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Polynomial-time metrics for attributed trees

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3 Author(s)
A. Torsello ; Dipartimento di Informatica, Universita Ca Foscari di Venezia, Venezia Mestre, Italy ; D. Hidovic-Rowe ; M. Pelillo

We address the problem of comparing attributed trees and propose four novel distance measures centered around the notion of a maximal similarity common subtree. The proposed measures are general and defined on trees endowed with either symbolic or continuous-valued attributes and can be applied to rooted as well as unrooted trees. We prove that our measures satisfy the metric constraints and provide a polynomial-time algorithm to compute them. This is a remarkable and attractive property, since the computation of traditional edit-distance-based metrics is, in general, NP-complete, at least in the unordered case. We experimentally validate the usefulness of our metrics on shape matching tasks and compare them with (an approximation of) edit-distance.

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:27 ,  Issue: 7 )