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» Generalized Closed Itemsets for Association Rule Mining
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DEXA
2004
Springer
153views Database» more  DEXA 2004»
13 years 10 months ago
A New Approach of Eliminating Redundant Association Rules
Two important constraints of association rule mining algorithm are support and confidence. However, such constraints-based algorithms generally produce a large number of redundant ...
Mafruz Zaman Ashrafi, David Taniar, Kate A. Smith
DAWAK
2010
Springer
13 years 5 months ago
Mining Closed Itemsets in Data Stream Using Formal Concept Analysis
Mining of frequent closed itemsets has been shown to be more efficient than mining frequent itemsets for generating non-redundant association rules. The task is challenging in data...
Anamika Gupta, Vasudha Bhatnagar, Naveen Kumar
JCST
2008
119views more  JCST 2008»
13 years 4 months ago
Mining Frequent Generalized Itemsets and Generalized Association Rules Without Redundancy
This paper presents some new algorithms to efficiently mine max frequent generalized itemsets (g-itemsets) and essential generalized association rules (g-rules). These are compact ...
Daniel Kunkle, Donghui Zhang, Gene Cooperman
KDD
2000
ACM
118views Data Mining» more  KDD 2000»
13 years 8 months ago
Generating non-redundant association rules
The traditional association rule mining framework produces many redundant rules. The extent of redundancy is a lot larger than previously suspected. We present a new framework for...
Mohammed Javeed Zaki
CIKM
2009
Springer
13 years 9 months ago
A novel approach for privacy mining of generic basic association rules
Data mining can extract important knowledge from large data collections - but sometimes these collections are split among various parties. Privacy concerns may prevent the parties...
Moez Waddey, Pascal Poncelet, Sadok Ben Yahia