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Longest Common Subsequence in k Length Substrings

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Similarity Search and Applications (SISAP 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8199))

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Abstract

In this paper we define a new problem, motivated by computational biology, LCSk aiming at finding the maximal number of k length substrings, matching in both input string while preserving their order of appearance in the input strings. The traditional LCS definition is a spacial case of our problem, where k = 1. We provide an algorithm, solving the general case in O(n 2) time, where n is the length of the input, equaling the time required for the special case of k = 1. The space requirement is O(kn). In order to enable backtracking of the solution O(n 2) space is needed.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Boston University, Boston, MA, 02215, USA

    Gary Benson

  2. Department of Software Engineering, Shenkar College, Ramat-Gan, 52526, Israel

    Avivit Levy & B. Riva Shalom

Authors
  1. Gary Benson
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  2. Avivit Levy
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  3. B. Riva Shalom
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Editor information

Editors and Affiliations

  1. Database Laboratory, Universidade da Coruña, Spain

    Nieves Brisaboa  & Oscar Pedreira  & 

  2. Faculty of Informatics, Masaryk University, Brno, Czech Republic

    Pavel Zezula

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Benson, G., Levy, A., Shalom, B.R. (2013). Longest Common Subsequence in k Length Substrings. In: Brisaboa, N., Pedreira, O., Zezula, P. (eds) Similarity Search and Applications. SISAP 2013. Lecture Notes in Computer Science, vol 8199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41062-8_26

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  • DOI: https://doi.org/10.1007/978-3-642-41062-8_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41061-1

  • Online ISBN: 978-3-642-41062-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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