Design And Implementation Of Job Recruitment System Based On Data Mining Technology

Construction of Web-based employment system is to serve all kinds of businesses and various job hunting groups and build an interactive platform for businesses and job applicants. The thesis creates this platform, uses web data mining technique to analyze job applicant and recruiters so as to dig out contents hidden in network data and documents, uses classification analysis in data mining tasks to process data so as to find out valuable information.The thesis focuses on data mining technique, researches the classification of web data mining and processing technique, probes processing procedure of data mining technique on the basis of data mining technique at home and abroad. The thesis analyzes pattern discovery technology. In the phase, web data mining methods, such as classification, clustering, association rules are selected according to actual demands. The thesis researches the definition of web classification and classification methods in terms of Web data mining classification technology and focuses on researching the Bayesian theory and the simple Bayesian classifier and Bayesian belief networks so as to provide research basis for employment system classification. A processing model employment system based on Web data mining is established. It goes through four phases such as data preparation, data processing, the mining implementation and results analysis, classifies information by classification mining and establishes classification model of employment system on Weka platform by using Bayesian algorithm to find out employment requirements report.