A Semantic Similarity Measure for Ontology-Based Information

Computing the similarity between data elements is a basic functionality in flexible query answering systems. In the case of complex data definitions, for instance in terms of an ontology, computing the similarity between data elements becomes a non-trivial problem. In this paper, we propose a similarity measure for data described in terms of the DL-lite ontology language. In this measure, we take implicit information contained in the definition of classes and relations into account. In contrast to many other proposals for similarity measures, our proposal does not rely on structural criteria of the definitions involved but is solely based on the logical consequences that can be drawn.