Foundations of Refinement Operators for Description Logics
From Ontology Learning
|title||Foundations of Refinement Operators for Description Logics|
|author||Jens Lehmann, Pascal Hitzler|
|editor||Hendrick Blockeel, Jude W. Shavlik, Prasad Tadepalli|
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.