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Fixed Block Compression Boosting in FM-Indexes

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String Processing and Information Retrieval (SPIRE 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7024))

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Abstract

A compressed full-text self-index occupies space close to that of the compressed text and simultaneously allows fast pattern matching and random access to the underlying text. Among the best compressed self-indexes, in theory and in practice, are several members of the FM-index family. In this paper, we describe new FM-index variants that combine nice theoretical properties, simple implementation and improved practical performance. Our main result is a new technique called fixed block compression boosting, which is a simpler and faster alternative to optimal compression boosting and implicit compression boosting used in previous FM-indexes.

Juha Kärkkäinen is supported by Academy of Finland grant 118653 (ALGODAN). Simon J. Puglisi is supported by a Newton Fellowship.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Helsinki, Finland

    Juha Kärkkäinen

  2. Department of Informatics, King’s College London, London, United Kingdom

    Simon J. Puglisi

Authors
  1. Juha Kärkkäinen
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  2. Simon J. Puglisi
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Editor information

Editors and Affiliations

  1. Università di Pisa, Italy

    Roberto Grossi

  2. Consiglio Nazionale delle Ricerche, Area della Ricerca di Pisa, Istituto di Scienza e Tecnologia dell’Informazione “Alessandro Faedo”, Via Giuseppe Moruzzi 1, 56124, Pisa, Italy

    Fabrizio Sebastiani  & Fabrizio Silvestri  & 

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Kärkkäinen, J., Puglisi, S.J. (2011). Fixed Block Compression Boosting in FM-Indexes. In: Grossi, R., Sebastiani, F., Silvestri, F. (eds) String Processing and Information Retrieval. SPIRE 2011. Lecture Notes in Computer Science, vol 7024. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24583-1_18

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  • DOI: https://doi.org/10.1007/978-3-642-24583-1_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24582-4

  • Online ISBN: 978-3-642-24583-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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