輔仁大學
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記錄編號3328
狀態NC088FJU00396002
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學校名稱輔仁大學
系所名稱資訊管理學系
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學號487746017
研究生(中)張瑋倫
研究生(英)Wei Lun Chang
論文名稱(中)應用資料挖掘學習方法探討顧客關係管理問題
論文名稱(英)A Synthesized Learning Approach for Web-Based CRM
其他題名
指導教授(中)苑守慈
指導教授(英)Soe-Tsyr Yuan
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國圖全文開放日期.2005.01.01
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學位類別碩士
畢業學年度88
出版年
語文別中文
關鍵字(中)資料挖掘 顧客關係管理 Self-Organization Maps
關鍵字(英)Data Mining Customer Relationship Management Self-Organization Maps
摘要(中)近年來由於顧客關係管理(Customer Relationship Management)議題的快速崛起,顧客也成為在建立企業時的一項重要指標。因此對於如何保留顧客與創造顧客利潤也成為當前最重要的課題,但目前對於資料的分群與分析仍存在著瓶頸。本研究從資料挖掘的相關應用技術來探討,嘗試解決並突破過去所存在的瓶頸,其中包括了Self-Organization Maps (S.O.M.)、階層式自動標記分群法(Automatic-Labeling S.O.M.)、分類決策樹(Decision Tree)與交叉分析(Cross-Analysis),並結合四項技術形成新的整合研究方法,全自動地將所有資料分群並標記出重要的特徵屬性,然後藉由分類區隔出正常群集、偏差群集與可能偏差群集三種類別,最後運用交叉分析的方式找出顧客叛離的原因,提供給相關的管理決策者以作為解決目前顧客關係管理所遭遇困難之參考。
摘要(英)The issue of customer relationship management emerges rapidly. Customers have become one of the important considerations to companies being built as well. Accordingly, customer retention is a very important topic. In this research, we present a synthesized learning approach for better understanding customers and the provision of clues for improving customer relationship based on different sources of web customer data. The approach is a combination of Self-Organization Maps, Hierarchical Automatic Labeling SOM, and Decision Trees. The objective of the approach is to segment data source into clusters, automatically label the features of the clusters, discover the characteristics of normal, defected and possibly defected clusters of customers, and provide clues for gaining customer retention.
論文目次論 文 摘 要ABSTRACT 表 次 圖 次 第壹章 緒論 第貳章 文獻探討 第參章 研究方法 第肆章 實驗流程與變數說明 第伍章 實驗評估(一) 第陸章 實驗評估(二) 第柒章 實驗評估(三) 第捌章 結論與未來展望 參考文獻 附錄A
參考文獻[1] Andreas Arning, R. Agrawal, P. Raghavan, "A Linear Method for Deviation Detection in Large Databases", Proc. of the 2nd Int''''l Conference on Knowledge Discovery in Databases and Data Mining, Portland, Oregon, August, 1996 [2] Agrawal, A. Arning, T. Bollinger, M. Mehta, J. Shafer, R. Srikant: "The Quest Data Mining System", Proc. of the 2nd Int''''l Conference on Knowledge Discovery in Databases and Data Mining, Portland, Oregon, August, 1996. [3] Barbro Back, Kaisa Sere, Hannu Vanharanta, “Analyzing Financial Performance with Self-Organization Maps”, In Proc. of Workshop on the Self-Organizing Map (WSOM''''97), Espoo, Finland, June 1997. [4] Bart De Ketelaere, Dimitrios Moshou, Peter Coucke, Josse De Baerdemaeker, “A hierarchical Self-Organization Map for classification problems”, Proceeding of the Workshop on Self-Organizing Maps (WSOM97), Helsinki, Finland, 1997. [5] Juha Vesanto, “Data Mining Techniques Based on the Self-Organization Map”, Thesis for the degree of Master of Science in Engineering, 1997 [6] Kimmo Kiviluoto, Pentti Bergius, “Analyzing Financial Statements with the Self-Organizing Map”, Proceeding of the Workshop on Self-Organizing Maps (WSOM97), Helsinki, Finland, 1997. [7] K. F. Goser, “Self organising maps for intelligent process control”, Proceeding of the Workshop on Self-Organizing Maps (WSOM97), Helsinki, Finland, 1997. [8] Kevin J. Cherkauer, Jude W. Shavlik, “Growing Simpler Decision Tree to Facilitate Knowledge Discovery”, Appears in Proceeding, Seond International Conference on Knowledge Discovery and Data Mining, Portland, OR: AAAI, 1996 [9] R. Agrawal, R. Srikant: ''''Mining Sequential Patterns'''''''', Proceeding of the Int''''l Conference on Data Engineering (ICDE), Taipei, Taiwan, March 1995 [10] Rauber Andreas, “Cluster Visualization in Unsupervised Neural Networks” Diplomarbeit (Master Thesis, in English), Technische Universit Wien, Austria, 1996 [11] Rauber Andreas, “Alternative Ways for Cluster Visualization in Self-Organizing Maps”, Proceeding of the Workshop on Self-Organizing Maps (WSOM97), Helsinki, Finland, 1997. [12] Rauber Andreas , “LabelSOM: On the Labeling of Self-Organizing Maps” Proceedings of the International Joint Conference on Neural Networks (IJCNN''''99), Washington, DC, July 10 - 16, 1999. [13] Rauber Andreas , “Automatic Labeling of Self-Organizing Maps: Making a Treasure-Map Reveal its Secrets” Proceedings of the 3. Pacific-Asia Conference on Knowledge Discovery and Data Mining} (PAKDD''''99), Bejing, China, April 26--28, 1999. LNCS / Lecture Notes in Artificial Intelligence, LNAI 1574, pp. 228 - 237, Springer Verlag [14] Robert Leivian, William Peterson, Mike Gardner, “CorDex:a knowledge Discovery Tool”, Proceeding of the Workshop on Self-Organizing Maps (WSOM97), Helsinki, Finland, 1997. [15] Teuvo Kohonen, Panu Somervuo ,“Self-Organization Maps of Symbol Strings with Application to Speech Recognition”, Proceeding of the Workshop on Self-Organizing Maps (WSOM97), Helsinki, Finland, 1997. [16] Timo Honkela, Samuel Kaski, Krista Lagus, Teuvo Kohonen, “WEBSOM-Self Organization Maps of Document Collections”, Proceeding of the Workshop on Self-Organizing Maps (WSOM97), Helsinki, Finland, 1997. [17] Timo Honkela, “Comparisons of Self-Organization Word Category Maps”, Proceeding of the Workshop on Self Organizing Maps (WSOM97), Helsinki, Finland, 1997. [18] Timo Honkela, “Comparisons of Self-Organized Word Category Maps”, Proceeding of the Workshop on Self Organizing Maps (WSOM97), Helsinki, Finland, 1997. [19] Xiaowei Xu, Martin Ester, Hans-Peter Kriegel, Lorg Sander, “A Distribution-Based Clustering Algorithm for Mining in Large Spatial Database” [20] Kaski, Samuel, Method For Exploratory Data Analysis, Samuel Kaski, Teuvo Kohonen, “Exploratory data analysis by the self-organizing map: Structures of welfare and poverty in the world” In Apostolos-Paul N. Refenes, Yaser Abu-Mostafa, John Moody, and Andreas Weigend, editors, Neural Networks in Financial Engineering, pages 498--507. World Scientific, Singapore, 1996 [21] “Building Classification Models: ID3 and C4.5”, UGAI97 Workshop, http://yoda.cis.temple.edu:8080/UGAIWWW/lectures/C45/ [22] Customer Retention Practices:Solutions http://retention.harrisblackintl.com/solutions/ [23] Customer Retention Associates http://www.customerloyalty.org/ [24] Stuart Russell, Peter Norvig, “Artificial Intelligence A Modern Approach”, Prentice Hall, p531-p544, 1997 [25] Customer Relationship Management http://www.dci.com/crm [26] Chris Saunders, Michael Meltzer, “Driving Customer Retention, Development And Acquisition For Profit In The Insurance Business”, Mitchell Madison Group, 1998 http://www.crm-forum.com/crm_forum_white_papers/dcr/sld01.htm [27] Simon Caufield, “Does Customer Relationship Management Really Pay”, Mitchell Madison Group,1998 http://www.crm-forum.com/crm_forum_white_papers/dpay/sld01.htm [28] NCR:CRM:Issues-Customer Profitability, 1998 http://www3.ncr.com/product/crm/profitability.html [29] Customer Retention Practices:Newsletter http://retention.harrisblackintl.com/mar98newsletter/page1.html
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