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Constrained longest common subsequence computing algorithms in practice

  • Goldman Sachs Group

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)

Abstract

The problem of finding a constrained longest common subsequence (CLCS) for the sequences A and B with respect to sequence P was introduced recently. Its goal is to find a longest subsequence C of A and B such that P is a subsequence of C. There are several algorithms solving the CLCS problem, but there is no real experimental comparison of them. The paper has two aims. Firstly, we propose an improvement to the algorithms by Chin et al. and Deorowicz based on an entry-exit points technique by He and Arslan. Secondly, we compare experimentally the existing algorithms for solving the CLCS problem.

Original languageEnglish
Pages (from-to)427-445
Number of pages19
JournalComputing and Informatics
Volume29
Issue number3
Publication statusPublished - 2010

Keywords

  • Ceconstrained longest common subsequence
  • Longest common subsequent
  • Sequence alignment
  • Sparse dynamic programming
  • String matching

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications
  • Computational Theory and Mathematics

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