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SBACPAD
2003
IEEE
180views Hardware» more  SBACPAD 2003»
15 years 9 months ago
New Parallel Algorithms for Frequent Itemset Mining in Very Large Databases
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
ISCC
2002
IEEE
147views Communications» more  ISCC 2002»
15 years 9 months ago
A new method for finding generalized frequent itemsets in generalized association rule mining
Generalized association rule mining is an extension of traditional association rule mining to discover more informative rules, given a taxonomy. In this paper, we describe a forma...
Kritsada Sriphaew, Thanaruk Theeramunkong
KDD
1999
ACM
108views Data Mining» more  KDD 1999»
15 years 8 months ago
Mining the Most Interesting Rules
Several algorithms have been proposed for finding the “best,” “optimal,” or “most interesting” rule(s) in a database according to a variety of metrics including confid...
Roberto J. Bayardo Jr., Rakesh Agrawal
PKDD
1998
Springer
113views Data Mining» more  PKDD 1998»
15 years 8 months ago
Text Mining at the Term Level
Knowledge Discovery in Databases (KDD) focuses on the computerized exploration of large amounts of data and on the discovery of interesting patterns within them. While most work on...
Ronen Feldman, Moshe Fresko, Yakkov Kinar, Yehuda ...
KDD
1994
ACM
82views Data Mining» more  KDD 1994»
15 years 8 months ago
Architectural Support for Data Mining
Oneof the mainobstacles in applying data mining techniques to large, real-world databasesis the lack of efficient data management.In this paper, wepresent the design and implement...
Marcel Holsheimer, Martin L. Kersten