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. © Springer-Verlag Berlin Heidelberg 2004.
CITATION STYLE
Torsello, A., Hidović, D., & Pelillo, M. (2004). A polynomial-time metric for attributed trees. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3024, 414–427. https://doi.org/10.1007/978-3-540-24673-2_34
Mendeley helps you to discover research relevant for your work.