An even Faster and More Unifying Algorithm for Comparing Trees via Unbalanced Bipartite Matchings

Ming Yang Kao*, Tak Wah Lam, Wing Kin Sung, Hing Fung Ting

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

46 Scopus citations


A widely used method for determining the similarity of two labeled trees is to compute a maximum agreement subtree of the two trees. Previous work on this similarity measure has only been concerned with the comparison of labeled trees of two special kinds, namely, uniformly labeled trees (i.e., trees with all their nodes labeled with the same symbol) and evolutionary trees (i.e., leaf-labeled trees with distinct symbols for distinct leaves). This paper presents an algorithm for comparing trees that are labeled in an arbitrary manner. In addition to this generality, this algorithm is faster than the previous algorithms. Another contribution of this paper is on maximum weight bipartite matchings. We show how to speed up the best known matching algorithms when the input graphs are node-unbalanced or weight-unbalanced. Based on these enhancements, we obtain an efficient algorithm for a new matching problem called the hierarchical bipartite matching problem, which is at the core of our maximum agreement subtree algorithm.

Original languageEnglish (US)
Pages (from-to)212-233
Number of pages22
JournalJournal of Algorithms
Issue number2
StatePublished - Aug 2001

ASJC Scopus subject areas

  • Control and Optimization
  • Computational Mathematics
  • Computational Theory and Mathematics


Dive into the research topics of 'An even Faster and More Unifying Algorithm for Comparing Trees via Unbalanced Bipartite Matchings'. Together they form a unique fingerprint.

Cite this