跳到主要內容

臺灣博碩士論文加值系統

(3.237.38.244) 您好!臺灣時間:2021/07/26 08:42
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

我願授權國圖
: 
twitterline
研究生:姜芝怡
研究生(外文):Jiang Jhih Yi
論文名稱:漸進式的資料分類方法
論文名稱(外文):An Incremental Data Classification Technique
指導教授:楊熙年
學位類別:碩士
校院名稱:國立清華大學
系所名稱:資訊系統與應用研究所
學門:電算機學門
學類:系統設計學類
論文種類:學術論文
論文出版年:2004
畢業學年度:92
語文別:中文
論文頁數:45
中文關鍵詞:資料探勘漸進式資料探勘分類
外文關鍵詞:data miningincremental dataminingclassification
相關次數:
  • 被引用被引用:0
  • 點閱點閱:198
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
在這個競爭激烈的時代,企業為了掌握競爭優勢,時時都得注意最新資訊,這些資訊也許在報章媒體上、也許在市場中、也許就存在企業自己的資料庫中。如何將這些隱藏的資訊挖掘出來進而轉換成有用的競爭策略,是資料探勘這個領域的主題。
顧客關係管理(CRM)系統是近來最常被談論的資料探勘應用之一,本研究分析一3C零售業者的顧客管理系統中的一個子系統----聯名卡推薦系統,並提出一個漸進式資料探勘分類系統的架構,應用此系統架構到此聯名卡推薦系統上,與原先系統所使用的方法比較,研究此系統架構應用在相關問題時是否能得到較佳的效果。經過本研究實驗發現這樣的架構確能達到預期加速的目的,而且所建造出來的分類模型和原系統兩者間的準確率差異在可接受的範圍內。
In this high competition age, a company has to continuously keep an eye on the latest information in order to hold the upper hand of the industry. The company may have to find the information on the mass media or on the market. They can even find useful information in their own database. The task of mining unseen information and then transforming it into the competitive strategy is essential in the data mining area.
Customer relationship management system is one of the most popular data mining applications. In this study, we analyze a subsystem of a 3C retailer’s CRM System ---an eCard recommendation system. At the same time, we propose an architecture for incremental data classification. We then apply this technique to the eCard recommendation system to see whether it would perform better than the existing ones. Experimental results show that the classifier built according to the proposed method has acceptable error rate compared with the existing classifiers. Moreover, it can generate a set of rules which provide some high level semantic description about the data.
[1] Jiawei Han and Micheline Kamber, “Data Mining: Concepts and techniques”, 2001

[2]Michael J.A. Berry and Gordan S. Linoff, ”Data Mining Techniques: for marketing, sales, and customer support”,1997

[3]Catherine Bounsaythip and Esa Rinta-Runsala, “Overview of Data Mining for Customer Behavior Modeling”, VTT Information Technology, 2001

[4] Michael Goebel, Le Gruenwald, “A survey of data mining and knowledge discovery software tools”, ACM SIGKDD Explorations Newsletter Vol. 1 , Issue 1, P. 20 – 33, 1999

[5]TJEN-SIEN LIM ,WEI-YIN LOH and YU-SHAN SHIH, “A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-three Old and New Classification Algorithms”, Machine Learning, Vol. 40 , Issue 3 p. 203 - 228,,2000

[6]Venkatesh Ganti, Johannes Gehrke and Raghu Ramakrishnan, “Mining Data Streams under Block Evolution”, ACM SIGKDD
Explorations Newsletter archive Vol. 3 , Issue 2, 2002

[7] Venkatesh Ganti, Johannes Gehrke and Raghu Ramakrishnan, “A Framework for Measuring Changes in Data Characteristics”, In Proceedings of the Eighteenth ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems (PODS 1999). Philadelphia, Pennsylvania, 1999

[8]Qingguo Zheng, Ke Xu and Shilong Ma, “When to Update the Sequential Patterns of Stream Data?”, Proc. 7th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Korea, LNAI 2637, p. 545-550, 2003

[9] David W. Cheung, Jiawei Han, Vincent T, Ng and C.Y. Wong, “Maintenance of Discovered Association Rules in Large Databases: An Incremental Updating Technique”, ICDE, Proceedings of the Twelfth International Conference on Data Engineering, P. 106 – 114 , 1996

[10]David W. Cheung, S. D. Lee, and Benjamin Kao, “Maintenance of Discovered Association Rules in Large Databases: An Incremental Updating Technique.”, In Proceedings of the Fifth International
Conference on Database Systems for Advanced Applications, Melbourne, Australia, 1-4 April 1997

[11]S.D. Lee and David W. Cheung, “Maintenance of Discovered Association Rules: When to Update?”, Proc. 1997 ACM-SIGMOD Workshop on Data Mining and Knowledge Discovery (DMKD'97) in cooperation with ACM-SIGMOD'97,Tucson, Arizona, May 11, 1997

[12]Bing Liu, Wynne Hsu Yiming Ma, “Integrating Classification and Association Rule Mining”, Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98, full paper), New York, USA, 1998

[13]Bing Liu, Yiming Ma and Ching-Kian Wong, “Classification Using Association Rules: Weaknesses and Enhancements”, To appear in Vipin Kumar, et al, (eds), Data mining for scientific applications, 2001

[14]James Dougherty, Ron Kohavi and Mehran Sahami, “Supervised and Unsupervised Discretization of Continuous Features”, ML-95

[15]Rakesh Agrawa and Ramakrishnan Srikant, “Mining Sequential Patterns”, Proceedings of the Eleventh International Conference on Data Engineering, P. 3 – 14, 1995

[16]Johannes Gehrke, Venkatesh Ganti, Raghu Ramakrishnan and Wei-Yin Loh, “BOAT--- Optimistic Decision Tree Construction”, In Proceedings of the ACM SIGMOD Conference on Management of Data (SIGMOD
1999), Philadelphia, Pennsylvania, 1999

[17]Michael J. A. Berry and Gordon S. Linoff, “Mastering Data Mining: The Art and Science of Customer Relationship Management”, 2000

[18]楊昌憲, “資料庫行銷之新產品推薦系統, 國立台灣大學國際企業學研究所碩士學位論文, 2002
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top