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Statistical Learning for Inductive Query Answering on OWL Ontologies

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Part of the book series:Lecture Notes in Computer Science ((LNISA,volume 5318))

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Abstract

A novel family of parametric language-independent kernel functions defined for individuals within ontologies is presented. They are easily integrated with efficient statistical learning methods for inducing linear classifiers that offer an alternative way to perform classification w.r.t. deductive reasoning. A method for adapting the parameters of the kernel to the knowledge base through stochastic optimization is also proposed. This enables the exploitation of statistical learning in a variety of tasks where an inductive approach may bridge the gaps of the standard methods due the inherent incompleteness of the knowledge bases. In this work, a system integrating the kernels has been tested in experiments on approximate query answering with real ontologies collected from standard repositories.

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Authors and Affiliations

  1. Dipartimento di Informatica, Università degli Studi di Bari, Campus Universitario, Via Orabona 4, 70125, Bari, Italy

    Nicola Fanizzi, Claudia d’Amato & Floriana Esposito

Authors
  1. Nicola Fanizzi
  2. Claudia d’Amato
  3. Floriana Esposito

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Wright State University, Colonel Glenn Way 3640, 454350001, Dayton, USA

    Amit Sheth

  2. Institut für Informatik, Universität Koblenz-Landau, Universitätsstr. 1, 56016, Koblenz, Germany

    Steffen Staab

  3. BBN Technologies, 48103, Ann Arbor, USA

    Mike Dean

  4. DoCoMo Communications Laboratories Europe GmbH, 80687, Munich, Germany

    Massimo Paolucci

  5. Department of Computer Science, University of Sheffield, Regent Court, 211 Portobello Street, S1 4DP, Sheffield, UK

    Diana Maynard

  6. CSEE Department, UMBC, 1000 Hilltop Circle, MD 21250, Baltimore, USA

    Timothy Finin

  7. Department of Computer Science and Engineering, Wright State University, 3640 Colonel Glenn Highway, OH 45435, Dayton, USA

    Krishnaprasad Thirunarayan

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© 2008 Springer-Verlag Berlin Heidelberg

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Fanizzi, N., d’Amato, C., Esposito, F. (2008). Statistical Learning for Inductive Query Answering on OWL Ontologies. In: Sheth, A.,et al. The Semantic Web - ISWC 2008. ISWC 2008. Lecture Notes in Computer Science, vol 5318. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88564-1_13

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