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Improved and Extended Locating Functionality on Compressed Suffix Arrays

  • Conference paper
Experimental Algorithms (SEA 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8504))

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Abstract

Compressed Suffix Arrays (CSAs) offer the same functionality as classical suffix arrays (SAs), and more, within space close to that of the compressed text, and in addition they can reproduce any text fragment. Furthermore, their pattern search times are comparable to those of SAs. This combination has made CSAs extremely successful substitutes for SAs on space-demanding applications. Their weakest point is that they are orders of magnitude slower when reporting the precise positions of pattern occurrences. SAs have other well-known shortcomings, inherited by CSAs, such as retrieving those positions in arbitrary order. In this paper we present new techniques that, on one hand, improve the current space/time tradeoffs for locating pattern occurrences on CSAs, and on the other, efficiently support extended pattern locating functionalities, such as reporting occurrences in text order or limiting the occurrences to within a text window. Our experimental results display considerable savings with respect to the baseline techniques.

Funded by Fondecyt grant 1-140796, Chile and ARC grant DP110101743, Australia.

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Author information

Authors and Affiliations

  1. Department of Computing and Information Systems, The University of Melbourne, Australia

    Simon Gog

  2. Department of Computer Science, University of Chile, Chile

    Gonzalo Navarro

Authors
  1. Simon Gog
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  2. Gonzalo Navarro
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Editors and Affiliations

  1. School of IT, University of Sydney, Building J12, 2006, Sydney, NSW, Australia

    Joachim Gudmundsson

  2. Department of Computer Science, University of Copenhagen, Universitetsparken 5, 2100, Copenhagen East, Denmark

    Jyrki Katajainen

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Gog, S., Navarro, G. (2014). Improved and Extended Locating Functionality on Compressed Suffix Arrays. In: Gudmundsson, J., Katajainen, J. (eds) Experimental Algorithms. SEA 2014. Lecture Notes in Computer Science, vol 8504. Springer, Cham. https://doi.org/10.1007/978-3-319-07959-2_37

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  • DOI: https://doi.org/10.1007/978-3-319-07959-2_37

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07958-5

  • Online ISBN: 978-3-319-07959-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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