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Mining of Association Rules in Very Large Databases: A Structured Parallel Approach⋆

  • P. Becuzzi
  • M. Coppola
  • M. Vanneschi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1685)

Abstract

Newer and newer parallel architectures being developed raise a strong demand for high-level and programmer-friendly parallel tools. We show some results regarding mining of association rules, a well-known Data Mining algorithm, which we ported from sequential to parallel within the PQE2000/SkIE environment. The main goals achieved are the low effort spent in parallelizing the code, the machine independence of the application produced, source code portability and performance portability. Here we report test results for the same parallel program on three different architectures.

Keywords

Completion Time Association Rule Minimum Support Frequent Itemset Parallel Architecture 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • P. Becuzzi
    • 1
  • M. Coppola
    • 1
  • M. Vanneschi
    • 1
  1. 1.Dipartimento di InformaticaUniversità degli Studi di PisaItaly

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