A Note on the Evaluation of Inductive Concept Classification Procedures

The limitations of deductive logic-based approaches at deriving operational knowledge from ontologies may be overcome by inductive (instancebased) methods, which are usually efficient and noise-tolerant. However the evaluation of such methods is made particularly difficult by the open-world semantics which may often cause individuals not to be deductively classified by the reasoner. In this paper an evaluation method is proposed that is suitable for comparing inductive classification methods to standard reasoners. Experimentally we show that the behavior of a nearest neighbor classifier is comparable with the one of a standard reasoner in terms of the proposed indices.