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KDD
2006
ACM
198views Data Mining» more  KDD 2006»
16 years 6 months ago
CFI-Stream: mining closed frequent itemsets in data streams
Mining frequent closed itemsets provides complete and condensed information for non-redundant association rules generation. Extensive studies have been done on mining frequent clo...
Nan Jiang, Le Gruenwald
KDD
2005
ACM
92views Data Mining» more  KDD 2005»
16 years 6 months ago
Summarizing itemset patterns: a profile-based approach
Frequent-pattern mining has been studied extensively on scalable methods for mining various kinds of patterns including itemsets, sequences, and graphs. However, the bottleneck of...
Xifeng Yan, Hong Cheng, Jiawei Han, Dong Xin
KDD
2003
ACM
175views Data Mining» more  KDD 2003»
16 years 6 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
KDD
2003
ACM
156views Data Mining» more  KDD 2003»
16 years 6 months ago
Fast vertical mining using diffsets
A number of vertical mining algorithms have been proposed recently for association mining, which have shown to be very effective and usually outperform horizontal approaches. The ...
Mohammed Javeed Zaki, Karam Gouda
KDD
2002
ACM
171views Data Mining» more  KDD 2002»
16 years 6 months ago
Mining complex models from arbitrarily large databases in constant time
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
Geoff Hulten, Pedro Domingos