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Query Evaluation on Probabilistic RDF Databases

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Web Information Systems Engineering - WISE 2009 (WISE 2009)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5802))

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Abstract

Over the last few years, RDF has been used as a knowledge representation model in a wide variety of domains. Some domains are full of uncertainty. Thus, it is desired to process and manage probabilistic RDF data. The core operation of queries on an RDF probabilistic database is computing the probability of the result to a query. In this paper, we describe a general framework for supporting SPARQL queries on probabilistic RDF databases. In particular, we consider transitive inference capability for RDF instance data. We show that the find operation for an atomic query with the transitive property can be formalized as the problem of computing path expressions on the transitive relation graph and we also propose an approximate algorithm for computing path expressions efficiently. At last, we implement and experimentally evaluate our approach.

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Author information

Authors and Affiliations

  1. Faulty of ICT, Swinburne University of Technology, Australia

    Hai Huang & Chengfei Liu

Authors
  1. Hai Huang
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  2. Chengfei Liu
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Editor information

Editors and Affiliations

  1. European Research Center for Information Systems, University of Münster,, Leonardo Campus 3, 48149, Münster, Germany

    Gottfried Vossen

  2. Dept. of Computer Science, School of Engineering, University of California, 95064, Santa Cruz, CA, USA

    Darrell D. E. Long

  3. Dept. of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, William M. W. Mong Engineering Building, Shatin, N. T.,, Hong Kong, China

    Jeffrey Xu Yu

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© 2009 Springer-Verlag Berlin Heidelberg

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Huang, H., Liu, C. (2009). Query Evaluation on Probabilistic RDF Databases. In: Vossen, G., Long, D.D.E., Yu, J.X. (eds) Web Information Systems Engineering - WISE 2009. WISE 2009. Lecture Notes in Computer Science, vol 5802. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04409-0_32

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  • DOI: https://doi.org/10.1007/978-3-642-04409-0_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04408-3

  • Online ISBN: 978-3-642-04409-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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