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Assertion Prediction with Ontologies through Evidence Combination

  • 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

Following previous works on inductive methods for ABox reasoning, we propose an alternative method for predicting assertions based on the available evidence and the analogical criterion. Once neighbors of a test individual are selected through some distance measures, a combination rule descending from the Dempster-Shafer theory can join together the evidence provided by the various neighbor individuals in order to predict unknown values in a learning problem. We show how to exploit the procedure in the problems of determining unknown class- and role-memberships or fillers for datatype properties which may be the basis for many further ABox inductive reasoning algorithms. This work presents also an empirical evaluation of the method on real ontologies.

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Author information

Authors and Affiliations

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

    Giuseppe Rizzo, Claudia d’Amato, Nicola Fanizzi & Floriana Esposito

Authors
  1. Giuseppe Rizzo
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  2. Claudia d’Amato
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  3. Nicola Fanizzi
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  4. Floriana Esposito
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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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Rizzo, G., d’Amato, C., Fanizzi, N., Esposito, F. (2013). Assertion Prediction with Ontologies through Evidence Combination. 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_15

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  • DOI: https://doi.org/10.1007/978-3-642-35975-0_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35974-3

  • Online ISBN: 978-3-642-35975-0

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