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Efficiently Computing Weighted Tree Edit Distance Using Relaxation Labeling

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Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2134))

Abstract

This paper investigates an approach to tree edit distance problem with weighted nodes. We show that any tree obtained with a sequence of cut and relabel operations is a subtree of the transitive closure of the original tree. Furthermore, we show that the necessary condition for any subtree to be a solution can be reduced to a clique problem in a derived structure. Using this idea we transform the tree edit distance problem into a series of maximum weight clique problems and then we use relaxation labeling to find an approximate solution.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of York, York, YO10 5DD, UK

    Andrea Torsello & Edwin R. Hancock

Authors
  1. Andrea Torsello
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  2. Edwin R. Hancock
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Editor information

Editors and Affiliations

  1. Instituto de Telecomunicacoes and Instituto Superior Tecnico, 1049-001, Lisboa, Portugal

    Mário Figueiredo

  2. INRIA, 2004 Route des Lucioles, 06902 Sophia-Antipolis cedex, France

    Josiane Zerubia

  3. Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, 48824, USA

    Anil K. Jain

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© 2001 Springer-Verlag Berlin Heidelberg

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Torsello, A., Hancock, E.R. (2001). Efficiently Computing Weighted Tree Edit Distance Using Relaxation Labeling. In: Figueiredo, M., Zerubia, J., Jain, A.K. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 2001. Lecture Notes in Computer Science, vol 2134. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44745-8_29

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  • DOI: https://doi.org/10.1007/3-540-44745-8_29

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42523-6

  • Online ISBN: 978-3-540-44745-0

  • eBook Packages: Springer Book Archive

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