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Efficient Algorithms for Similarity Search

Author

Listed:
  • S. Rajasekaran

    (University of Florida)

  • Y. Hu

    (University of Florida)

  • J. Luo

    (University of Florida)

  • H. Nick

    (University of Florida)

  • P.M. Pardalos

    (University of Florida)

  • S. Sahni

    (University of Florida)

  • G. Shaw

    (University of Florida)

Abstract

The problem of our interest takes as input a database of m sequences from an alphabet Σ and an integer k. The goal is to report all the pairs of sequences that have a matching subsequence of length at least k. We employ two algorithms to solve this problem. The first algorithm is based on sorting and the second is based on generalized suffix trees. We provide experimental data comparing the performances of these algorithms. The generalized suffix tree based algorithm performs better than the sorting based algorithm.

Suggested Citation

  • S. Rajasekaran & Y. Hu & J. Luo & H. Nick & P.M. Pardalos & S. Sahni & G. Shaw, 2001. "Efficient Algorithms for Similarity Search," Journal of Combinatorial Optimization, Springer, vol. 5(1), pages 125-132, March.
  • Handle: RePEc:spr:jcomop:v:5:y:2001:i:1:d:10.1023_a:1009897903540
    DOI: 10.1023/A:1009897903540
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    Cited by:

    1. Blum, Christian & Lozano, José A. & Davidson, Pinacho, 2015. "Mathematical programming strategies for solving the minimum common string partition problem," European Journal of Operational Research, Elsevier, vol. 242(3), pages 769-777.

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