Abstract

Similarity measures play a key role in the Semantic Web perspective. Indeed, most of the ontology related operations such as ontology learning, ontology alignment, ontology ranking and ontology population are grounded on the notion of similarity. In the last few years several similarity functions have been proposed for measuring both concept similarity and ontology similarity. However, they lack of a comprehensive formal characterization that is able to explain their behavior and value added, in particular when the ontologies are formulated in description logics languages like OWL-DL. Concept similarity functions need to be able to deal with the high expressive power of the ontology representation language, and to convey the underlying semantics of the ontology to which concepts refer. We propose a semantic similarity measure for complex Description Logics concept descriptions that elicits the underlying ontology semantics. Furthermore, we theorize a set of criteria that a measure has to satisfy in order to be compliant with a semantic expected behavior.KeywordsDescription LogicDissimilarity MeasureEquivalence SoundnessConcept DescriptionPrimitive ConceptThese 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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