Modeling Uncertainty in Knowledge Representation

  • Yi Cai
  • Ching-man Au Yeung
  • Ho-fung Leung

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.

Keywords

Membership Function Knowledge Representation Semantic Similarity Resource Description Framework Description Logic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Higher Education Press, Beijing and Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Yi Cai
    • 1
  • Ching-man Au Yeung
    • 2
  • Ho-fung Leung
    • 3
  1. 1.School of Software EngineeringSouth China University of TechnologyGuangzhouChina
  2. 2.Hong Kong Applied Science and Technology Research InstituteHong KongChina
  3. 3.Department of Computer Science and EngineeringThe Chinese University of Hong KongHong KongChina

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