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IEEEHPCS
2010
13 years 5 months ago
Discovering closed frequent itemsets on multicore: Parallelizing computations and optimizing memory accesses
The problem of closed frequent itemset discovery is a fundamental problem of data mining, having applications in numerous domains. It is thus very important to have efficient par...
Benjamin Négrevergne, Alexandre Termier, Je...
FIMI
2003
104views Data Mining» more  FIMI 2003»
13 years 8 months ago
AIM: Another Itemset Miner
We present a new algorithm for mining frequent itemsets. Past studies have proposed various algorithms and techniques for improving the efficiency of the mining task. We integrate...
Amos Fiat, Sagi Shporer
PPOPP
2005
ACM
14 years 20 days ago
A sampling-based framework for parallel data mining
The goal of data mining algorithm is to discover useful information embedded in large databases. Frequent itemset mining and sequential pattern mining are two important data minin...
Shengnan Cong, Jiawei Han, Jay Hoeflinger, David A...
PODS
2009
ACM
134views Database» more  PODS 2009»
14 years 7 months ago
An efficient rigorous approach for identifying statistically significant frequent itemsets
As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is b...
Adam Kirsch, Michael Mitzenmacher, Andrea Pietraca...
IDEAS
2005
IEEE
99views Database» more  IDEAS 2005»
14 years 21 days ago
Distribution-Based Synthetic Database Generation Techniques for Itemset Mining
The resource requirements of frequent pattern mining algorithms depend mainly on the length distribution of the mined patterns in the database. Synthetic databases, which are used...
Ganesh Ramesh, Mohammed Javeed Zaki, William Mania...