Semantic Similarity in a Taxonomy by Refining the Relatedness of Concept Intended Senses

Abstract

In this paper, we present an evolution of a novel approach for evaluating semantic similarity in a taxonomy, based on the well-known notion of information content. Such an approach takes into account not only the generic sense of a concept but also its intended sense in a given context. In this work semantic similarity is evaluated according to a refined relatedness measure between the generic sense and the intended sense of a concept, leading to higher correlation values with human judgment with respect to the original proposal.