A Foundational Approach to Mining Itemset Utilities from Databases.

作者: Cory J. Butz , Howard J. Hamilton , Hong Yao

DOI:

关键词:

摘要: Most approaches to mining association rules implicitly consider the utilities of itemsets be equal. We assume that may differ, and identify high utility based on information in transaction database external about utilities. Our theoretical analysis resulting problem lays foundation for future algorithms.

参考文章(10)
Heikki Mannila, A. Inkeri Verkamo, Hannu Toivonen, Efficient algorithms for discovering association rules knowledge discovery and data mining. pp. 181- 192 ,(1994)
Ke Wang, Senqiang Zhou, Jiawei Han, Profit Mining: From Patterns to Actions extending database technology. pp. 70- 87 ,(2002) , 10.1007/3-540-45876-X_7
Songfeng Lu, Heping Hu, Fan Li, Mining weighted association rules intelligent data analysis. ,vol. 5, pp. 211- 225 ,(2001) , 10.3233/IDA-2001-5303
Gregory Piatetsky-Shapiro, Discovery, Analysis, and Presentation of Strong Rules Knowledge Discovery in Databases. pp. 229- 238 ,(1991)
Brock Barber, Howard J. Hamilton, Extracting Share Frequent Itemsets with Infrequent Subsets Data Mining and Knowledge Discovery. ,vol. 7, pp. 153- 185 ,(2003) , 10.1023/A:1022419032620
Willi Klösgen, Explora: a multipattern and multistrategy discovery assistant knowledge discovery and data mining. pp. 249- 271 ,(1996)
Heikki Mannila, Hannu Toivonen, Levelwise Search and Borders of Theories in KnowledgeDiscovery Data Mining and Knowledge Discovery. ,vol. 1, pp. 241- 258 ,(1997) , 10.1023/A:1009796218281
U.M. Feyyad, Data mining and knowledge discovery: making sense out of data IEEE Intelligent Systems. ,vol. 11, pp. 20- 25 ,(1996) , 10.1109/64.539013
Raymond Chan, Qiang Yang, Yi-Dong Shen, Mining high utility itemsets international conference on data mining. pp. 19- 26 ,(2003) , 10.1109/ICDM.2003.1250893
Rakesh Agrawal, Tomasz Imieliński, Arun Swami, Mining association rules between sets of items in large databases Proceedings of the 1993 ACM SIGMOD international conference on Management of data - SIGMOD '93. ,vol. 22, pp. 207- 216 ,(1993) , 10.1145/170035.170072