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Title: | 以資料採礦方法探討國內數位落差之現象 Effect of Digital Divide in Taiwan: Data Mining Applications |
Authors: | 林建宇 Lin,chien yu |
Contributors: | 鄭宇庭 林建宇 Lin,chien yu |
Keywords: | 數位落差 資訊富人 資訊窮人 資料採礦 分類迴歸樹 C5.0決策樹 C&RT分類樹 CHAID分類樹 Digital Divide Information-rich Information-poor Data Mining Decision Tree C5.0 C&RT CHAID |
Date: | 2009 |
Issue Date: | 2010-12-08 01:51:57 (UTC+8) |
Abstract: | 全球化時代與資訊化社會的來臨,電腦與網際網路成為生活中不可或缺的要素,儘管至2008年為止,我國有將近七成的民眾透過網路科技享受到更多的便利性,但社會上仍存在著數位落差(digital divide)的問題,數位落差除了使得資訊窮人(information-poor)不易取得資訊,亦將對其經濟、人權等各方面造成影響。故研究目的在利用資料採礦的應用,配合SPSS Clementine 12.0的軟體,探討數位落差的現象,並嘗試找出形成數位落差的影響原因。
本研究主要投入人口統計變數以及生活型態變數,並藉由C5.0決策樹、C&RT分類樹,以及CHAID分類樹建立模型,透過這三個分類迴歸樹的模型,發現到「年齡」、「教育程度」、「地理區域」、「個人資產狀況」、「經濟主要來源:子女」、「個人每月可支配所得」以及「收入來源:薪資」共七項變數同時對民眾是否成為數位落差中的資訊富人(information-rich)有著較重要的影響性,因此,研究最後依據此七項進行政策建議,以提供相關單位之參考。 In this globalized and informational society, computers and internet networks are essential elements in our daily lives. Until the year 2008, almost 70% of population in Taiwan has enjoyed greater conveniences through networking technologies. However, the issue of “digital divide” remains, where information-poor cannot obtain information easily, and the issue affects the society in terms of economies and human rights. Consequently, the purpose of this research is aimed to find the reasons behind “digital divide” using data-mining techniques with SPSS Clementine 12.0 statistical software.
The research will input demographic variables and life-style variables. Using C5.0 decision tree, C&RT tree, and CHAID methodologies to build model, and subsequently discovers that whether the 7 variables - “age”, “level of education”, “location”, “personal asset status”, “main source of income: children”, “monthly personal disposal income” and “source of income: salary” will have significant impacts on information-rich population within “digital divide”. Therefore, the research recommendations will be provided according to the results from these 7 variables. |
Reference: | 王石番,2000,《網路使用者人口結構及使用動機調查分析》,行政院研究發展考核委員會委託研究報告。台北:行政院研究發展考核委員會。 李孟壕、曾淑芬,2005,〈數位落差再定義與衡量指標之研究〉,《資訊社會研究》9,頁89-124。 香港管理專業發展中心編,2001,《市場學概論》,香港:香港中文大學出版社。 曾淑芬、吳齊殷,2002,《台灣地區數位落差問題之研究》,行政院研究發展考核委員會委託研究報告。台北:行政院研究發展考核委員會。 葉俊榮,2006,〈台灣數位落差的現狀與政策〉,《研考雙月刊》,30(1),頁3-16。 潘金谷、曾淑芬、林玉凡,2009,〈數位吉尼係數應用之擴充:我國數位落差現況〉,《資訊社會研究》,16,頁1-32。 戴肇洋、林耀欽,2004,《規劃數位落差之對策研究計畫》,行政院研究發展考核委員會委託研究報告。台北:行政院研究發展考核委員會。 謝邦昌、鄭宇庭、蘇志雄,2009,《Data Mining 概述---以Clementine 12.0為例》,台北:中華資料採礦協會。 Breiman, L., J. H. Friedman, R. A. Olshen, and C. J. Stone, (1984). Classification and Regression Trees, Belmont, CA: Wadsworth International Group. Loh, W., and Y. Shih (1997), “Split Selection Methods for Classification Trees,” Statistica Sinica, Vol. 7, pp. 815-840. OECD (2001), “Understanding the Digital Divide”, Organization for Economic Co-operation and Development: Paris。Retrieved April 20, 2010, from the World Wide Web: http://www.oecd.org/dataoecd/38/57/1888451.pdf Perreault, W. J. and H. J. Barksdale. (1980). A Model-Free Approach for Analysis of Complex Contingency Data in Survey Research. Journal of Marketing Research, 503-515. Plummer, J. T. (1974). The Concept and Application of Life-Style Segmentation. Journal of Marketing, Vol.38, Jan, P34. Quinlan, J. R. (1979), “Discovering rules by induction from large collections of examples”, D. Michie ed., Expert Systems in the Microelectronic Age, Edinburgh University Press, Edinburgh, pp.168-201, Strover, S. (1999), Rural Internet Connectivity, Columbia, MO: Rural Policy Research Institute, pp.1-25. |
Description: | 碩士 國立政治大學 企業管理研究所 96355064 98 |
Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0096355064 |
Data Type: | thesis |
Appears in Collections: | [企業管理學系] 學位論文
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