Approach for instance-based ontology alignment: Using argument and event structures of generative Lexicon

Abstract

Ontology alignment became a very important problem to ensure semantic interoperability for different sources of information heterogeneous and distributed. Instance-based ontology alignment represents a very promising technique to find semantic correspondences between entities of different ontologies when they contain a lot of instances. In this paper, we describe a new approach to manage ontologies that do not share common instances. This approach extracts the argument and event structures from a set of instances of the concept of the source ontology and compared them with other semantic features extracted from a set of instances of the concept of the target ontology using Generative Lexicon Theory. We show that it is theoretically powerful because it is based on linguistic semantics and useful in practice. We present the experimental results obtained by running our approach on Biblio test of Benchmark1 series of OAEI2 2011. The results show the good performance of our approach.