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Storing and Querying Fuzzy Knowledge in the Semantic Web Using FiRE

  • Conference paper
Uncertainty Reasoning for the Semantic Web II (URSW 2010, URSW 2009, URSW 2008, UniDL 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7123))

Abstract

An important problem for the success of ontology-based applications is how to provide persistent storage and querying. For that purpose, many RDF tools capable of storing and querying over a knowledge base, have been proposed. Recently, fuzzy extensions to ontology languages have gained considerable attention especially due to their ability to handle vague information. In this paper we investigate on the issue of using classical RDF storing systems in order to provide persistent storing and querying over large scale fuzzy information. To accomplish this we propose a novel way for serializing fuzzy information into RDF triples, thus classical storing systems can be used without any extensions. Additionally, we extend the existing query languages of RDF stores in order to support expressive fuzzy querying services over the stored data. All our extensions have been implemented in FiRE—an expressive fuzzy DL reasoner that supports the language fuzzy-\(\mathcal{SHIN}\). Finally, the proposed architecture is evaluated using an industrial application scenario about casting for TV commercials and spots.

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Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, National Technical University of Athens, Zographou, 15780, Greece

    Nikolaos Simou, Giorgos Stoilos & Giorgos Stamou

Authors
  1. Nikolaos Simou
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  2. Giorgos Stoilos
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  3. Giorgos Stamou
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Systems Engineering, University of Zaragoza, Ada Byron Building, Maria de Luna 1, 50018, Zaragoza, Spain

    Fernando Bobillo

  2. Department of Systems Engineering and Operations Research, George Mason University, Engineering Building, 4400 University Drive, 22030-4444, Fairfax, VA, USA

    Paulo C. G. Costa

  3. Dipatimento di Informatica, Università degli Studi di Bari, Via Orabona 4, 70125, Bari, Italy

    Claudia d’Amato

  4. Dipatimento di Informatica and CILA, Università degli Studi di Bari, Via Orabona 4, 70125, Bari, Italy

    Nicola Fanizzi

  5. Department of Systems Engineering and Operations Research, George Mason University, Engineering Building, 4400 University Drive, 22030-4444, Fairfax, VA, USA

    Kathryn B. Laskey

  6. MIRTE Corporation, M/S H305, 7515 Colshire Drive, 22102-7508, McLean, VA, USA

    Kenneth J. Laskey

  7. Department of Computer Science, University of Oxford, Wolfson Building, Parks Road, OX1 3QD, Oxford, UK

    Thomas Lukasiewicz

  8. Technische Universität München, Abteilung für Informatk, Boltzmannstraße 3, 85748, Garching, Germany

    Matthias Nickles

  9. Goldman Sachs, 30 Hudson Street, 07302-4699, Jersey City, NJ, USA

    Michael Pool

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Simou, N., Stoilos, G., Stamou, G. (2013). Storing and Querying Fuzzy Knowledge in the Semantic Web Using FiRE. In: Bobillo, F., et al. Uncertainty Reasoning for the Semantic Web II. URSW URSW URSW UniDL 2010 2009 2008 2010. Lecture Notes in Computer Science(), vol 7123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35975-0_9

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  • DOI: https://doi.org/10.1007/978-3-642-35975-0_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35974-3

  • Online ISBN: 978-3-642-35975-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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