Finding similar consensus between trees: An algorithm and a distance hierarchy

Document Type

Article

Publication Date

1-1-2001

Abstract

The problem of finding this similar consensus (also known as the largest approximately common substructures) of two trees arises in many pattern recognition applications. This paper presents a dynamic programming algorithm to solve the problem based on the distance measure originated from Tanaka and Tanaka. The algorithm runs as fast as the best-known algorithm for comparing two trees using Tanaka's distance measure when the allowed distance between the common substructures is a constant independent of the input trees. In addition, we establish a hierarchy among Tanaka's distance measure and three other edit-based distance measures published in the literature. © 2000 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

Identifier

0035196763 (Scopus)

Publication Title

Pattern Recognition

External Full Text Location

https://doi.org/10.1016/S0031-3203(99)00199-5

ISSN

00313203

First Page

127

Last Page

137

Issue

1

Volume

34

Grant

IRI-9531548

Fund Ref

National Science Foundation

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