Four Metrics for Efficiently Comparing Attributed Trees

Andrea Torsello, Dzena Hidovic, Marcello Pelillo

Abstract: We address the problem of comparing attributed trees and propose four novel distance metrics centered around the notion of a maximal similarity common subtree, and hence can be computed in polynomial time. We experimentally validate the usefulness of our metrics on shape matching tasks, and compare them with edit-distance.