KR102419327B1 - Agent system for selective sorting and recommending of project information - Google Patents

Abstract

The present invention relates to an enterprise-freelance agent system through selective sorting and recommending of project information. The enterprise-freelance agent system includes: a project unit which selectively acquires and provides predetermined recruiting information for a project of a company; and an agent unit which selectively recommends and mediates freelancers to companies by selectively sorting predetermined recruiting information through preset machine learning.

Description

Enterprise-freelance agent system through selective salting and recording of project information {Agent system for selective sorting and recommending of project information}

The present invention relates to an enterprise-freelance agent system through selective salting and recording of project information. More specifically, it is a technology field related to a system that acquires corporate recruiting information, generates it as standardized project information, and mutually analyzes the company's project information through machine learning to mediate the matching between the company and the freelancer.

According to the issue report of the Software Policy Research Institute (SPRi) (Jan. 6, 2021), as non-face-to-face services expand in the aftermath of COVID-19, the demand for software (software) developers in all industries has increased. The recruitment of SW developers has been expanded not only in the IT field but also in the non-IT field. Accordingly, due to the phenomenon of excessive demand for software developers, competition for a wage increase occurred in the software developer employment market. Large corporations were able to actively participate in wage increase competition to secure talent, but small and medium-sized venture companies could not survive the wage increase competition and are experiencing severe manpower shortage.

In order to fill the shortage of manpower, small and medium-sized venture companies are running their business by hiring software freelancers only for the duration of the project instead of regular workers.

SW developers experience frequent turnover and employment changes in the process of growing up, so they do not often think of their current job as a lifelong job. In addition, since working as a freelancer is also recognized as a career, working as a freelancer helps you to prove your skills by gaining experience and forming a career.

In this process, the role of the job brokerage platform is expected to expand. The job brokerage platform serves as an intermediary between freelance developers and businesses. Freelancers can find jobs through the platform, and the platform will certify the freelancer's career and provide a decent job.

As an example of the related prior patent literature, "freelance service platform providing method, apparatus and program (Registration No. 10-2147450, hereinafter referred to as Patent Literature 1)" exists.

In the case of the invention according to Patent Document 1, in the method performed by a computer, obtaining information on one or more services provided by freelancers, obtaining information for evaluation of freelancers, information on the obtained services And based on the information for evaluation, calculating the success rate score of the freelancer and posting information about the freelancer together with the service provided by the freelancer and the calculated success rate score, a freelance service platform providing method is provided.

Another example of patent literature is “a method and system for matching a company and a freelancer (registration number 10-2007018, hereinafter referred to as Patent Literature 2)”.

In the case of the invention according to Patent Document 2, each includes a computer, a tablet PC, or an electronic device such as a laptop computer, a first corporate client, a first freelance client, and a server including a processor for executing instructions and a memory in which instructions are stored, , a first corporate client, a first freelance client, and a server that can communicate with each other through a network, a matching method of a matching system of a freelancer is disclosed.

As another example of a patent document, "a job search matching device and its job search matching method (registration number 10-2278627, hereinafter referred to as Patent Document 3)" exists.

In the case of the invention according to Patent Document 3, receiving a plurality of job information from a plurality of company terminals, receiving a plurality of job search information from a plurality of job seeker terminals, based on the plurality of job information and the plurality of job search information, providing a list of job seekers and a list of job seekers to each of the corporate terminal and the job seeker terminal; receiving evaluation information from the job seekers and job seekers whose matching has been established according to the job seeker list or the job seeker list; and the received evaluation information as learning data for a predetermined machine learning algorithm, and when the information of the job seeker and the information of the job seeker are input Learning a neural network model that extracts fitness according to may include steps.

Registration No. 10-2147450 Registration No. 10-2007018 Registration No. 10-2278627

The enterprise-freelance agent system through selective salting and recording of project information according to the present invention has been devised to solve the conventional problems as described above, and presents the following problems to be solved.

First, it is intended to generate predetermined recruiting information for a company's project.

Second, we want to verify and select the company's predetermined recruiting information.

Third, we want to match the company's project and the freelancer's portfolio with each other through machine learning.

The problems to be solved of the present invention are not limited to those mentioned above, and other problems not mentioned will be clearly understood by those skilled in the art from the following description.

Enterprise-freelance agent system through selective salting and recording of project information according to the present invention has the following problem solving means for the above-mentioned problem.

The enterprise-freelance agent system through selective salting and recording of project information according to the present invention includes: a project unit that selectively obtains and provides predetermined recruiting information for a project of the enterprise from an enterprise; and selectively acquiring the predetermined recruiting information from the project unit, selectively salting the predetermined recruiting information through preset machine learning, and selectively recommending and intermediating freelancers to the company. It may be characterized by including.

The project unit of the enterprise-freelance agent system through selective salting and recording of project information according to the present invention allows the enterprise to generate the predetermined recruiting information, the project progress stage, work field, task At least one of the following: scope, occupation, technical field, required specification, project name, work location, preference, input manpower, start date, end date, deadline, company information, expected unit price, desired experience, desired age, or person in charge information It may be characterized in that it comprises a recruiting input unit.

The project unit of the enterprise-freelance agent system through selective salting and recording of project information according to the present invention allows the enterprise to pay a predetermined payroll used for the enterprise's project to the freelancer, the enterprise It may be characterized in that it further comprises a payment information input unit for allowing the payroll payment information of the input.

The agent unit of the enterprise-freelance agent system through selective salting and recording of project information according to the present invention selectively converts the predetermined recruiting information obtained from the project unit into a preset pattern, It may be characterized in that it includes a converting unit that selectively generates predetermined project information.

The agent unit of the enterprise-freelance agent system through selective salting and recording of project information according to the present invention converts the predetermined recruiting information provided in the predetermined project information generated from the converting unit to the preset machine It may be characterized by further comprising a validation (validation) unit for selectively selecting the company by verification through learning.

The agent unit of the enterprise-freelance agent system through selective salting and recording of project information according to the present invention receives the portfolio information provided in advance from the freelancer, and through the preset machine learning, the previously provided It may further include a matching unit for selectively matching the company and the freelancer by performing a predetermined matching simulation between the portfolio information and the predetermined project information.

The agent unit of the enterprise-freelance agent system through selective salting and recording of project information according to the present invention receives the portfolio information provided in advance from the freelancer, and receives the previously provided portfolio information through the predetermined matching simulation. By calculating a matching rate between portfolio information and the predetermined project information, it may further include a recording unit for selectively recommending the predetermined project information to the top N freelancers.

The agent unit of the enterprise-freelance agent system through selective salting and recording of project information according to the present invention selectively generates and stores a predetermined payroll code from the payroll payment information input from the payment information input unit It may be characterized in that it further comprises a wealth.

The payment unit of the enterprise-freelance agent system through selective salting and recording of project information according to the present invention is characterized in that the payment unit of the freelance agent system pending the predetermined payroll payment for the project of the enterprise through the predetermined payroll code. can

The payment unit of the enterprise-freelance agent system through selective salting and recording of project information according to the present invention, when the enterprise and the freelancer are matched, payment of the predetermined payroll for the project in a preset period It can be characterized by selectively proceeding.

The enterprise-freelance agent system through selective salting and recording of project information according to the present invention of the configuration as described above provides the following effects.

First, it is possible to generate standardized project information for each company by converting predetermined recruiting information of a company into a preset pattern.

Second, companies can be selected by verifying project information through preset machine learning.

Third, the company's project information and the freelancer's portfolio can be matched with each other by performing matching simulation through machine learning.

Effects of the present invention are not limited to those mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the following description.

1 is a conceptual diagram of an enterprise-freelance agent system through selective salting and recording of project information according to an embodiment of the present invention.
2 is a conceptual diagram of the recruiting input unit of the enterprise-freelance agent system through selective salting and recording of project information according to an embodiment of the present invention.
Figure 3 is a conceptual diagram of the converting unit of the enterprise-freelance agent system through selective salting and recording of project information according to an embodiment of the present invention.
Figure 4 is a conceptual diagram of the salting unit of the enterprise-freelance agent system through selective salting and recording of project information according to an embodiment of the present invention.
5 is a conceptual diagram of a matching unit of the enterprise-freelance agent system through selective salting and recording of project information according to an embodiment of the present invention.
6 is a conceptual diagram of the recording unit of the enterprise-freelance agent system through selective salting and recording of project information according to an embodiment of the present invention.
Figure 7 is a conceptual diagram showing that the project unit of the freelance agent system through selective salting and recording of project information according to an embodiment of the present invention transmits predetermined recruiting information in parallel.
8 is a conceptual diagram of a payment information input unit and a payment unit of the enterprise-freelance agent system through selective salting and recording of project information according to an embodiment of the present invention.

Enterprise-freelance agent system through selective salting and recording of project information according to the present invention can make various changes and can have several embodiments, specific embodiments are illustrated in the drawings and detailed in the detailed description I would like to explain However, this is not intended to limit the present invention to specific embodiments, and it should be understood to include all modifications, equivalents and substitutes included in the spirit and scope of the present invention.

1 is a conceptual diagram of an enterprise-freelance agent system through selective salting and recording of project information according to an embodiment of the present invention. 2 is a conceptual diagram of the recruiting input unit of the enterprise-freelance agent system through selective salting and recording of project information according to an embodiment of the present invention. Figure 3 is a conceptual diagram of the converting unit of the enterprise-freelance agent system through selective salting and recording of project information according to an embodiment of the present invention. Figure 4 is a conceptual diagram of the salting unit of the enterprise-freelance agent system through selective salting and recording of project information according to an embodiment of the present invention. 5 is a conceptual diagram of a matching unit of the enterprise-freelance agent system through selective salting and recording of project information according to an embodiment of the present invention. 6 is a conceptual diagram of the recording unit of the enterprise-freelance agent system through selective salting and recording of project information according to an embodiment of the present invention. 7 is a conceptual diagram showing that the project unit of the freelance agent system transmits predetermined recruiting information in parallel - the enterprise through selective salting and recording of project information according to an embodiment of the present invention. 8 is a conceptual diagram of a payment information input unit and a payment unit of the enterprise-freelance agent system through selective salting and recording of project information according to an embodiment of the present invention.

Enterprise through selective salting and recording of project information according to the present invention - In the case of a freelance agent system, as shown in FIG. 1, applying unit (100), project unit (project unit, 200) and It will include an agent unit (300).

First, in the case of the applying unit 100, it is configured to selectively obtain and provide predetermined career information of a freelancer from a freelancer.

The applying unit 100 intends to acquire predetermined career information input through a freelancer's terminal, for example, a mobile phone, a smartphone, a notebook computer, a tablet PC, a desktop, and the like.

The predetermined career information referred to herein may be defined as information such as basic profile information, occupation, work field, and career of a freelancer.

The applying unit 100 is interconnected with the server of the agent unit 300 through networking or cloud, and can transmit and receive predetermined career information.

The predetermined career information provided from the applying unit 100 is preferably converted in the form of a predetermined portfolio.

In the case of the project unit 200, as shown in FIG. 2, it is configured to selectively obtain and provide predetermined recruiting information for a project from a company.

The project unit 200 is interworking with the server of the agent unit 300 through networking or cloud, so that it is possible to transmit and receive predetermined recruiting information.

In this case, the predetermined recruiting information of the project unit 200 may be input through a terminal (mobile phone, smart phone, notebook, computer, tablet PC, desktop) of the personnel in charge of the company, or the project manager of the company.

In addition, the project referred to herein refers to short-term or long-term projects such as development, publishing, design, and planning carried out by individual business owners and corporate business owners with business registration certificates. It can be defined as a condition of participation.

Enterprise through selective salting and recording of project information according to the present invention - In the case of the project unit 200 of the freelance agent system, the recruiting input unit 210, the former project input unit 220, the recruiting sending/receiving unit 230 and payment The information input unit 240 is included.

In the case of the recruiting input unit 210, as shown in FIG. 2, in order for the company to generate predetermined recruiting information, the project progress stage, work field, work scope, job type, technical field, required specification, project name, It is a configuration in which at least one or more information of the place of work, preference, input manpower, start date, end date, deadline, company information, expected unit price, desired experience, desired age, and person in charge information is input.

Information on the project may be input through the recruiting input unit 210 . First, there are analysis/design, planning, design, publishing, development, and operation in the progress stage of the project. Business fields include shopping malls, travel agencies, finance, securities, card, insurance, hospitals, universities, public institutions, logistics, accounting, manufacturing, construction, communication, distribution, production, media, education, semiconductors, automobiles, cryptocurrency, block chain, It is preferable that big data and the like exist.

There are developers, publishers, designers, planners, etc. in the job openings input through the recruiting input unit 210 .

In addition, through the recruiting input unit 210, the details of the project, such as the current development progress, total input manpower, current status, duties, work scope, preferential matters, required manpower, required specifications, work location, monthly unit price, etc. to be input do.

We aim to increase the matching probability and satisfaction between companies and freelancers by inputting project information in detail so that the best freelancers tailored to the project can apply.

In the case of the former project input unit 220 , it is configured to allow the company to input information about the former project previously performed.

At this time, the information on the previously progressed project may be input directly from the company, but in interworking with the agent unit 300, information about the project previously performed from the agent unit 300 may be retrieved and input.

Information on a project mainly carried out by the company may be provided through the former project input unit 220 , and evaluation information of the company from freelancers participating in each project is also preferably included.

In the case of the recruiting transmission/reception unit 230 , it is configured to transmit and receive predetermined recruitment information input from the company to the agent unit 300 .

At this time, it is preferable to convert the predetermined recruiting information into a binary sequence of 1 and 0 and transmit it to the agent unit 300 .

The recruiting transceiver 230 converts predetermined recruiting information into a binary sequence and generates as recruiting data (recruiting data).

The recruiting transmitting/receiving unit 230 lists the recruiting data in a line, omitting some of the recruiting data to generate the omission data, and the omission data and the recruiting data in which the omission data is missing in parallel to the agent unit 300, respectively. ) will be sent to

As shown in FIG. 7 , the recruiting transmitting/receiving unit 230 omits a part of the recruiting data to generate omission data, a recruiting listing unit 231, a recruiting circle unit 232 , a recruiting spin (recruiting spin) unit 233, and a recruiting omitting unit 234 are included.

In the case of the recruiting listing unit 231, as shown in FIG. 7, the recruiting data converted into a binary sequence is arranged in a line.

In addition, the recruiting listing unit 231 gives an order to each of the recruiting data arranged in a line.

That is, each of the recruiting data is assigned a unique order.

In the case of the recruiting circle unit 232, as shown in FIG. 7, the recruiting data to which the order is given is rolled and arranged in a circle.

In the case of the recruiting spin unit 233, as shown in FIG. 7, the recruiting data arranged in a circle is rotated clockwise or counterclockwise.

At this time, the rotation direction and the number of rotations of the recruiting data arranged in a circle are randomly determined.

In addition, information on the rotation direction and number of rotations of the recruiting data is shared only by the transmitting end and the receiving end, and the transmitting end and the receiving end here are the project unit 200 and the agent unit 300 .

In the case of the recruiting o-meeting unit 234, it is possible to arbitrarily select a predetermined area from among the recruiting data arranged in a circle, and to omit the selected predetermined area to generate the o-meeting data.

In this case, the predetermined area is an area including at least one or more recruiting data arranged in a circle, and is randomly determined, and information on the predetermined area is also shared only by the transmitting end and the receiving end.

The o-meeting data generated by the info meeting unit 234 and the recruiting data in which a predetermined area is omitted are each independently transmitted to the server of the agent unit 300 .

Through this, the recruiting transceiver 230 selectively converts the company's project information, arranges it randomly, and omits it.

In addition, the recruiting data, meeting data, predetermined area information, rotation information, and information on the number of rotations in the recruiting transmitter are shared only by the transmitter and the receiver, so that the company's trade secrets and project secrets are leaked to the outside can be prevented from becoming

In the case of the payment information input unit 240 , as shown in FIG. 8 , in order for a company to pay a predetermined payroll used for a project of the company to a freelancer, the company's payroll payment information is inputted.

The payment information input unit 240 inputs payment information for a company to pay wages for a project to a freelancer when a project starts.

The predetermined payroll referred to herein refers to wages, prices, monthly wages, salaries, etc. paid to freelancers, and the company's payroll payment information may be defined as payment information for the company to pay wages.

The payment information input unit 240 allows the company to select a payment method and input payment information according to the payment method.

Through the payment information input unit 240, the company provides a payment amount in advance to the agent unit (300). This is to prevent a situation in which freelancers do not receive payment in advance.

In addition, the company's payroll payment information input from the payment information input unit 240 is transmitted to the agent unit 300 through the recruiting transmitting/receiving unit 230, and similarly, the company's payroll information is also omit and transmitted in parallel, the company We want to protect your payment information.

In the case of the agent unit 300, as shown in Fig. 1, by selectively acquiring predetermined recruiting information from the project unit 200, and selectively salting predetermined recruiting information through preset machine learning, the company provides freelance It is a configuration that selectively recommends and mediates.

The agent unit 300 is interlocked with each of the applying unit 100 and the project unit 200, and receives each predetermined career information and recruiting information, and a customized freelancer that meets the conditions desired by freelancers and companies We will match each customized company.

Through the mediation of the agent unit 300, you can manage and coordinate the matched project from beginning to end, secure both information about the company and the freelancer for each project, and obtain various big data about matching and project process, results, and evaluation. there will be

Through this, the agent unit 300 will be able to provide information about the project that was previously carried out through the applying unit 100 and the project unit 200 .

In addition, the preset machine learning referred to herein is defined as learning to improve the ability of the agent unit 300 to mediate freelancers and companies by using the experience of reading, analyzing, and processing predetermined portfolio information and predetermined recruiting information. can

For example, the preset machine learning is to optimize a predetermined portfolio data of a freelancer and a company's recruitment information data using a model composed of a plurality of parameters.

The preset machine learning includes supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning, depending on the type of portfolio data, recruiting information data, and project data. learning) can be applied.

In addition, the preset machine learning is based on machine learning and deep learning using already commercialized artificial intelligence, and detailed mechanisms related to algorithms are omitted.

In the case of the agent unit 300 of the agent system through selective salting and matching simulation of the portfolio according to the present invention, a converting unit 310, a validation unit 320, a salting unit 330 , a matching unit 340 , a recommending unit 350 , and a payment unit 360 .

First, in the case of the converting unit 310, as shown in Fig. 3, by selectively converting predetermined recruiting information obtained from the project unit 200 into a preset pattern, predetermined project information for each company is selectively formed is a configuration that

The preset pattern formed by the converting unit 310 is for forming all information input by companies in different formats to fit a standardized frame.

That is, the predetermined project information may be defined as recruiting information formed according to a preset pattern.

The converting unit 310 is to automatically convert the information about the recruitment input by companies in various formats into a single form.

It is possible to accurately compare and analyze the recruiting information for a plurality of projects within the agent unit 300 through the converting unit 310 .

In the case of the validation unit 320, the company is selectively selected by verifying the predetermined recruitment information provided in the predetermined project information generated by the converting unit 310 through preset machine learning.

The validation unit 320 performs verification of the integrity and validity of the recruiting information in order to determine whether the project information input by the person in charge of the company is true.

For example, the validation unit 320 is interlocked with an external server based on preset machine learning to receive corporate financial statements, corporate credit evaluation information, investment information, cooperative company information, etc., and the company's stability, profitability, and activity Based on information such as , cash flow, company size, feasibility, reliability, labor-management relations, business-related, and manager-related information, it is possible to verify the company's project execution capability.

Through this, it is possible to fact-check the company's project information, and if the company has written the project information false, it can be revealed and the company can be selected.

In the case of the salting unit 330, as shown in FIG. 4, a predetermined project of the company verified by the validation unit 320 is salted based on a preset standard.

The salting unit 330 arbitrarily arranges project information of an unspecified number of companies based on a preset standard in order to disclose it to freelancers.

The preset criteria referred to here can be defined by project grade, project description, project implementation area, and the like.

For example, as shown in FIG. 4 , the salting unit 330 can sort predetermined project information according to grades through preset machine learning. The grade is classified into elementary/intermediate/advanced, and allows freelancers to sort and view only predetermined project information corresponding to their career and grade.

In the case of the matching unit 340, as shown in Fig. 5, by receiving the portfolio information provided in advance from the freelancer, and through preset machine learning, the portfolio information and the predetermined project information provided in advance are subjected to a predetermined matching simulation. In the process, it is a configuration that selectively matches companies and freelancers.

The predetermined simulation includes the project progress stage, work field, work scope, job type, technical field, required specification, project name, work location, preference, input manpower, start date, end date, deadline, company information, Select at least one of the expected unit price, desired experience, desired age, and person in charge information to proceed.

For example, the first matching is performed by filtering and extracting predetermined project information sorted by grade from the salting unit 330 and a portfolio previously provided from the freelancer by the same grade. For example, if predetermined project information and portfolio information corresponding to the intermediate level are extracted through primary matching, the extracted predetermined project information is again filtered by project technology, and a freelancer's portfolio matching the description of the predetermined project information is extracted Thus, the second matching is carried out.

In this way, it is possible to match companies and freelancers by repeating the matching simulation several times.

In the case of the recording unit 350, as shown in FIG. 6, by receiving the portfolio information provided in advance from the freelancer, and calculating a matching rate between the portfolio information and the predetermined project information provided in advance through a predetermined matching simulation, It is a configuration in which predetermined project information is selectively recommended to the top N freelancers.

It is desirable to set the criteria for the top N people here to be five or ten times the number of manpower that the company puts into the project or the number of manpower required.

For example, when the number of manpower that the company intends to put into a given project is 3, it is possible to recommend the given project information to 15 or 30 freelancers.

The recording unit 350 may calculate a matching rate from a predetermined matching simulation through preset machine learning.

The matching rate here is preferably calculated as (company-freelancer matching number)/(predetermined portfolio reading number)*100 or (company-freelancer matching number)/(predetermined project reading number)*100.

In the case of the payment unit 360, as shown in FIG. 8 , a predetermined payroll code is selectively generated and stored from the company's payroll payment information input from the payment information input unit 240 .

The payment unit 360 generates corporate payroll payment information as a predetermined payroll code. The predetermined payroll code may be defined as a code composed of letters or numbers.

At this time, the predetermined payroll code allows only the agent unit 300 to be generated. The predetermined payroll code can convert payroll payment information into a predetermined payroll code through a preset rule, and the preset rule is a rule that only the agent unit 300 knows, so that only the agent unit 300 can make a payment This is to secure the payment amount.

In addition, the payment unit 360 allows a predetermined payroll payment for a project of the company to be pending (pending) through a predetermined payroll code.

Pending referred to here can be defined as receiving the payment for a company's project in advance from the company and keeping the agent, for example, it is preferable that the agent put it in an escrow account.

That is, when the company and the freelancer match, the payment unit 360 receives the payment for the project from the company and takes care of it, and selectively proceeds with payment of a predetermined payroll for the project at a preset period to pay the freelancer. let it be

For example, when a company and a freelancer are matched, a contract for wage payment is concluded. The preset cycle referred to here can be defined as a wage payment cycle according to the contract details.

The agent unit 300 generates a predetermined payroll code in advance so that wages are automatically paid to the freelancer at a preset period according to the contract details.

It is desirable to ensure that wages are paid by referring to whether the freelancer has implemented the project.

Through the payment unit 360, freelancers are prevented from taking the money for the project, and it is possible to protect the rights and interests of freelancers.

The scope of the present invention is determined by the matters described in the claims, and parentheses used in the claims are not described for selective limitation, but are used for clear components, and descriptions in parentheses are also interpreted as essential components. should be

100: applying unit
110: career input unit
120: needs input unit
130: history input unit
140: career transceiver
200: project unit
210: recruiting input unit
220: former project input unit
230: Recruiting transceiver
240: payment information input unit
300: agent unit
310: converting unit
320: validation unit
330: salting unit
340: matching unit
350: recording unit
360: payment unit

Claims (10)

a project unit that selectively obtains and provides predetermined recruiting information for a project of the enterprise from the enterprise; and
An agent unit that selectively acquires the predetermined recruitment information from the project unit and selectively salts the predetermined recruitment information through preset machine learning to selectively recommend and mediate freelancers to the enterprise but,
The project unit is
In order for the company to generate the predetermined recruitment information, the project progress stage, work field, work scope, job type, technical field, required specification, project name, work location, preferential treatment, input manpower, start date, end date, deadline , Recruitment input unit for inputting at least one or more of company information, expected unit price, desired career, desired age, or person in charge information; and
and a payment information input unit for inputting payroll payment information of the company in order for the company to pay a predetermined payroll used for the project of the company to the freelancer,
The agent unit,
a converting unit for selectively converting the predetermined recruiting information obtained from the project unit into a preset pattern, and selectively generating predetermined project information for each company; and
a payment unit for selectively generating and storing a predetermined payroll code from the payroll payment information input from the payment information input unit;
The payment unit,
Pending the predetermined payroll payment for the project of the company through the predetermined payroll code,
When the company and the freelancer are matched, the company through selective salting and recording of project information, characterized in that the payment of the predetermined payroll for the project is selectively performed at a preset period - a freelance agent system.
delete delete delete According to claim 1, wherein the agent unit,
By verifying the predetermined recruitment information provided in the predetermined project information generated from the converting unit through the preset machine learning, it characterized in that it further comprises a validation (validation) unit for selectively selecting the company, Enterprise-freelance agent system through selective salting and recording of project information.
The method of claim 5, wherein the agent unit comprises:
By receiving the portfolio information provided in advance from the freelancer, and performing a predetermined matching simulation between the previously provided portfolio information and the predetermined project information through the preset machine learning, the company and the freelancer are selectively matched The enterprise through selective salting and recording of project information, characterized in that it further comprises a matching unit - freelance agent system.
The method of claim 6, wherein the agent unit,
By receiving the portfolio information provided in advance from the freelancer, and calculating a matching rate between the portfolio information provided in advance and the predetermined project information through the predetermined matching simulation,
The enterprise-freelance agent system through selective salting and recording of project information, characterized in that it further comprises a recording unit for selectively recommending the predetermined project information to the top N freelancers.
delete delete delete

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