政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/35211
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    政大機構典藏 > 商學院 > 資訊管理學系 > 學位論文 >  Item 140.119/35211


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    題名: 全球資訊網中使用者網頁-動作路徑的資料挖掘
    作者: 林青峰
    Lin , Qing-Fung
    貢獻者: 楊亨利
    Yang , Herng-Li
    林青峰
    Lin , Qing-Fung
    關鍵詞: 全球資訊網
    網站使用挖掘
    資料挖掘
    使用者行為
    網頁路徑
    動作路徑
    World-Wide-Web
    Web-Useage Mining
    Data-Mining
    User Behavior
    Page Path
    Action Path
    日期: 2003
    上傳時間: 2009-09-18 14:27:26 (UTC+8)
    摘要: 　　客戶在從事消費時，往往會有許多不一樣的行為產生。對組織而言，研究客戶的消費行為能夠協助組織更了解客戶的資訊，進而支援其經營活動。以往與客戶行為相關的資料挖掘研究，較著重於客戶的消費資料。而對於客戶在商店中做了那些動作，及其動作會導致發生的事件並沒有較全盤及深入的討論。對實體業者而言，要實際的去記錄使用者在商店內的行為，是不太可行的；但相對的說，隨著網際網路與資料收集技術的發展，網站經營者應用log留存技術，將比傳統業者更容易且完整的收集到消費者行為記錄。本研究試圖在全球資訊網的環境中建立一個能夠同時分析使用者的瀏覽網頁路徑及其動作過程的演算法；並且配合該演算法建置一個雛形系統，以驗証其效能，最後並評估其日後實務操作的可行性。
    Different kind of customer purchases with different behavior. Studying the customer’s purchase behavior can help organizations understand their client intentions to support their business activities. In the past, customer behavior data mining emphasized on their purchase items, i.e., what they buy. There was few studies discussing what path they took and what actions they made in an e-store. It is impossible for a physical store to record its customers’ all actions and passing paths. However, a website store can easily collect such data in an Internet log. This study proposes a data mining algorithm that can analyze both customers’ browsing pages and their actions path. The algorithm’s efficiency and feasibility were examined in our prototype. This study may contribute to help the website mangers to restructure their website layouts or advertisement position to catch the customer’s eyes.
    參考文獻: 1、陳仕昇、許秉瑜與陳彥良, "以可重複序列挖掘網路瀏覽規則之研究," 資訊管理學報,第六卷,第二期, 2000
    2、Agrawal, R., Ghosh, S., Imielinski, T., Iyer B. and Swami, A., "An Interval Classifier for Database Mining Applications," Proceeding of th 18th VLDB Confrence, Vancouver, Canada, August, 1992, pp.560-573.
    3、Agrawal, R., Imielinski, T. and Swami, A., "Database Mining: A Performance Perspective," IEEE Transactions on Knowledge, Vol.5, No.6, December, 1993, pp.914-925.
    4、Agrawal, R. and Srikant, R., "Fast Algorithms for Mining Association Rules," Proc. of the 20th Int`l Conference on Very Large Databases, Santiago, Chile, Sep. 1994.
    5、Agrawal, R. and Srikant, R., "Mining Sequential Patterns," Proc. of the Int`l Conference on Data Engineering (ICDE), Taipei, Taiwan, March 1995.
    6、Chen, M-S., Han, J. and Yu, P. S., "Data Mining：An Overview from a Database Perspective," IEEE Transactions on Knowledge and Data Engineering, Vol. 8, No. 6, 1996, pp. 866-883.
    7、Chen, M-S., Park J-S. and Yu, P. S., "Efficient Data Mining for Path Traversal Patterns," IEEE Trans. on Knowledge and Data Engineering, Vol. 10, No. 2, April 1998, pp. 209-221.
    8、Cooley, R., Mobasher, B. and Srivastava, J., "Web Mining: Information and Pattern Discovery on the World Wide Web," in Proceedings of the 9th IEEE International Conference on Tools with Artificial Intelligence (ICTAI`97), Nov. 1997.
    9、Cooley, R., Mobasher, B. and Srivastava, J., "Grouping Web Page References into Transactions for Mining World Wide Web Browsing Patterns," Proceedings of the 1997 IEEE Knowledge and Data Engineering Exchange Workshop (KDEX-97), Nov. 1997.
    10、Cooley, R., Mobasher, B. and Srivastava, J., "Data Preparation for Mining World Wide Web Browsing Patterns," Journal of Knowledge and Information Systems, Vol. 1, No. 1, 1999.
    11、Frawley, W.J., Paitetsky-Shapiro, G. and Matheus C. J., "Knowledge Discovery in Databases: An Overview," Knowledge Discovery in Databases, California, Edited by Paitetsky-Shapiro, G.. and Frawley,W.J., AAAI/MIT Express, 1991, pp.1-30.
    12、Han, J., Cai, Y. and Cercone, N., "Attribute-Oriented Induction in Relational Databases," in G. Piatetsky-Shapiro and W. J. Frawley(eds.), Knowledge Discovery in Databases, AAAI/MIT Press, 1991, pp. 213-228.
    13、Han, J., Cai, Y. and Cercone, N., "Knowledge Discovery in Databases : An Attribute-Oriented Approach," Proceeding of the 18th VLDB Conference, Canada, August, 1992, pp. 547-549.
    14、Han, J. and Fu, Y., "Discovery of Multiple-Level Association Rules from Large Databases," Oric. of 1995 Int`1 Conf. on Very Large Data Bases (VLDB`95), Zuich, Switzerland, September 1995, pp. 420-431.
    15、Han, J., Koperski, K. and Adhikary, J., "Spatial Data Mining: and Challenges," 1996 SIGMOD`96 Workshop. on Resarch Issues on Data Mining and Knowledge Discovery(DMKD`96), Montreal, Canada, June 1996.
    16、Han, J., Yang, Q. and Kim, E., "Plan Mining by Divide-and-Conquer," Proc. 1999 SIGMOD`99 Workshop on Research Issues on Data Mining and Knowledge Discovery (DMKD`99) , Philadelphia, PA, May 1999, pp. 8:1-8:6
    17、Hsieh, C. C. and Chang, C.T., "An enhanced transaction identification module on web usage mining", Asia Pacific Management, pp.241~252, 2001.
    18、Lewinson., "Data Mining:Intelligent Technology Gets Down To Business," PC AI, Vol7, Vol.6 November/December 1993, pp.16-23.
    19、Pasquier, N., Bastide, Y., Taouil R. and Lakhal, L., "Efficient Mining Of Association Rules Using Closed Itemset Lattices," Information Systems, Vol. 24, No. 1, March 1999, pp. 25-46.
    20、Quinlan, J. R., "Induction of Decion Trees," Machine Learning, Vol1, No.1, 1986, pp.81-106.
    21、Ramkumar, G.D. and Swami, A., "Clustering data without distance functions", IEEE Technical committee on Data Engineering, Data(base) Engineering Bulletin, pp.9~14, 1998.
    22、Savasere, A., Omiecinski, E. and Navathe, S., "An Efficient Algorithm for Mining Association Rules in Large Databases," Proc. Int`l Conf. Very Large Data Bases, Zurich, Switzerland, Sep. 1995, pp. 432-444.
    23、Toivonen, H., "Sampling Large Databases For Association Rules," The 22th International Conference on Very Large Databases (VLDB`96), Mumbay, India, Sep. 1996, pp. 134-145.
    24、Yu C-C., and Chen, Y-L., "Mining sequential patterns from multi-dimensional sequence data," revised in IEEE Trans. On Knowledge and Data engineering. (SCI) ,2002
    25、Yun, C.H. and Chen, M.S., "Using pattern-join and purchase-combination for mining transaction patterns in an electronic commerce environment", The 24th Annual International Conference On Computer Software and Applications, Taipei, Taiwan, pp.99~104, 25-27 Oct 2000.
    26、 Zhang, W., Xu, B., Song, W., Yung, H. and Liu, K., "Data mining algorithms for web pre-fetching", Proceeding of the First International Conference On Web Information Systems Engineering, Hong Kong, China, Vol.2 pp.34-38, 19-21 June 2000.
    描述: 碩士
    國立政治大學
    資訊管理研究所
    91356030
    92
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0091356030
    資料類型: thesis
    顯示於類別:[資訊管理學系] 學位論文

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