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OFR: An Efficient Representation of RDF Datasets

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Languages, Applications and Technologies (SLATE 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 563))

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Abstract

The constant growth of structured data, often in the form of RDF, demands for efficient compression methods, to facilitate their storage and transmission. We propose an RDF compression algorithm that produces a succinct representation of RDF datasets. It consists of two stages. The first splits the input triples into multiple streams, and applies tailored compaction techniques for each stream. In the second, a general-purpose compression is applied. We experimentally show on a number of datasets that the proposed algorithm achieves compression ratios significantly better than the RDF compressors known from the literature.

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Notes

  1. 1.

    http://www.compression.ru/ds/ppmdj1.rar (PPMd, var. J rev. 1, May 10, 2006, by D. Shkarin).

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    Z. Tan, ulib. An efficient library for developing high-performance and scalable systems in C and C++, 2012, http://code.google.com/p/ulib/.

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Author information

Authors and Affiliations

  1. Institute of Information Technology in Management, University of Szczecin, Mickiewicza 64, 71-101, Szczecin, Poland

    Jakub Swacha

  2. Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924, Łódź, Poland

    Szymon Grabowski

Authors
  1. Jakub Swacha
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  2. Szymon Grabowski
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Correspondence to Jakub Swacha .

Editor information

Editors and Affiliations

  1. Complutense University of Madrid, Madrid, Spain

    José-Luis Sierra-Rodríguez

  2. Universidade do Porto - DCC, Porto, Portugal

    José-Paulo Leal

  3. Universidade do Minho, Braga, Portugal

    Alberto Simões

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Swacha, J., Grabowski, S. (2015). OFR: An Efficient Representation of RDF Datasets. In: Sierra-Rodríguez, JL., Leal, JP., Simões, A. (eds) Languages, Applications and Technologies. SLATE 2015. Communications in Computer and Information Science, vol 563. Springer, Cham. https://doi.org/10.1007/978-3-319-27653-3_22

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  • DOI: https://doi.org/10.1007/978-3-319-27653-3_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27652-6

  • Online ISBN: 978-3-319-27653-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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