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研究生: 李杰儒
Li, Jie Ru
論文名稱: 應用貝氏網路分析待業期關鍵影響因素之資料挖礦架構及個案研究
A Data Mining Framework for Analyzing Key Factors of Unemployment Duration Using Bayesian Networks and Case Studies
指導教授: 簡禎富
Chien, Chen Fu
口試委員: 李大華
劉念琪
吳佳虹
學位類別: 碩士
Master
系所名稱: 工學院 - 工業工程與工程管理學系
Department of Industrial Engineering and Engineering Management
論文出版年: 2016
畢業學年度: 104
語文別: 中文
論文頁數: 88
中文關鍵詞: 人力資本人力銀行待業期分析貝氏網路資料挖礦與大數據分析
外文關鍵詞: Human Capital, Human Resource Agency, Unemployment Duration Analysis, Bayesian Network, Data Mining and Big Data Analytics
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  • 本研究目的為發展待業期關鍵影響因素探討之資料挖礦與大數據分析架構,透過國內具指標性之某人力銀行網站的實際資料分析影響待業期之關鍵因素與各因素間之影響關係,從大量資料中萃取有意義之知識與樣型。本研究根據文獻回顧與整理,結合領域專家知識以建立研究假設,並整合貝氏網路、統計檢定與關聯係數等量化工具以篩選出求職者之「基本資訊、求職需求、教育程度、工作經驗與新工作類型」中有15項關鍵影響因素對於待業期具有顯著影響,進而透過貝氏網路以架構出潛藏於關鍵因素與待業期間複雜之影響關係,最後依循本研究提出之案例解析流程進行個案探討。研究結果反映出現今就業環境中,各領域的未來出路與進入各產業之待業情形、具有不同求職需求族群之就業走向與跨產業轉職之現況分析等資訊,例如:在特定產業中,累計3~6年工作經驗者之異動程度較高,可能具有較高的離職意圖與轉職行為,以及中高齡者再就業困難、區域性薪資落差等社會議題。本研究分析結果得以協助各類型求職者掌握周全資訊,更加了解就業市場現況、衡量自身在就業市場中之利基與發展走向,供其作為求職與職涯規劃之參考,同時也可以提供政府單位與徵才企業研擬應對策略之參考。對於人力銀行業者而言,得以基於貝氏網路推論各路徑待業期長短之機率,提供求職者與徵才企業更精確之推薦媒合服務,協助各領域求職者找到最有利之求職方向。


    This study aims to develop a data mining framework to analyze key factors of unemployment duration and the complex relationships among each factor. Conducted on the basis of real data collected from a representative Human Resource Agency in Taiwan. In order to extract latent knowledge and patterns from huge data about job seekers. This study formulates research hypotheses based on literature review, domain expert knowledge and supported by Bayesian Network, statistical test and correlation coefficient to screen out 15 key factors of the job seekers’ “general information, job requirement, education, working experience and new work category” have a significant effect on unemployment duration. Then, using Bayesian network to clarify the relationships among each factor and unemployment duration. Finally, this study presents a process of case studies that can extract the useful knowledge of data mining results efficiently. Major findings indicate that unemployment duration difference among each field, the employment tendency of different type of job seekers and job transition patterns in the current domestic labor market. For example, in a particular industry, workers with 3 to 6 years’ seniority may have a high turnover intention, the reemployment difficulty among middle aged workers, the regional wage gaps and other social issues. The results assist various types of job seekers obtain comprehensive information to find their own niche in the labor market. In the meantime, this study also provides the decision-making reference for government and enterprise. On the other hand, Human Resource Agency can base on the results to improve their services. Help job seekers to find the most favorable direction.

    目錄 i 表目錄 iii 圖目錄 v 符號定義 1 第一章 緒論 3 1.1 研究背景、動機與重要性 3 1.2 研究目的 5 1.3 論文結構 6 第二章 文獻回顧 8 2.1 人力資本(Human Capital) 8 2.2 就業、失業與待業期之相關研究 9 2.3 貝氏網路(Bayesian Network) 15 2.3.1 貝氏網路之理論基礎 15 2.3.2 貝氏網路之優點 17 2.3.3 貝氏網路之應用 18 第三章 研究架構 20 3.1 問題定義 21 3.2 資料準備 21 3.2.1 資料檢視 22 3.2.2 資料轉換 23 3.2.3 資料清理 25 3.2.4 重要變數篩選與假設建立 26 3.2.5 資料分割 28 3.3 模型建構 29 3.3.1 貝氏網路模型建構 29 3.3.2 模型效能檢驗 29 3.4 結果討論 30 第四章 實證研究 33 4.1 問題定義 33 4.2 資料準備 34 4.2.1資料檢視 34 4.2.2 資料轉換 43 4.2.3 資料清理 45 4.2.4 重要變數篩選與假設建立 47 4.2.5 資料分割 50 4.3 模型建構 51 4.3.1 貝氏網路模型建構 51 4.3.2 模型效能檢驗 52 4.4 結果討論 55 4.4.1 案例一:教育程度、科系類別與待業期之影響關係 56 4.4.2 案例二:應徵職務、新工作職務別與待業期之影響關係 59 4.4.3 案例三:社會新鮮人求職方向建議 64 4.4.4 案例四:轉職行為探討(以特定族群為例) 67 第五章 結論與未來研究 71 5.1 研究貢獻 71 5.2 未來研究方向 72 參考文獻 74 附錄 79

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