Foundations of Refinement Operators for Description Logics

  • Jens Lehmann
  • Pascal Hitzler
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4894)


In order to leverage techniques from Inductive Logic Programming for the learning in description logics (DLs), which are the foundation of ontology languages in the Semantic Web, it is important to acquire a thorough understanding of the theoretical potential and limitations of using refinement operators within the description logic paradigm. In this paper, we present a comprehensive study which analyses desirable properties such operators should have. In particular, we show that ideal refinement operators in general do not exist, which is indicative of the hardness inherent in learning in DLs. We also show which combinations of desirable properties are theoretically possible, thus providing an important step towards the definition of practically applicable operators.


Inductive Logic Programming Weak Equality Complete Operator Refinement Operator Negation Normal Form 
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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© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Jens Lehmann
    • 1
  • Pascal Hitzler
    • 2
  1. 1.Department of Computer ScienceUniversität LeipzigLeipzigGermany
  2. 2.AIFB InstituteUniversität Karlsruhe (TH)KarlsruheGermany

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