本研究將以國內某知名人力銀行求職與求才資料庫為對象，應用資料探勘(Data Mining)中內容導向過濾(Content-Based Filter-ing)及群集分析(Cluster Analysis) 等技術進行實證分析，藉以探討如何有效地運用資料探勘的技術從大量的求職與求才資料庫中挖掘出完整媒合資訊，以推薦適當的個人化媒合資訊給使用者。
In recent years, due to development of on-line job matching systems, looking for a job is no longer limited to follow the traditional way of getting related information from newspapers and magazines. By providing rich kinds of information, the on-line job matching systems have attracted more and more of job seekers. The on-line job match-ing system are fast, convenient, and low cost, and offers function of publishing resumes and applying for job online which traditional job-finding service can not provide. How-ever, a huge and powerful database is then needed to keep the records of available va-cancies and applicants and provide precisely matching results.
Based on the data from a famous domestic manpower bank, this study uses con-tent-based filtering and cluster analysis techniques popular in the data mining field to verify the matching results. This paper describes how to obtain complete matching in-formation from job matching database and recommend adequate personalized matched results to users.
