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Fourth International Conference on Software Engineering Research, Management and Applications (SERA'06)
A Parallel Apriori Algorithm for Frequent Itemsets Mining
Seattle, Washington
August 09-August 11
ISBN: 0-7695-2656-X
ASCII Text
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Yanbin Ye, Chia-Chu Chiang, "A Parallel Apriori Algorithm for Frequent Itemsets Mining," Software Engineering Research, Management and Applications, ACIS International Conference on, pp. 87-94, Fourth International Conference on Software Engineering Research, Management and Applications (SERA'06), 2006.
 
 
BibTex
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@article{ 10.1109/SERA.2006.6,
author = {Yanbin Ye and Chia-Chu Chiang},
title = {A Parallel Apriori Algorithm for Frequent Itemsets Mining},
journal ={Software Engineering Research, Management and Applications, ACIS International Conference on},
volume = {0},
year = {2006},
isbn = {0-7695-2656-X},
pages = {87-94},
doi = {http://doi.ieeecomputersociety.org/10.1109/SERA.2006.6},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Software Engineering Research, Management and Applications, ACIS International Conference on
TI - A Parallel Apriori Algorithm for Frequent Itemsets Mining
SN - 0-7695-2656-X
SP87
EP94
A1 - Yanbin Ye,
A1 - Chia-Chu Chiang,
PY - 2006
KW - Apriori
KW - Association Rules
KW - Data Mining
KW - Frequent Itemsets Mining (FIM)
KW - Parallel Computing
VL - 0
JA - Software Engineering Research, Management and Applications, ACIS International Conference on
ER -
 
Yanbin Ye, Acxiom Corporation, Little Rock, Arkansas
Chia-Chu Chiang, University of Arkansas at Little Rock
Finding frequent itemsets is one of the most investigated fields of data mining. The Apriori algorithm is the most established algorithm for frequent itemsets mining (FIM). Several implementations of the Apriori algorithm have been reported and evaluated. One of the implementations optimizing the data structure with a trie by Bodon catches our attention. The results of the Bodon?s implementation for finding frequent itemsets appear to be faster than the ones by Borgelt and Goethals. In this paper, we revised Bodon?s implementation into a parallel one where input transactions are read by a parallel computer. The effect a parallel computer on this modified implementation is presented.
Index Terms:
Apriori, Association Rules, Data Mining, Frequent Itemsets Mining (FIM), Parallel Computing
Citation:
Yanbin Ye, Chia-Chu Chiang, "A Parallel Apriori Algorithm for Frequent Itemsets Mining," sera, pp.87-94, Fourth International Conference on Software Engineering Research, Management and Applications (SERA'06), 2006
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