A Combined Fuzzy Semantic Similarity Measure In Owl Ontologies

Abstract

An algorithm is presented in this paper to calculate a semantic similarity measure inside an OWL ontology. The formulation is based on a combined measure taking into account the two most important aspects involved in the similarity computation. These are the structural properties of a concept, and the information content inside the ontology. We define a fuzzy system to blend these information sources with a training process over some ontologies. Finding a similarity measure between concepts of an ontology is a fundamental topic to accomplish information exchange on the Web. Through this measure it is possible to perform sophisticated queries over the web where the user is able to request concepts with a predefined similarity (or even dissimilarity) degree.