PGP-mc: Towards a Multicore Parallel Approach for Mining Gradual Patterns

  • Anne Laurent
  • Benjamin Negrevergne
  • Nicolas Sicard
  • Alexandre Termier
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5981)


Gradual patterns highlight complex order correlations of the form “The more/less X, the more/less Y”. Only recently algorithms have appeared to mine efficiently gradual rules. However, due to the complexity of mining gradual rules, these algorithms cannot yet scale on huge real world datasets. In this paper, we propose to exploit parallelism in order to enhance the performances of the fastest existing one (GRITE). Through a detailed experimental study, we show that our parallel algorithm scales very well with the number of cores available.


Association Rule Pattern Mining Frequent Itemsets Multicore Processor Gradual Pattern 
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 2010

Authors and Affiliations

  • Anne Laurent
    • 1
  • Benjamin Negrevergne
    • 2
  • Nicolas Sicard
    • 3
  • Alexandre Termier
    • 2
  1. 1.LIRMM - UM2- CNRS UMR 5506Montpellier Cedex 5
  2. 2.LIG - UJF-CNRS UMR 5217Saint Martin d’Hères
  3. 3.LRIE - EFREI - 30-32 av. de la républiqueVillejuif

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