Research On Resume Selection In Enterprise Internet Recruitment Based On Machine Learning

In today's era of big data,all kinds of information data show geometric growth,but also impact the survival and development of enterprises,how to use information technology means to improve the current way of work,improve the operation efficiency of enterprises is crucial.The essence of competition among enterprises is the competition of talents.The quality and quantity of talents determine whether the company can develop for a long time.With more and more developed,information technology has been largely under the background of popularization of Internet,Internet recruitment has become the most domestic enterprises daily the most common way of recruitment,faced with the enormous talent resume on the Internet,how to rapidly and accurately found that meets the needs of company development and talent,become experts in recent years,many enterprises and scholars common focus.Resume screening,as an important part of human resource recruitment,involves the basis of subsequent interview and employment,and the quality of candidate list also determines the quality of talents in the enterprise.At present,enterprises are more dependent on human experience and subjective judgment in resume screening,which will have higher requirements on resume screening personnel.The current evaluation of human resources is aimed at the requirements of job requirements and screening,often through long-term work experience accumulated a set of fixed screening methods,but in fact it is the company's various positions of talent requirements combined with the needs of the company's current development stage is dynamically adjusted.In addition,faced with the inconsistency of resume style and format of various third-party recruitment platforms on the Internet,the difficulty of manpower selection is greatly increased,and the low efficiency also restricts the development of the company.This paper starts from the cost of recruitment in human resources to reduce the inefficiency of artificial resume screening.Specifically,it will combine the construction of job talent model before resume screening and the acquisition of key resume data on the Internet platform with machine learning algorithm as the program of resume automatic screening.On the basis of previous studies,this paper proposes a resume screening method based on dynamic adjustment of enterprise talent requirements,which,to some extent,reduces the cost of human resources recruitment and improves the efficiency of talent recruitment.In this paper,nanjing chengqin education technology co.,LTD.,a big data IT company,took the recruitment of real data r&d engineers as an example to verify the proposed Internet resume screening scheme.Two sets of samples were used for verification.The first group was 100 resume samples,and the second group was 100 resume samples on the basis of 100 resume samples.The qualified screening list was calculated by machine learning.In the first round,without changing the scheme,the stability of Internet resume screening scheme was verified by observing whether the conforming list obtained from the original sample subset was consistent with the case that the data sample was enlarged.In the second round of verification,after adjusting the relevant parameters,the scheme runs to determine whether the matching rate of resume screening is targeted.Through the sample test,it is found that this scheme has certain practical value,and can also provide support for other enterprises in the Internet resume screening work..