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A Polynomial-Time Metric for Attributed Trees

  • Andrea Torsello
  • Džena Hidović
  • Marcello Pelillo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3024)

Abstract

We address the problem of comparing attributed trees and propose a novel distance measure centered around the notion of a maximal similarity common subtree. The proposed measure is general and defined on trees endowed with either symbolic or continuous-valued attributes, and can be equally applied to ordered and unordered, rooted and unrooted trees. We prove that our measure satisfies the metric constraints and provide a polynomial-time algorithm to compute it. This is a remarkable and attractive property since the computation of traditional edit-distance-based metrics is NP-complete, except for ordered structures. We experimentally validate the usefulness of our metric on shape matching tasks, and compare it with edit-distance measures.

Keywords

Editing Distance Rand Index Attribute Tree Unrooted Tree Pattern Recognition Letter 
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 2004

Authors and Affiliations

  • Andrea Torsello
    • 1
  • Džena Hidović
    • 2
  • Marcello Pelillo
    • 1
  1. 1.Dipartimento di InformaticaUniversità Ca’ Foscari di VeneziaVenezia MestreItaly
  2. 2.School of Computer ScienceUniversity of BirminghamEdgbaston, BirminghamUnited Kingdom

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