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HIPC
2003
Springer
13 years 10 months ago
Parallel and Distributed Frequent Itemset Mining on Dynamic Datasets
Traditional methods for data mining typically make the assumption that data is centralized and static. This assumption is no longer tenable. Such methods waste computational and I/...
Adriano Veloso, Matthew Eric Otey, Srinivasan Part...
ICDM
2003
IEEE
140views Data Mining» more  ICDM 2003»
13 years 10 months ago
Mining Frequent Itemsets in Distributed and Dynamic Databases
Traditional methods for frequent itemset mining typically assume that data is centralized and static. Such methods impose excessive communication overhead when data is distributed...
Matthew Eric Otey, Chao Wang, Srinivasan Parthasar...
ICDM
2005
IEEE
125views Data Mining» more  ICDM 2005»
13 years 11 months ago
A Thorough Experimental Study of Datasets for Frequent Itemsets
The discovery of frequent patterns is a famous problem in data mining. While plenty of algorithms have been proposed during the last decade, only a few contributions have tried to...
Frédéric Flouvat, Fabien De Marchi, ...
JIIS
2010
106views more  JIIS 2010»
13 years 3 days ago
A new classification of datasets for frequent itemsets
The discovery of frequent patterns is a famous problem in data mining. While plenty of algorithms have been proposed during the last decade, only a few contributions have tried to ...
Frédéric Flouvat, Fabien De Marchi, ...