CN113435841A - Talent intelligent matching recruitment system based on big data - Google Patents
Talent intelligent matching recruitment system based on big data Download PDFInfo
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Abstract
The invention provides a talent intelligent matching recruitment system based on big data. Comprising a recruiter module: the system is used for releasing the recruitment post, acquiring and screening resumes of job seekers, screening the resume of the job seekers and determining intention job seekers; job seeker module: the resume drawing system is used for uploading job-seeking resumes, drawing resumes, determining intention posts and delivering resumes to the intention posts; big data processing module: the job application resume is matched with the recruitment post through big data, and the post matching degree of the intention job seeker is determined; a server module: and the system is used for storing recruitment post information, job hunting information and final matching degree. The invention has the beneficial effects that: according to the invention, through big data matching, job seekers can find the posts with higher intention, and job seekers can find more suitable job seekers by adopting the recruiting posts.
Description
Technical Field
The invention relates to the technical field of talent information processing, in particular to a talent intelligent matching recruitment system based on big data.
Background
At present, with the rapid development of network technology, the 5G technology is gradually mature, so that better network platform experience is brought; meanwhile, the employment number is increased year by year, and more job seekers seek jobs through the network recruitment platform; the recruitment enterprise and the job seeker can perform post recruitment and job application on the online job hunting platform; along with the change of the epidemic situation, the safety and the convenience of on-line job hunting are higher than those of off-line job hunting, the time cost on the road is left for job hunters, and the site cost for off-line job hunting is saved for companies; the existing online platform job hunting information is too messy, the matching degree of job hunters and enterprises is not accurate enough, the steps of the application process are not perfect enough, and some job hunters with missing resume information can be screened out due to screening conditions, but the working capacity of the job hunters is still strong enough.
Disclosure of Invention
The invention provides a talent intelligent matching recruitment system based on big data, which is used for solving the problems that the existing online platform is too messy in job hunting information, the matching degree of job hunters and enterprises is not accurate enough, and the steps of an application flow are not perfect; some job seekers with missing resume information can be screened out for the screening condition.
A talent intelligent matching recruitment system based on big data comprises:
a recruiter module: the system is used for releasing the recruitment post, acquiring and screening resumes of job seekers, screening the resume of the job seekers and determining intention job seekers;
job seeker module: the resume drawing system is used for uploading job-seeking resumes, drawing resumes, determining intention posts and delivering resumes to the intention posts;
big data processing module: the job application resume is matched with the recruitment post through big data, and the post matching degree of the intention job seeker is determined;
a server module: and the system is used for storing recruitment post information, job hunting information and final matching degree.
Preferably, the recruiter module comprises:
screening unit: the system is used for setting screening parameters for the recruitment post, screening the job hunting resume and determining the intention resume; wherein the content of the first and second substances,
the screening parameters comprise age ranges, sex parameters, college and university parameters, professional parameters, political face parameters, prize winning parameters, major and minor repair subject parameters and working experience parameters;
a positioning unit: the system is used for acquiring the intention resume and positioning the job seeker through the intention resume;
the assessment unit: the system is used for setting a job hunting assessment mode according to the number of job hunters and assessing the job hunters; wherein the content of the first and second substances,
the job hunting assessment mode comprises the following steps: single-round independent examination or multi-round comprehensive examination.
Preferably, the examination unit includes: single-round independent examination and multi-round comprehensive examination; wherein the content of the first and second substances,
the single-round independent examination and examination matches corresponding examination questions for job seekers through a large data question bank to obtain job seeker scores;
and performing multi-round comprehensive assessment on the job seeker by the recruiter to interview the job seeker in a multi-round stroke test mode and determining the intention job seeker.
Preferably, the job seeker module comprises:
an uploading unit: the resume management system is used for uploading job-seeking resumes and performing resume portrayal;
screening unit: used for screening the post which can be delivered according to the resume portrait;
a delivery unit: the system is used for selecting an intention position from the deliverable positions to deliver;
a docking unit: used for docking and delivering posts; wherein the content of the first and second substances,
the docking delivery station comprises: and (4) assessment butt joint and result butt joint.
Preferably, the big data processing module includes:
big data screening unit: the system is used for screening the resume uploading and the post uploading and extracting the information of the resume uploading and the post uploading;
a matching unit: the job matching system is used for performing job matching through the extracted information to generate matching degree and pushing the matching degree to job seekers and recruiters;
big data question bank unit: the system is used for generating single-round independent examination questions and multi-round comprehensive examination questions and testing job seekers;
intelligent interview unit: the online interview recording method is used for online interview and recording an online interview video for job hunting; wherein the content of the first and second substances,
the online interview comprises: and opening an online room, virtualizing a job seeker and virtualizing a recruiter.
Preferably, the matching unit generates a matching degree:
matching the matching degree through preset post requirements and job searching information, and carrying out normalization processing to generate the matching degree; wherein the content of the first and second substances,
the preset post requirements include: requirements of age range, gender, colleges, professions, political aspects, awards, major and minor matters and work experience;
the matching degree interval is [ 0-1 ], and when the matching degree is greater than the preset recruitment matching degree, the recruitment post is successfully matched with the job seeker.
Preferably, the docking unit comprises an examination docking and a result docking: wherein the content of the first and second substances,
the assessment butt joint is used for the job seeker to enter a preset assessment system to assess the intention posts to obtain assessment results;
the result docking is used for sending the assessment result to the big data processing module when the job seeker obtains the assessment result, and docking the job seeker to the job entry department when the assessment result is larger than the qualified result preset in the intention post; otherwise, sending the prompt message which is not in accordance with the current position.
Preferably, the server module includes:
a first storage unit: the system is used for storing recruitment post information, resume information of job seekers, screening result information and matching information;
a second storage unit: the system is used for storing large-data question bank information, examination detailed records and examination scores;
a derivation unit: and the system is used for exporting the qualified information of the job seekers to the recruiters.
Preferably, the server module further comprises:
a sampling unit: the system comprises a server, a server and a system, wherein the server is used for discretely sampling the resume for job hunting through the Latin hypercube, randomly generating K random resume samples and calculating the content characteristics of the resume samples;
a detection unit: the resume sample pool is established by the abnormal sample; wherein the content of the first and second substances,
the detection comprises the following steps: contact mode detection, academic calendar monitoring, school detection and work experience monitoring;
a gain calculation unit: the resume sample processing module is used for determining an average abnormal characteristic according to the abnormal sample and the information missing degree of the abnormal sample, determining the content gain of each resume sample by taking the average abnormal characteristic as a reference value, and taking the resume sample with the maximum content gain as a first priority resume sample;
a training unit: importing the first priority resume sample into the sample pool, and constructing a resume rating model based on comparison training;
a rating unit: and importing the resume sample into a resume rating model according to the resume rating model, and determining the priority grade of each resume.
Preferably, the training unit constructing the resume rating model based on the comparison training comprises:
selecting a recurrent neural network of a neural network model as a base model, importing the first priority resume sample into the base model, and performing feature modeling to generate a base model;
and taking the abnormal resume in the sample pool as a training set, importing the abnormal resume into the basic model for comparison training, and generating a resume rating model after the training is finished.
The invention has the beneficial effects that: according to the invention, through big data matching, job seekers can find out posts with higher intention, and job seekers can find out more suitable job seekers by adopting recruiting posts; compared with job hunting screening methods in the prior art, the method can accurately analyze resume information of talents, thereby judging which post the job hunter is suitable for.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a system block diagram of a talent intelligent matching recruitment system based on big data according to an embodiment of the present invention;
fig. 2 is a block diagram of a server module of a talent intelligent matching recruitment system based on big data according to an embodiment of the present invention;
fig. 3 is a component diagram of a recruiter module of a talent intelligent matching recruitment system based on big data according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
As shown in fig. 1, an embodiment of the present invention provides a talent intelligent matching recruitment system based on big data, including:
a recruiter module: the system is used for releasing the recruitment post, acquiring and screening resumes of job seekers, screening the resume of the job seekers and determining intention job seekers; the module is mainly used for screening resumes after the recruiter sends out the recruiting post and when the resumes of the job seekers are received, determining which job seekers are in the consideration range of the enterprise.
Job seeker module: the resume drawing system is used for uploading job-seeking resumes, drawing resumes, determining intention posts and delivering resumes to the intention posts; the job seeker uploads the resume through the system, after uploading, the job seeker can search for an intention post, and resume delivery is achieved after searching.
Big data processing module: the job application resume is matched with the recruitment post through big data, and the post matching degree of the intention job seeker is determined; the invention calculates the matching degree of the resume and the post of the application through big data, and further judges which job seekers are available talents.
A server module: and the system is used for storing recruitment post information, job hunting information and final matching degree. The server belongs to a module for information transfer and calculation, and can be regarded as a database and a server for data calculation call.
The working principle of the technical scheme is as follows: the recruiter module can be used for releasing recruitment information, the job seeker module can upload resumes, the big data processing module matches the uploaded resumes with the recruitment information, and the generated data information is stored in the server module.
The beneficial effects of the above technical scheme are: according to the invention, through big data matching, job seekers can find out posts with higher intention, and job seekers can find out more suitable job seekers by adopting recruiting posts; compared with job hunting screening methods in the prior art, the method can accurately analyze resume information of talents, thereby judging which post the job hunter is suitable for.
In one embodiment, the recruiter module comprises:
screening unit: the system is used for setting screening parameters for the recruitment post, screening the job hunting resume and determining the intention resume; in order to more accurately determine the intended job seeker, the invention realizes accurate screening in multiple directions by setting high-fine-grained screening parameters in a screening mode.
The screening parameters comprise age ranges, sex parameters, college and university parameters, professional parameters, political face parameters, prize winning parameters, major and minor repair subject parameters and working experience parameters;
a positioning unit: the system is used for acquiring the intention resume and positioning the job seeker through the intention resume;
the assessment unit: the system is used for setting a job hunting assessment mode according to the number of job hunters and assessing the job hunters; wherein the content of the first and second substances,
the job hunting assessment mode comprises the following steps: single-round independent examination or multi-round comprehensive examination.
When the number of job hunters is large during examination, the invention realizes the screening of the number of people through multiple rounds of comprehensive examination and determines the best people. If the number of people is small, the job seeker can meet the post requirement through single round of independent examination.
The working principle of the technical scheme is as follows: the post is screened for the job seeker through the screening unit, the job seeker is positioned, and the job seeker is examined.
The beneficial effects of the above technical scheme are: the screening parameters are multiple, and job hunting resumes more consistent with the recruiting posts can be screened out; the recruiters can select job seekers more accurately through single-round independent examination and multi-round comprehensive examination.
In one embodiment, the assessment unit comprises: single-round independent examination and multi-round comprehensive examination; wherein the content of the first and second substances,
the single-round independent examination matches corresponding examination questions for job seekers through a large data question bank to obtain job seeker scores; the large data question bank can select questions which are more consistent with the professional experiences of job seekers according to the working experiences of the job seekers, and deep excavation is convenient to be carried out on the abilities of the job seekers.
And performing multi-round comprehensive assessment on the job seeker by the recruiter to interview the job seeker in a multi-round stroke test mode and determining the intention job seeker.
The working principle of the technical scheme is as follows: the single round of independent examination can be used for examining the job seeker through the large data question bank, and the multiple rounds of comprehensive examination can be combined into two or more examination modes for examining the job seeker.
The beneficial effects of the above technical scheme are: the richness of the assessment mode and the accuracy based on the big data can better select job seekers for the recruiters, the job seekers can be independently assessed in a single round, and assessment on the job seekers can be realized according to the self abilities of the job seekers. The best talents can be screened out through multiple rounds of examination.
In one embodiment, the job seeker module comprises:
an uploading unit: the resume management system is used for uploading job-seeking resumes and performing resume portrayal;
the resume portrait is used for portraying the academic calendar, the subject, the work experience, the vocational skills and the like in the resume, and the post portrait is natural and can be screened through the resume portrait and the post portrait.
Screening unit: used for screening the post which can be delivered according to the resume portrait;
a delivery unit: the system is used for selecting an intention position from the deliverable positions to deliver;
a docking unit: is used for docking and delivering posts, wherein,
the docking delivery station comprises: checking and docking and result docking;
the working principle of the technical scheme is as follows: the job seeker uploads the job hunting resume, the system screens deliverable posts through the resume uploaded by the job seeker, the job seeker selects intentional posts from the posts to deliver, and then the job seeker participates in post assessment to obtain assessment results.
The beneficial effects of the above technical scheme are: the job seeker selects the post meeting job hunting conditions, job hunting quality of the job seeker is improved, and meanwhile the job seeker can participate in post assessment more quickly to obtain assessment results.
In one embodiment, the big data processing module comprises:
big data screening unit: the system is used for screening the resume uploading and the post uploading and extracting the information of the resume uploading and the post uploading;
a matching unit: the job matching system is used for performing job matching through the extracted information to generate matching degree and pushing the matching degree to job seekers and recruiters;
big data question bank unit: the system is used for generating single-round independent examination questions and comprehensive examination questions and testing job seekers;
intelligent interview unit: the online interview recording method is used for online interview and recording an online interview video for job hunting; wherein the content of the first and second substances,
the online interview comprises: and opening an online room, virtualizing a job seeker and virtualizing a recruiter. The method for virtualizing the job seeker and the recruiter is to establish a virtual interview space based on a network space in a mode of simulating the job seeker, the recruiter and a 3D portrait, and perform 3D virtual interview.
The working principle of the technical scheme is as follows: after the recruiter issues the recruiting post and the job seeker uploads the resume, the system screens and matches the post and the job seeker to generate a matching degree, different examination questions are generated through a large data question bank, and the intelligent interview can be performed on line on job seekers.
The beneficial effects of the above technical scheme are: through the big data, the screening and matching of job seekers and posts are more accurate, the big data question bank provides different examination questions for different recruitment posts, and the selection operation is quicker.
In one embodiment, the matching unit includes generating a degree of matching:
matching the matching degree through preset post requirements and job searching information, and carrying out normalization processing to generate the matching degree; wherein the content of the first and second substances,
the preset post requirements include: requirements of age range, gender, colleges, professions, political aspects, awards, major and minor matters and work experience;
the matching degree interval is [ 0-1 ], and when the matching degree is greater than the preset recruitment matching degree, the recruitment post is successfully matched with the job seeker, so that the time cost of the post is saved.
In one embodiment, the docking unit comprises an assessment docking and a result docking: wherein the content of the first and second substances,
the assessment butt joint is used for the job seeker to enter a preset assessment system to assess the intention posts to obtain assessment results;
the result docking is used for sending the assessment result to the big data processing module when the job seeker obtains the assessment result, and docking the job seeker to the job entry department when the assessment result is larger than the qualified result preset in the intention post; otherwise, sending the prompt message which is not in accordance with the current position.
The working principle of the technical scheme is as follows: the job seeker which finishes the examination is docked to the company if the job seeker passes the examination, and prompt information is sent if the job seeker does not pass the examination
The beneficial effects of the above technical scheme are: in the aspects of assessment docking and company docking, the time cost is saved for job seekers and recruiters, and the assessment efficiency is improved.
In one embodiment, the server module comprises:
a first storage unit: the system is used for storing recruitment post information, resume information of job seekers, screening result information and matching information;
a second storage unit: the system is used for storing large-data question bank information, examination detailed records and examination scores;
a derivation unit: and the system is used for exporting the qualified information of the job seekers to the recruiters. (ii) a
The working principle of the technical scheme is as follows: the system can store the information uploaded by job seekers, the information released by recruiters, the screening result, the matching information, the large data question bank information, the detailed examination record and the examination score as the comprehensive consideration and evaluation data of the job seekers.
The beneficial effects of the above technical scheme are: the job seeker can be stored, and evaluation on the job seeker is facilitated.
In one embodiment, the server module further comprises:
a sampling unit: the system comprises a server, a server and a system, wherein the server is used for discretely sampling the resume for job hunting through the Latin hypercube, randomly generating K random resume samples and calculating the content characteristics of the resume samples; the Latin hypercube is a method for approximate random sampling from multivariate parameter distribution, belongs to a layered sampling technology, and is commonly used for computer experiments or Monte Carlo integration and the like. The sample resume generated in the way has great randomness, is more suitable for detection and feature calculation, and is also more suitable for the actual resume features.
A detection unit: the system comprises a resume sample pool, a resume sample analysis module, a resume analysis module and a resume analysis module, wherein the resume sample pool is used for detecting the content of the resume sample, judging whether an abnormal sample exists in the resume sample, and establishing a resume sample pool through the abnormal sample; wherein the content of the first and second substances,
the detection comprises the following steps: contact mode detection, academic calendar monitoring, school detection and work experience monitoring; the abnormal detection mainly judges whether the resume has information loss or not, and the more information, the more complete the evaluation is, and certainly the detection is also biased; for example, where the job experience is rich, yet consistent with the business position, its priority must be high. If there is no working experience or learning experience, the winning status is complete and the priority is lower according to the contact way.
A gain calculation unit: the resume sample processing module is used for determining an average abnormal characteristic according to the abnormal sample and the information missing degree of the abnormal sample, determining the content gain of each resume sample by taking the average abnormal characteristic as a reference value, and taking the resume sample with the maximum content gain as a first priority resume sample; the gain calculation is used for calculating the resume condition which best meets the sample pool by taking the information missing degree of the abnormal sample as the characteristic of the abnormality and taking the average characteristic as a reference. Then, the most complete and most elegant resume in the abnormal resumes is determined through the calculation mode.
A training unit: importing the first priority resume sample into the sample pool, and constructing a resume rating model based on comparison training; the training unit is used for constructing the resume rating model so as to judge the level of the resume of the job seeker and facilitate the establishment of the resume rating model
A rating unit: and importing the resume sample into a resume rating model according to the resume rating model, and determining the priority grade of each resume. The rating unit scores resumes through a resume rating model, and accordingly determines the occupation status of each person.
The invention has the beneficial effects that: the invention can calculate the integrity and priority of the abnormal resume by establishing a sample pool of the abnormal resume, and the gain condition of the abnormal resume calculation is mainly aimed at preventing talents from losing to the maximum extent according to resume data because the resumes of some talents are originally missing but not affecting the talents as good employees. Compared with the direct screening of the existing recruitment system, the recruitment system has better effect. For example: and detecting the contact information, and if no contact information exists, rating the contact information first and then contacting the contact information through the APP for job hunting.
In one embodiment, the training unit constructing the comparison training-based constructed resume rating model comprises:
selecting a recurrent neural network of a neural network model as a base model, importing the first priority resume sample into the base model, and performing feature modeling to generate a base model;
and taking the abnormal resume in the sample pool as a training set, importing the abnormal resume into the basic model for comparison training, and generating a resume rating model after the training is finished.
The invention is greatly different from the prior art when building a resume model, the prior art generally trains directly through a general network model to obtain a resume rating model, and the invention builds a base model based on talent screening through a first priority resume. All talent screens were referenced to the base model. The rating height of the model at the time of abnormal resume rating is limited. And then, after the trained basic model is changed into a resume rating model through comparison, when the resumes are rated, the talents are selected by the most important position requirement factors regardless of abnormal resumes or normal resumes.
As an embodiment of the present invention: the server module further comprises:
sending a corresponding recommendation result to a target terminal corresponding to the job seeker according to a preset recommendation rule, wherein the steps are as follows:
calculating the recommendation weight adopting the ambiguity recommendation algorithm according to the following formula:
wherein eta represents the recommendation weight of the digital fuzzy recommendation algorithm; a represents the number of basic conditions contained in job hunting indexes of corresponding job hunters when the digital fuzzy recommendation algorithm is adopted for recommendation; delta represents important indexes in the information required by the job seeker (such as salary, promotion mechanism and the like of the job seeker); epsilon represents a very important indicator (a recruitment academic requirement of the recruiter, etc., which is a comprehensive indicator) in the recruiter requirement information; epsilon represents a very important indicator in the job seeker or recruiter requirement information; beta represents the number of the indispensable conditions (such as academic requirements, work experience requirements and occupational skill requirements) contained in the recruitment indicator of the recruiter when the digital fuzzy recommendation algorithm is adopted for recommendation;
calculating the fault tolerance rate of the recruitment website during recommendation according to the following formula:
wherein P represents the error rate of the recruitment website during recommendation; theta represents an error coefficient when the website recruitment is recommended; eta represents the recommendation weight when the digital fuzzy recommendation algorithm is adopted for recommendation; gamma represents the number of times of errors in recommendation in the recruitment website recommendation period; k represents the total number of recommendations within the recruitment website recommendation period; tau represents the maximum number of times of errors allowed in the total number of times of recommendation in the recruitment website recommendation period; ζ represents a correction coefficient of the recruiting website;
comparing the error rate obtained by calculation with a preset error rate;
and if the error rate is lower than the preset error rate, the recruitment website sends a recommendation result to the job seeker.
In the embodiment, the digital fuzzy recommendation algorithm comprises actions of job seekers, including job browsing operation, delivery establishing operation, basic information filling operation and the like, the mathematical algorithm of the fuzzy algorithm is used for calculating, positions of job seekers which may want to seek job are predicted and recommended, the fuzzy set can be performed on information of the job seekers, and then the required positions are predicted. The ambiguity recommendation algorithm also comprises the steps of obtaining the recent operation information of the user, not having memory on the previous operation of the user, and recommending a position or a website which may be required to the user through the current operation, such as a talent career net.
In this embodiment, the job hunting index refers to a basic condition set by the job seeker or recruiter during job hunting or recruiting, such as minimum academic requirement, work experience, and the like that must be satisfied
In this embodiment, the job hunting indexes refer to positions obtained by comparing the importance degree of a certain index with the importance degrees of other indexes in job hunting by a job seeker, and assign values to the indexes, and substitute the assignments into corresponding positions for calculation during calculation, such as age, academic calendar, and work experience. In this embodiment, the job seeker can set job hunting indexes in the adjusted ambiguity by himself or herself.
The beneficial effects of the above technical scheme are: according to the scheme, the accuracy of the website during recommendation is ensured, meanwhile, the importance degree of the index can be set artificially, the method is convenient for recommending the posts or staff suitable for the website according to the condition of each person, and the using effect of the method is improved.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A talent intelligent matching recruitment system based on big data is characterized in that:
a recruiter module: the system is used for releasing the recruitment post, acquiring and screening resumes of job seekers, screening the resume of the job seekers and determining intention job seekers;
job seeker module: the resume drawing system is used for uploading job-seeking resumes, drawing resumes, determining intention posts and delivering resumes to the intention posts;
big data processing module: the job application resume is matched with the recruitment post through big data, and the post matching degree of the intention job seeker is determined;
a server module: and the system is used for storing recruitment post information, job hunting information and final matching degree.
2. The big-data based talent intelligent matching recruitment system of claim 1 wherein the recruiter module comprises:
screening unit: the system is used for setting screening parameters for the recruitment post, screening the job hunting resume and determining the intention resume; wherein the content of the first and second substances,
the screening parameters comprise age ranges, sex parameters, college and university parameters, professional parameters, political face parameters, prize winning parameters, major and minor repair subject parameters and working experience parameters;
a positioning unit: the system is used for acquiring the intention resume and positioning the job seeker through the intention resume;
the assessment unit: the system is used for setting a job hunting assessment mode according to the number of job hunters and assessing the job hunters; wherein the content of the first and second substances,
the job hunting assessment mode comprises the following steps: single-round independent examination or multi-round comprehensive examination.
3. The system for intelligent talent matching recruitment according to claim 2, wherein the single round of independent assessment and examination matches corresponding assessment questions through a big data question bank and information of job seeker working experience, specialty and academic history to obtain job seeker performance;
and performing multi-round comprehensive assessment on the job seeker by the recruiter to interview the job seeker in a multi-round stroke test mode and determining the intention job seeker.
4. The system for intelligent talent matching recruitment based on big data of claim 1 wherein the job seeker module comprises:
an uploading unit: the resume management system is used for uploading job-seeking resumes and performing resume portrayal;
screening unit: used for screening the post which can be delivered according to the resume portrait;
a delivery unit: the system is used for selecting an intention position from the deliverable positions to deliver;
a docking unit: used for docking and delivering posts; wherein the content of the first and second substances,
the docking delivery station comprises: and (4) assessment butt joint and result butt joint.
5. The system for intelligent talent matching recruitment based on big data as claimed in claim 1, wherein the big data processing module comprises:
big data screening unit: the system is used for screening the resume uploading and the post uploading and extracting the information of the resume uploading and the post uploading;
a matching unit: the job matching system is used for performing job matching through the extracted information to generate matching degree and pushing the matching degree to job seekers and recruiters;
big data question bank unit: the system is used for generating single-round independent examination questions and multi-round comprehensive examination questions and testing job seekers;
intelligent interview unit: the online interview recording method is used for online interview and recording an online interview video for job hunting; wherein the content of the first and second substances,
the online interview comprises: and opening an online room, virtualizing a job seeker and virtualizing a recruiter.
6. The system for intelligent talent matching recruitment based on big data as claimed in claim 5, wherein the matching unit generates the matching degree, comprising the following steps:
matching the matching degree through preset post requirements and job searching information, and carrying out normalization processing to generate the matching degree; wherein the content of the first and second substances,
the preset post requirements include: requirements of age range, gender, colleges, professions, political aspects, awards, major and minor matters and work experience;
the matching degree interval is [ 0-1 ], and when the matching degree is greater than the preset recruitment matching degree, the recruitment post is successfully matched with the job seeker.
7. The system for talent intelligent matching recruitment based on big data of claim 4 wherein the docking unit comprises an assessment docking and a result docking: wherein the content of the first and second substances,
the assessment butt joint is used for the job seeker to enter a preset assessment system to assess the intention posts to obtain assessment results;
the result docking is used for sending the assessment result to the big data processing module when the job seeker obtains the assessment result, and docking the job seeker to the job entry department when the assessment result is larger than the qualified result preset in the intention post; otherwise, sending the prompt message which is not in accordance with the current position.
8. The system for intelligent talent matching recruitment based on big data as claimed in claim 1, wherein the server module comprises:
a first storage unit: the system is used for storing recruitment post information, resume information of job seekers, screening result information and matching information;
a second storage unit: the system is used for storing large-data question bank information, examination detailed records and examination scores;
a derivation unit: and the system is used for exporting the qualified information of the job seekers to the recruiters.
9. A virtual reality moderator system based recommendation method according to claim 1 wherein said server module further comprises:
a sampling unit: the system comprises a server, a server and a system, wherein the server is used for discretely sampling the resume for job hunting through the Latin hypercube, randomly generating K random resume samples and calculating the content characteristics of the resume samples;
a detection unit: the resume sample pool is established by the abnormal sample; wherein the content of the first and second substances,
the detection comprises the following steps: contact mode detection, academic calendar monitoring, school detection and work experience monitoring;
a gain calculation unit: the resume sample processing module is used for determining an average abnormal characteristic according to the abnormal sample and the information missing degree of the abnormal sample, determining the content gain of each resume sample by taking the average abnormal characteristic as a reference value, and taking the resume sample with the maximum content gain as a first priority resume sample;
a training unit: importing the first priority resume sample into the sample pool, and constructing a resume rating model based on comparison training;
a rating unit: and importing the resume sample into a resume rating model according to the resume rating model, and determining the priority grade of each resume.
10. The virtual reality moderator system-based recommendation method of claim 9, wherein the training unit constructing a resume rating model based on comparison training comprises:
selecting a recurrent neural network of a neural network model as a base model, importing the first priority resume sample into the base model, and performing feature modeling to generate a base model;
and taking the abnormal resume in the sample pool as a training set, importing the abnormal resume into the basic model for comparison training, and generating a resume rating model after the training is finished.
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