Similarity-based ontology alignment in OWL-Lite

Euzenat, Jérôme; Valtchev, Petko

by Jérôme Euzenat, Petko Valtchev

Abstract:

Interoperability of heterogeneous systems on the Web will be admittedly achieved through an agreement between the underlying ontologies. However, the richer the ontology description language, the more complex the agreement process, and hence the more sophisticated the required tools. Among current ontology alignment paradigms, similarity-based approaches are both powerful and ﬂexible enough for aligning ontologies expressed in languages like OWL. We deﬁne a universal measure for comparing the entities of two ontologies that is based on a simple and homogeneous comparison principle: Similarity depends on the type of entity and involves all the features that make its deﬁnition (such as superclasses, properties, instances, etc.). One-to-many relationships and circularity in entity descriptions constitute the key difﬁculties in this context: These are dealt with through local matching of entity sets and iterative computation of recursively dependent similarities, respectively.

Reference:

Similarity-based ontology alignment in OWL-Lite (Jérôme Euzenat, Petko Valtchev), In Processing.

Bibtex Entry:

@article{Euzenat,
abstract = {Interoperability of heterogeneous systems on the Web will be admittedly achieved through an agreement between the underlying ontologies. However, the richer the ontology description language, the more complex the agreement process, and hence the more sophisticated the required tools. Among current ontology alignment paradigms, similarity-based approaches are both powerful and ﬂexible enough for aligning ontologies expressed in languages like OWL. We deﬁne a universal measure for comparing the entities of two ontologies that is based on a simple and homogeneous comparison principle: Similarity depends on the type of entity and involves all the features that make its deﬁnition (such as superclasses, properties, instances, etc.). One-to-many relationships and circularity in entity descriptions constitute the key difﬁculties in this context: These are dealt with through local matching of entity sets and iterative computation of recursively dependent similarities, respectively.},
author = {Euzenat, J\'{e}r\^{o}me and Valtchev, Petko},
journal = {Processing},
keywords = {SML-LIB-BIBLIO,lang:ENG},
mendeley-tags = {SML-LIB-BIBLIO,lang:ENG},
title = {{Similarity-based ontology alignment in OWL-Lite}}
}