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How Fuzzy Is My Fuzzy Description Logic?

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Automated Reasoning (IJCAR 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7364))

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Abstract

Fuzzy Description Logics (DLs) with t-norm semantics have been studied as a means for representing and reasoning with vague knowledge. Recent work has shown that even fairly inexpressive fuzzy DLs become undecidable for a wide variety of t-norms. We complement those results by providing a class of t-norms and an expressive fuzzy DL for which ontology consistency is linearly reducible to crisp reasoning, and thus has its same complexity. Surprisingly, in these same logics crisp models are insufficient for deciding fuzzy subsumption.

Partially supported by the DFG under grant BA 1122/17-1 and in the Collaborative Research Center 912 “Highly Adaptive Energy-Efficient Computing”.

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Author information

Authors and Affiliations

  1. Theoretical Computer Science, TU Dresden, Germany

    Stefan Borgwardt, Felix Distel & Rafael Peñaloza

Authors
  1. Stefan Borgwardt
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  2. Felix Distel
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  3. Rafael Peñaloza
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Editor information

Editors and Affiliations

  1. Fakultät für Informatik, Technische Universität Wien, Favoritenstr. 9, E185/2, 1040, Wien, Austria

    Bernhard Gramlich

  2. École Polytechnique, INRIA Saclay and Laboratoire d’Informatique, Route de Saclay, 91128, Palaiseau Cedex, France

    Dale Miller

  3. School of Computer Science, University of Manchester, Oxford Road, M13 9PL, Manchester, UK

    Uli Sattler

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Borgwardt, S., Distel, F., Peñaloza, R. (2012). How Fuzzy Is My Fuzzy Description Logic?. In: Gramlich, B., Miller, D., Sattler, U. (eds) Automated Reasoning. IJCAR 2012. Lecture Notes in Computer Science(), vol 7364. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31365-3_9

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  • DOI: https://doi.org/10.1007/978-3-642-31365-3_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31364-6

  • Online ISBN: 978-3-642-31365-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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