Title :
ODAM: An optimized distributed association rule mining algorithm
Author :
Ashrafi, Mafruz Zaman ; Taniar, David ; Smith, Kate
Author_Institution :
Monash Univ., Clayton, Vic., Australia
fDate :
6/26/1905 12:00:00 AM
Abstract :
Association rule mining is an active data mining research area. However, most ARM algorithms cater to a centralized environment. In contrast to previous ARM algorithms, we have developed a distributed algorithm, called optimized distributed association mining, for geographically distributed data sets. ODAM generates support counts of candidate itemsets quicker than the other DARM algorithms and reduces the size of average transactions, data sets, and message exchanges.
Keywords :
computational complexity; data mining; distributed algorithms; distributed databases; data mining; distributed algorithm; geographically distributed data sets; optimized distributed association mining; Algorithm design and analysis; Association rules; Costs; Data mining; Distributed algorithms; Distributed computing; Itemsets; Merging; Partitioning algorithms; Transaction databases;
Journal_Title :
Distributed Systems Online, IEEE
DOI :
10.1109/MDSO.2004.1285877