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Fuzzy Computational Ontologies in Contexts pp 37–47Cite as

Modeling Uncertainty in Knowledge Representation

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Abstract

The classical view in cognitive psychology holds that an object is either an instance of a concept or it is not. In terms of mathematics, every concept is a crisp set. However, as we have discussed above, many concepts do not have clear boundaries or definitions. Different objects have different degrees of membership or typicality with respect to a certain concept. In this section, we give a review of studies that investigate how graded membership, vagueness and uncertainty are modeled. Several extensions to existing ontology models or description logics involves fuzzy sets, therefore we will start by briefly reviewing the basic notions of fuzzy set theory.

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Author information

Authors and Affiliations

  1. School of Software Engineering, South China University of Technology, Guangzhou, 510006, China

    Dr. Yi Cai

  2. Hong Kong Applied Science and Technology Research Institute, Hong Kong, China

    Dr. Ching-man Au Yeung

  3. Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, China

    Prof. Ho-fung Leung

Authors
  1. Dr. Yi Cai
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  2. Dr. Ching-man Au Yeung
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  3. Prof. Ho-fung Leung
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© 2012 Higher Education Press, Beijing and Springer-Verlag Berlin Heidelberg

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Cai, Y., Au Yeung, Cm., Leung, Hf. (2012). Modeling Uncertainty in Knowledge Representation. In: Fuzzy Computational Ontologies in Contexts. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25456-7_4

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  • DOI: https://doi.org/10.1007/978-3-642-25456-7_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25455-0

  • Online ISBN: 978-3-642-25456-7

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