個人化線上求職推薦系統之研究

CCUR > College of Business > Department of Information Management & Graduate Institute of Information Management > Thesis > Item 987654321/27485

Please use this identifier to cite or link to this item: https://irlib.pccu.edu.tw/handle/987654321/27485

Title:	個人化線上求職推薦系統之研究 A Personalized On-line Job Matching Recommender System
Authors:	陳柏翰
Contributors:	資訊管理研究所碩士在職專班
Keywords:	資料探勘群集分析內容導向過濾線上求職 data mining cluster analysis content-based filtering online job hunting
Date:	2006
Issue Date:	2014-06-17 14:33:20 (UTC+8)
Abstract:	近年來由於線上求職系統的出現，打破了多年來只能由傳統的報章雜誌媒體來進行求職的單一管道限制，也因此改變了求職者對於求職媒體管道的使用習慣。由於線上求職系統提供了更豐富、更多元的求才資訊，吸引了許多求職者的喜愛，也改變了求職媒體的生態，使得許多的求職者愈來愈仰賴以線上求職系統來找尋符合本身需求的工作機會。雖然線上求職系統具備了快速、方便、成本低廉等優點，且線上求職系統還能提供許多傳統求職方式所無法匹敵的功能，例如：線上刊登履歷、線上應徵工作等，但因龐大的求職、求才資料庫所帶來的致命傷，造成媒合機制無法保證其媒合結果的素質。　　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.
Appears in Collections:	[Department of Information Management & Graduate Institute of Information Management] Thesis

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