Design And Implementation Of Job Matching System

Along with refining social division of labor, many job-hunting websites, which have massive information of worker and job, seem too clumsy and maladroit to fit for the enterprise recruitment. Nowadays, for each business, giving the professional and detailed domain service has been a mainstream in job-hunting. For more efficiency and security with lower cost, most companies ask the professional job-hunting agencies to search talents or elites. The success of job-hunting agencies depends on two factors:grasping the efficient information quickly and comprehensive, good job-hunting agents with rich experience of recruitment. However, it is difficult to acquire the above conditions to get better performance.In this paper, a job-hunting and job-matching system, named HHM, is developed to try to solve the above problems in job-hunting agencies. By utilizing the related technologies of vertical search, the HHM gathers the information of worker and job from multiple job-hunting websites with duplicate removing and data clustering analyzes the latent semantics of information of worker and job with full-text search, provides better job-worker matching. In the other side, HHM keeps track of the key points in each search of job-hunting agents, records the professional experience of job hunting and matching, lower the subjective risk of agents.Finally, the HHM system has been applied in a job-hunting agency in America. The runtime process showed it has good performance in job hunting and matching, which can achieve more economic profit.