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Frequent Pattern Mining in Attributed Trees

  • Claude Pasquier
  • Jérémy Sanhes
  • Frédéric Flouvat
  • Nazha Selmaoui-Folcher
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7818)

Abstract

Frequent pattern mining is an important data mining task with a broad range of applications. Initially focused on the discovery of frequent itemsets, studies were extended to mine structural forms like sequences, trees or graphs. In this paper, we introduce a new data mining method that consists in mining new kind of patterns in a collection of attributed trees (atrees). Attributed trees are trees in which vertices are associated with itemsets. Mining this type of patterns (called asubtrees), which combines tree mining and itemset mining, requires the exploration of a huge search space. We present several new algorithms for attributed trees mining and show that their implementations can efficiently list frequent patterns in a database of several thousand of attributed trees.

Keywords

tree mining frequent pattern mining attributed tree 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Claude Pasquier
    • 1
    • 2
  • Jérémy Sanhes
    • 1
  • Frédéric Flouvat
    • 1
  • Nazha Selmaoui-Folcher
    • 1
  1. 1.PPMEUniversity of New CaledoniaNouméaFrance
  2. 2.Institute of Biology Valrose (IBV), UNS - CNRS UMR7277 - INSERM U1091Nice cedex 2France

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