Application of Web-Based Data Mining in Personalized Online Recruiting System

Online recruiting methods become an important part in the recruitment system. However, the lack of personal service in a Web environment is one of development bottlenecks of online recruiting system. First, this paper analyzes single online candidate´s personal requirements. According to their requirements, a personalized recommendation system framework is proposed based on the technology of Web usage mining. The system provides individual recommendations in accordance with the analysis of single job seeker´s searching custom and interest, so the quality of service could be improved. Then, this paper researches on two key algorithms: maximum forward path (MFP) mining algorithm and association rules mining algorithm, and implements the programming of the two algorithms in the proceed of Web-based data preprocessing and mining .Finally, the result of the test indicates that the system designed in this paper is feasible.