期刊
PATTERN RECOGNITION
卷 34, 期 1, 页码 127-137出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/S0031-3203(99)00199-5
关键词
dynamic programming; edit distance; pattern matching; trees; computational biology
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. (C) 2000 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
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