Research On Resume Evaluation And Selection Based On Internet Recruitment

With the rapid development of Internet industry,benefit from the development of the industry a large number of Internet companies also obtained fast development,the development of enterprises depends on the development of human resources,recruitment in time to meet the requirements of the enterprise of talent for enterprise development play a crucial role.Recruitment is a process of two-way communication,a large number of job seekers through Internet channels to resume to the position of enterprises in the recruitment website information page,corporate recruiters in recruitment website backstage resume information received a large number of applicants for the job.On the one hand,faced with hundreds and thousands of resumes,repetitive resume screening can affect the efficiency of the recruiter.On the other hand,due to the lack of knowledge on the competency of talents in the industry,the recruitment specialist cannot accurately screen out the resumes that meet the job requirements.The low efficiency and low accuracy of recruitment specialists in screening resumes will make enterprises unable to supplement human resources timely,which will affect the development of enterprises.In this study work in the resume screening evaluation of recruiters practical scenarios,combined with previous studies of Internet recruitment and screening resume evaluation,using the web crawler,factors evaluation method and GRNN neural network model is constructed,resume information search and evaluation selection model and applied to the actual recruitment work,after the web crawler search tool to grab your resume information,through factor evaluation method and expert sorting method to determine the weights of evaluation indexes and evaluation,formation candidate resume information factors evaluation scores,and resume the score in a general regression neural network GRNN model screening,Can be successfully selected to meet the requirements of job candidates resume,number,and returns the resume through this resume number,recruiters can view the information through the screening of candidate resume,and called for a follow-up interview process.On the one hand,the model of resume screening based on GRNN neural network proposed in this paper can screen qualified resumes with 95% accuracy,and greatly reduce the time of resume screening.On the other hand,the evaluation and screening method of resume proposed in the study has flexible resume evaluation and classification and screening ability,and its screening accuracy and efficiency have reached the expected target.And under the environment of large Internet enterprise's actual hiring experiments,the results meet the practical talents in the field of large Internet companies recruitment recruitment requirements,use conforms to the enterprise environment experiment method to verify the feasibility and effectiveness of this method.Proved web crawler resume information search CV screening methods and GRNN neural network model to a certain extent,can reduce repetitive work in the resume screening and enhance the accuracy in CV screening,so as to improve the efficiency of the recruitment exercise.