The Research And Implementation Of The Recruiment Information And Resume Intelligent Matching System

In the era of big data,various recruitment platforms continue to emerge,and they are also facing the dilemma of "information overload" while providing users with colorful online recruitment services.In order to mine valuable information from massive resumes and job information,recommendation algorithms and text matching algorithms have been applied to the recruitment field.However,most of the existing recommendation systems only seek to maximize user satisfaction from a certain aspect of job applicants or enterprises,and cannot simultaneously consider the satisfaction of both job applicants and enterprises,which reduces the practicality of the system to a certain extent.At the same time,due to the particularity of resume text and position text,the traditional text matching algorithm can not meet the actual needs.Therefore,it is imperative to design and implement an intelligent matching system that takes into account the satisfaction of both job seekers and enterprises.This thesis proposes an intelligent matching model of recruitment information and resume by analyzing the text features of job information and resume information.In this model,different calculation strategies are adopted for structured text and unstructured text in recruitment information and resume.For structured text,a feature satisfaction calculation model is used for calculation;for unstructured text,WMD is used to calculate the text similarity.According to the results of both calculations,the matching degree matrix of position and resume can be constructed,and resumes and position information with higher matching degrees are selected as the final result.The experiment verifies the superiority of the proposed model by comparing its performance with the traditional user-based recommendation algorithm and text matching algorithm on the actual recruitment data set.In order to apply the intelligent matching algorithm of recruitment information and resume to practical applications,this thesis designs and implements an intelligent matching system of recruitment information and resume.This includes job search systems and corporate recruitment systems which use MVC and three-tier architecture,Bootstrap responsive layout,React Native and other technologies.This thesis implements a job search system including the Web side,Android and i OS client,We Chat applet,and Web-side enterprise recruitment system.In addition to the core intelligent matching function,extended functions such as resume search,resume management,job search,and job management are also implemented.Furthermore,this thesis also implements the visualization of recruitment data,including statistics,analysis and display of the data related to the intelligent matching algorithm in the database.Finally,this thesis carried out the functional test,security test and performance test of the intelligent matching system.By analyzing the performance test report,it was verified that the performance of the system meets the basic needs of the initial operation,and can provide online job search and recruitment services for both job seekers and enterprises,which improves the efficiency of job search and recruitment.