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International Symposium on Algorithms and Computation

ISAAC 2004: Algorithms and Computation pp 452–463Cite as

Fast Algorithms for Comparison of Similar Unordered Trees

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3341))

Abstract

We present fast algorithms for computing the largest common subtree (LCST) and the optimal alignment when two similar unordered trees are given. We present an O(4K n) time algorithm for the LCST problem for rooted trees, where n is the maximum size of two input trees and K is the minimum number of edit operations to obtain LCST. We extend this algorithm to unrooted trees and obtain an O(K 4K n) time algorithm. We also show that the alignment problem for rooted and unordered trees of bounded degree can be solved in linear time if K is bounded by a constant.

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Author information

Authors and Affiliations

  1. Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto, 606–8501, Japan

    Daiji Fukagawa

  2. Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, 611–0011, Japan

    Tatsuya Akutsu

Authors
  1. Daiji Fukagawa
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  2. Tatsuya Akutsu
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Fudan University, 200433, Shanghai, China

    Rudolf Fleischer

  2. Department of Computer Science, The Hong Kong University of Science and Technology, Hong Kong

    Gerhard Trippen

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© 2004 Springer-Verlag Berlin Heidelberg

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Fukagawa, D., Akutsu, T. (2004). Fast Algorithms for Comparison of Similar Unordered Trees. In: Fleischer, R., Trippen, G. (eds) Algorithms and Computation. ISAAC 2004. Lecture Notes in Computer Science, vol 3341. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30551-4_40

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  • DOI: https://doi.org/10.1007/978-3-540-30551-4_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24131-7

  • Online ISBN: 978-3-540-30551-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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