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Predicate Invention Based RDF Data Compression

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Semantic Technology (JIST 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11341))

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Abstract

RDF is a data representation format for schema-free structured information that is gaining speed in the context of semantic web, life science, and vice versa. With the continuing proliferation of structured data, demand for RDF compression is becoming increasingly important. In this study, we introduce a novel lossless compression technique for RDF datasets (triples), called PIC (Predicate Invention based Compression). By generating informative predicates and constructing effective mapping to original predicates, PIC only needs to store dramatically reduced number of triples with the newly created predicates, and restoring the original triples efficiently using the mapping. These predicates are automatically generated by a decomposable forward-backward procedure, which consequently supports very fast parallel bit computation. As a semantic compression method for structured data, besides the reduction of syntactic verbosity and data redundancy, we also invoke semantics in the RDF datasets. Experiments on various datasets show competitive results in terms of compression ratio.

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Notes

  1. 1.

    http://www.bzip.org.

  2. 2.

    http://www.7-zip.org/.

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Acknowledgement

This work is partially funded by the National Science Foundation of China under grant 61602260 and 61702279.

Author information

Authors and Affiliations

  1. School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, China

    Man Zhu, Weixin Wu, Jingyu Han & Qian Liu

  2. Department of Computing Science, University of Aberdeen, Aberdeen, UK

    Jeff Z. Pan

  3. College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China

    Pengfei Huang

Authors
  1. Man Zhu
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  2. Weixin Wu
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  3. Jeff Z. Pan
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  4. Jingyu Han
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  5. Pengfei Huang
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  6. Qian Liu
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Corresponding author

Correspondence to Man Zhu .

Editor information

Editors and Affiliations

  1. National Institute of Informatics, Tokyo, Japan

    Ryutaro Ichise

  2. Accenture Labs, Dublin, Ireland

    Freddy Lecue

  3. Japan Science and Technology Agency, Tokyo, Japan

    Takahiro Kawamura

  4. Peking University, Beijing, China

    Dongyan Zhao

  5. Imperial College London, London, UK

    Stephen Muggleton

  6. Osaka University, Osaka, Japan

    Kouji Kozaki

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Zhu, M., Wu, W., Pan, J.Z., Han, J., Huang, P., Liu, Q. (2018). Predicate Invention Based RDF Data Compression. In: Ichise, R., Lecue, F., Kawamura, T., Zhao, D., Muggleton, S., Kozaki, K. (eds) Semantic Technology. JIST 2018. Lecture Notes in Computer Science(), vol 11341. Springer, Cham. https://doi.org/10.1007/978-3-030-04284-4_11

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  • DOI: https://doi.org/10.1007/978-3-030-04284-4_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04283-7

  • Online ISBN: 978-3-030-04284-4

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