Computing frequent itemsets in parallel using partial support trees

Authors:
Dora Souliou;Aris Pagourtzis;Nikolaos Drosinos
Affiliations:
School of Electrical and Computer Engineering, National Technical University of Athens, Zografou, Greece;School of Electrical and Computer Engineering, National Technical University of Athens, Zografou, Greece;School of Electrical and Computer Engineering, National Technical University of Athens, Zografou, Greece
Venue:
PVM/MPI'05 Proceedings of the 12th European PVM/MPI users' group conference on Recent Advances in Parallel Virtual Machine and Message Passing Interface
Year:
2005

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Abstract

A key process in association rules mining, which has attracted a lot of interest during the last decade, is the discovery of frequent sets of items in a database of transactions. A number of sequential algorithms have been proposed that accomplish this task. In this paper we study the parallelization of the partial-support-tree approach (Goulbourne, Coenen, Leng, 2000). Results show that this method achieves a generally satisfactory speedup, while it is particularly adequate for certain types of datasets.