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Speeding-Up the Dynamic Programming Procedure for the Edit Distance of Two Strings

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Database and Expert Systems Applications (DEXA 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1062))

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Abstract

We describe a way to compute the edit distance of two strings without having to fill the whole dynamic programming (DP) matrix, through a sequence of increasing guesses on the edit distance. If the strings share a certain degree of similarity, the edit distance can be quite smaller than the value of non-optimal solutions, and a large fraction (up to 80–90%) of the DP matrix cells do not need to be computed. Including the method’s overhead, this translates into a speedup factor from \(3\times \) up to \(30\times \) in the time needed to find the optimal solution for strings of length about 20,000.

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References

  1. Backurs, A., Indyk, P.: Edit distance cannot be computed in strongly subquadratic time (unless SETH is false). SIAM J. Comput. 47(3), 1087–1097 (2018)

    Article  MathSciNet  Google Scholar 

  2. Gotoh, O.: An improved algorithm for matching biological sequences. J. Mol. Biol. 162(3), 705–708 (1982)

    Article  Google Scholar 

  3. Gusfield, D.: Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology, 534 p. Cambridge University Press (1997)

    Google Scholar 

  4. Jones, N.C., Pevzner, P.A.: An Introduction to Bioinformatics Algorithms, 456 p. MIT Press (2004)

    Google Scholar 

  5. Levenshtein, V.I.: Binary codes capable of correcting deletions, insertions, and reversals. Doklady Akademii Nauk SSSR 163(4), 845–848 (1965)

    MathSciNet  MATH  Google Scholar 

  6. Needleman, S.B., Wunsch, C.D.: A general method applicable to the search for similarities in the amino acid sequence of two proteins. J. Mol. Biol. 48(3), 443–453 (1970)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Dipartimento di Scienze Matematiche, Informatiche e Fisiche, University of Udine, Via delle Scienze 206, 33100, Udine, Italy

    Giuseppe Lancia

  2. Dipartimento di Ingegneria dell’Informazione, University of Padova, Via Gradenigo 6/A, 35131, Padova, Italy

    Marcello Dalpasso

Authors
  1. Giuseppe Lancia
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  2. Marcello Dalpasso
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Corresponding author

Correspondence to Giuseppe Lancia .

Editor information

Editors and Affiliations

  1. Institute of Telecooperation, Johannes Kepler University of Linz, Linz, Oberösterreich, Austria

    Gabriele Anderst-Kotsis

  2. Software Competence Center Hagenberg, Hagenberg, Austria

    A Min Tjoa

  3. Institute of Telecooperation, Johannes Kepler University of Linz, Linz, Oberösterreich, Austria

    Ismail Khalil

  4. ENSIT, LaTICE, University of Tunis, Tunis, Tunisia

    Mourad Elloumi

  5. Software Competence Center, Hagenberg, Austria

    Atif Mashkoor

  6. Steyregg, Oberösterreich, Austria

    Johannes Sametinger

  7. Edificio 204, ICT Division,TECNALIA, Derio, Vizcaya, Spain

    Xabier Larrucea

  8. Top 74, Innsbruck, Tirol, Austria

    Anna Fensel

  9. Hagenberg Gmbh, Software Competence Center, Hagenberg im Mühlkreis, Oberösterreich, Austria

    Jorge Martinez-Gil

  10. Software Competence Center Hagenberg, SC, Hagenberg im Mühlkreis, Oberösterreich, Austria

    Bernhard Moser

  11. University of Twente, ENSCHEDE, Overijssel, The Netherlands

    Christin Seifert

  12. Bauhaus Universität Weimar, Weimar, Thüringen, Germany

    Benno Stein

  13. MiCS, Media Computer Science, University of Passau, Passau, Bayern, Germany

    Michael Granitzer

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Lancia, G., Dalpasso, M. (2019). Speeding-Up the Dynamic Programming Procedure for the Edit Distance of Two Strings. In: Anderst-Kotsis, G., et al. Database and Expert Systems Applications. DEXA 2019. Communications in Computer and Information Science, vol 1062. Springer, Cham. https://doi.org/10.1007/978-3-030-27684-3_9

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  • DOI: https://doi.org/10.1007/978-3-030-27684-3_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-27683-6

  • Online ISBN: 978-3-030-27684-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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