A session-based approach for aligning large ontologies

Abstract

There are a number of challenges that need to be addressed when aligning large ontologies. Previous work has pointed out scalability and efficiency of matching techniques, matching with background knowledge, support for matcher selection, combination and tuning, and user involvement as major requirements. In this paper we address these challenges. Our first contribution is an ontology alignment framework that enables solutions to each of the challenges. This is achieved by introducing different kinds of interruptable sessions. The framework allows partial computations for generating mapping suggestions, partial validations of mappings suggestions and use of validation decisions in (re)computation of mapping suggestions and the recommendation of alignment strategies to use. Further, we describe an implemented system providing solutions to each of the challenges and show through experiments the advantages of the session-based approach. © 2013 Springer-Verlag Berlin Heidelberg.