Computing Concept Relatedness Based on Ontology

Abstract

Concept relatedness is widely used in information retrieval, text classification, semantic extension, and other fields. So measuring the concept relatedness efficiently is an important task. Previous studies rarely distinguish between relatedness and similarity; they usually use a common formula. We suggest that concept relatedness consists of similarity and relevance, which should be computed differently. In this paper, we first give a similarity measure based on path length, taxonomy depth, and different relations between concepts. Then we propose a method to measure the specific association relation besides basic relations. Finally, incorporating both similarity and specific relevance, we get an overall formula of computing concept relatedness. Compared to existing methods, our measure of concept relatedness is more consistent with human judgment. © Springer-Verlag Berlin Heidelberg 2014.