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Canadian Semantic Web pp 27–53Cite as

Knowledge Representation and Reasoning in Norm-Parameterized Fuzzy Description Logics

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Abstract

The Semantic Web is an evolving extension of the World Wide Web in which the semantics of the available information are formally described, making it more machine-interpretable. The current W3C standard for SemanticWeb ontology languages, OWL, is based on the knowledge representation formalism of Description Logics (DLs). Although standard DLs provide considerable expressive power, they cannot express various kinds of imprecise or vague knowledge and thus cannot deal with uncertainty, an intrinsic feature of the real world and our knowledge. To overcome this deficiency, this chapter extends a standard Description Logic to a family of norm-parameterized Fuzzy Description Logics. The syntax to represent uncertain knowledge and the semantics to interpret fuzzy concept descriptions and knowledge bases are addressed in detail. The chapter then focuses on a procedure for reasoning with knowledge bases in the proposed Fuzzy Description Logics. Finally, we prove the soundness, completeness, and termination of the reasoning procedure

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Authors and Affiliations

  1. Faculty of Computer Science, University of New Brunswick, Fredericton, NB, E3B 5A3, Canada

    Jidi Zhao

  2. Institute for Information Technology, National Research Council of Canada, Fredericton, NB, E3B 9W4, Canada

    Harold Boley

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  1. Jidi Zhao
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  2. Harold Boley
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Correspondence to Jidi Zhao .

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Editors and Affiliations

  1. , Faculty of Computer Science, University of New Brunswick, Fredericton, E3B 5A3, Canada

    Weichang Du

  2. , Faculty of Computer Science, University of New Brunswick, Fredericton, E3B 5A3, Canada

    Faezeh Ensan

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Zhao, J., Boley, H. (2010). Knowledge Representation and Reasoning in Norm-Parameterized Fuzzy Description Logics. In: Du, W., Ensan, F. (eds) Canadian Semantic Web. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-7335-1_2

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  • DOI: https://doi.org/10.1007/978-1-4419-7335-1_2

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  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-7334-4

  • Online ISBN: 978-1-4419-7335-1

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