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Computing Frequent Itemsets in Parallel Using Partial Support Trees

  • Dora Souliou
  • Aris Pagourtzis
  • Nikolaos Drosinos
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3666)

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.

Keywords

Parallel data mining association rules frequent itemsets partial support tree set-enumeration tree 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Dora Souliou
    • 1
  • Aris Pagourtzis
    • 1
  • Nikolaos Drosinos
    • 1
  1. 1.School of Electrical and Computer EngineeringNational Technical University of AthensZografouGreece

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