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POTMiner: mining ordered, unordered, and partially-ordered trees

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Abstract

Non-linear data structures are becoming more and more common in data mining problems. Trees, in particular, are amenable to efficient mining techniques. In this paper, we introduce a scalable and parallelizable algorithm to mine partially-ordered trees. Our algorithm, POTMiner, is able to identify both induced and embedded subtrees in such trees. As special cases, it can also handle both completely ordered and completely unordered trees.

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Authors and Affiliations

  1. Department of Computer Science and Artificial Intelligence, ETSIIT, University of Granada, Office 37, 18071, Granada, Spain

    Aída Jiménez & Juan-Carlos Cubero

  2. Department of Computer Science and Artificial Intelligence, ETSIIT, University of Granada, Office 17, 18071, Granada, Spain

    Fernando Berzal

Authors
  1. Aída Jiménez
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  2. Fernando Berzal
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  3. Juan-Carlos Cubero
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Correspondence to Aída Jiménez.

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Jiménez, A., Berzal, F. & Cubero, JC. POTMiner: mining ordered, unordered, and partially-ordered trees. Knowl Inf Syst 23, 199–224 (2010). https://doi.org/10.1007/s10115-009-0213-3

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  • DOI: https://doi.org/10.1007/s10115-009-0213-3

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