Mining induced and embedded subtrees in ordered, unordered, and partially-ordered trees

  • Authors:
  • Aída Jiménez;Fernando Berzal;Juan-Carlos Cubero

  • Affiliations:
  • Dept. Computer Science and Artificial Intelligence, ETSIIT, University of Granada, Granada, Spain;Dept. Computer Science and Artificial Intelligence, ETSIIT, University of Granada, Granada, Spain;Dept. Computer Science and Artificial Intelligence, ETSIIT, University of Granada, Granada, Spain

  • Venue:
  • ISMIS'08 Proceedings of the 17th international conference on Foundations of intelligent systems
  • Year:
  • 2008

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Abstract

Many data mining problems can be represented with non-linear data structures like trees. In this paper, we introduce a scalable algorithm to mine partially-ordered trees. Our algorithm, POTMiner, is able to identify both induced and embedded subtrees and, as special cases, it can handle both completely ordered and completely unordered trees (i.e. the particular situations existing algorithms address).