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Semantic Web Search and Inductive Reasoning

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Book cover 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

Extensive research activities are recently directed towards the Semantic Web as a future form of the Web. Consequently, Web search as the key technology of the Web is evolving towards some novel form of Semantic Web search. A very promising recent such approach is based on combining standard Web pages and search queries with ontological background knowledge, and using standard Web search engines as the main inference motor of Semantic Web search. In this paper, we further enhance this approach to Semantic Web search by the use of inductive reasoning techniques. This adds especially the important ability to handle inconsistencies, noise, and incompleteness, which are all very likely to occur in distributed and heterogeneous environments, such as the Web. We report on a prototype implementation of the new approach and experimental results.

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Author information

Authors and Affiliations

  1. Dipartimento di Informatica, Università degli Studi di Bari, Italy

    Claudia d’Amato & Nicola Fanizzi

  2. Dipartimento di Elettronica, Informatica e Sistemistica, Università della Calabria, Italy

    Bettina Fazzinga

  3. Department of Computer Science, University of Oxford, UK

    Georg Gottlob & Thomas Lukasiewicz

  4. Oxford-Man Institute of Quantitative Finance, University of Oxford, UK

    Georg Gottlob

Authors
  1. Claudia d’Amato
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  2. Nicola Fanizzi
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  3. Bettina Fazzinga
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  4. Georg Gottlob
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  5. Thomas Lukasiewicz
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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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d’Amato, C., Fanizzi, N., Fazzinga, B., Gottlob, G., Lukasiewicz, T. (2013). Semantic Web Search and Inductive Reasoning. 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_13

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  • DOI: https://doi.org/10.1007/978-3-642-35975-0_13

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