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» Mining Frequent Itemsets Using Re-Usable Data Structure
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SDM
2003
SIAM
134views Data Mining» more  SDM 2003»
13 years 9 months ago
Hierarchical Document Clustering using Frequent Itemsets
A major challenge in document clustering is the extremely high dimensionality. For example, the vocabulary for a document set can easily be thousands of words. On the other hand, ...
Benjamin C. M. Fung, Ke Wang, Martin Ester
VLDB
2007
ACM
204views Database» more  VLDB 2007»
14 years 1 months ago
Optimization of Frequent Itemset Mining on Multiple-Core Processor
Multi-core processors are proliferated across different domains in recent years. In this paper, we study the performance of frequent pattern mining on a modern multi-core machine....
Eric Li, Li Liu
KDD
2008
ACM
138views Data Mining» more  KDD 2008»
14 years 8 months ago
Quantitative evaluation of approximate frequent pattern mining algorithms
Traditional association mining algorithms use a strict definition of support that requires every item in a frequent itemset to occur in each supporting transaction. In real-life d...
Rohit Gupta, Gang Fang, Blayne Field, Michael Stei...
IDA
2007
Springer
13 years 7 months ago
Approximate mining of frequent patterns on streams
Abstract. This paper introduces a new algorithm for approximate mining of frequent patterns from streams of transactions using a limited amount of memory. The proposed algorithm co...
Claudio Silvestri, Salvatore Orlando
FIMI
2003
88views Data Mining» more  FIMI 2003»
13 years 9 months ago
A fast APRIORI implementation
The efficiency of frequent itemset mining algorithms is determined mainly by three factors: the way candidates are generated, the data structure that is used and the implementati...
Ferenc Bodon