted recommender, and in the case of direct application without going through the recommender, distribution to the recommender. There are cases in which headhunting services are provided that can receive up to the amount of compensation to be paid.

At this time, when the recommender cancellation function is used, it will also be possible to directly propose a reward list among applicants.

An embodiment in which the applicant directly provides a reward list may include an embodiment in which the recommender proposes a reward list as it is.

Meanwhile, the minimum compensation amount of the compensation list may be set to a predetermined value in order to prevent the update direction of the artificial intelligence model from being set differently from the original intention due to a decrease in the total amount of compensation included in the compensation list due to excessive competition.

The headhunting service providing server 400 may change the corresponding value to a predetermined value and use it as training data of the artificial intelligence model when there is a value less than or equal to the minimum compensation amount in the reward list for training the artificial intelligence model.

In addition, when the amount of compensation included in the reward list output by the artificial intelligence model is less than or equal to a predetermined amount, the amount of the reward list may be reset to a predetermined amount.

On the other hand, the provision of the reward list and the negotiation of the reward do not necessarily need to be performed when the recommender/applicant's request for job application is received for an efficient applicant recruitment process, and after the recruitment process based on FIG. It may also be possible that this is done immediately prior to distribution.

Those skilled in the art will understand that the various illustrative logical blocks, modules, processors, means, circuits, and algorithm steps described in connection with the embodiments disclosed herein are electronic hardware, (for convenience) , may be implemented by various forms of program or design code (referred to herein as software) or a combination of both.

The above-described present invention can be implemented as computer readable code on a medium on which a program is recorded. The computer-readable medium includes all types of recording devices in which data that can be read by a computer system is stored. Examples of computer-readable media include Hard Disk Drive (HDD), Solid State Disk (SSD), Silicon Disk Drive (SDD), ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage device, etc. there is

Claims (6)

A headhunting service providing method in which a computing device of a headhunting service providing server communicates with a user's terminal and reads and performs a headhunting service program,
Subscribing a user to act as a recommender or supporter as a general member;
When receiving a job posting registration request from a recruiter's terminal, posting a job posting according to the job posting registration request;
Receiving a job application request for the job posting and compensation list information from a terminal of the recommender or the applicant;
transmitting the compensation money list to the applicant's terminal, the recruiter's terminal, and the headhunting company;
receiving a signal from the applicant, the recruiter, and the headhunting company whether or not to accept the reward list;
if at least one of the applicant, the recruiter, and the headhunting company rejects the reward list, determining the reward list as a hiring reward using a reward list optimization model stored in the headhunting service providing server;
if the applicant, the recruiter, and the headhunting company accept the reward money list, determining the reward money list as a hiring reward;
transmitting the job application information to the recruiter's terminal;
Receiving information about a hiring result from the recruiter's terminal;
notifying whether or not the applicant has been hired to the terminal of the applicant according to the information on the result of the recruitment; and
Providing the hiring compensation money to the applicant, the recommender, and the headhunting company based on the compensation money list;
When at least one of the applicant, the recruiter, and the headhunting company rejects the reward list,
performing a reward negotiation operation of receiving a reward negotiation list from at least one terminal among the recommender, the applicant, the recruiter, and the headhunting company; and
When a signal that the recommender, the applicant, the recruiter, and the headhunting company all accept in the received compensation negotiation list is received by the headhunting service providing server, the compensation negotiation list is set as learning data of the compensation list optimization model, , Updating the reward list optimization model using the learning data,
How to provide headhunting services. According to claim 1,
The compensation list optimization model includes a regression model that performs a compensation list optimization operation using a neural network that outputs a compensation list when recruitment information is input.
How to provide headhunting services. According to claim 2,
The above employment information
Including at least one or more information of the detailed information of the job announcement corresponding to the size of the company, industry group, employment field, employment position and employment type,
How to provide headhunting services. delete According to claim 1,
Further comprising the step of receiving feedback data of the compensation negotiation list from a person who lacks acceptance of the compensation negotiation list, and updating the compensation list optimization model using the feedback data, when acceptance of the compensation negotiation list is lacking. doing,
How to provide headhunting services. According to claim 1,
The step of providing, by the applicant, a recommendation cancellation service for canceling the recommendation of the recommender through the applicant's terminal;
The providing of the recommendation cancellation service may include receiving a request for canceling the recommendation of the recommender by the applicant, charging the applicant a cancellation fee based on the recommender's employment compensation money, and providing the recommender with the recommender. Including the step of granting the status of, and upon receiving the first successful candidate information about the applicants, providing a header insurance service that shares the compensation to the recommenders of the first successful candidate.
How to provide headhunting services.

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