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» Association rules mining using heavy itemsets
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KAIS
2006
164views more  KAIS 2006»
14 years 9 months ago
On efficiently summarizing categorical databases
Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its a...
Jianyong Wang, George Karypis
ISCC
2002
IEEE
147views Communications» more  ISCC 2002»
15 years 2 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
2004
ACM
148views Data Mining» more  KDD 2004»
15 years 10 months ago
Interestingness of frequent itemsets using Bayesian networks as background knowledge
The paper presents a method for pruning frequent itemsets based on background knowledge represented by a Bayesian network. The interestingness of an itemset is defined as the abso...
Szymon Jaroszewicz, Dan A. Simovici
85
Voted
KDD
2003
ACM
175views Data Mining» more  KDD 2003»
15 years 10 months ago
Weighted Association Rule Mining using weighted support and significance framework
We address the issues of discovering significant binary relationships in transaction datasets in a weighted setting. Traditional model of association rule mining is adapted to han...
Feng Tao, Fionn Murtagh, Mohsen Farid
81
Voted
EMS
2008
IEEE
15 years 4 months ago
A Weighted Utility Framework for Mining Association Rules
Association rule mining (ARM) identifies frequent itemsets from databases and generates association rules by assuming that all items have the same significance and frequency of oc...
M. Sulaiman Khan, Maybin K. Muyeba, Frans Coenen