%0 Conference Paper %1 owlSim %A Euzenat, J. %A Valtchev, P. %B Proceedings of the 16th European Conference on Artificial Intelligence (ECAI-04) %D 2004 %E de Mántaras, R. López %E Saitta, L. %I IOS Press %K alignment matching owl semantic_web %P 333-337 %T Similarity-based Ontology Alignment in OWL-Lite %X Interoperability of heterogeneous systems on the Web will be admittedly achieved through an agreement between the un- derlying 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 align- ment 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 compar- ison principle: Similarity depends on the type of entity and involves all the features that make its deinition (such as superclasses, proper- ties, instances, etc.). One-to-many relationships and circularity in entity descriptions constitute the key dificulties in this context: These are dealt with through local matching of entity sets and iterative computation of recursively dependent similarities, respectively.

@inproceedings{owlSim, abstract = {Interoperability of heterogeneous systems on the Web will be admittedly achieved through an agreement between the un- derlying 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 align- ment 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 compar- ison principle: Similarity depends on the type of entity and involves all the features that make its deinition (such as superclasses, proper- ties, instances, etc.). One-to-many relationships and circularity in entity descriptions constitute the key dificulties in this context: These are dealt with through local matching of entity sets and iterative computation of recursively dependent similarities, respectively.}, added-at = {2007-03-24T13:15:49.000+0100}, author = {Euzenat, J. and Valtchev, P.}, biburl = {https://www.bibsonomy.org/bibtex/24bd0112fd8bdc6e98576ef12a9384245/mkaiser30}, booktitle = {Proceedings of the 16th European Conference on Artificial Intelligence (ECAI-04)}, description = {My Main bibliography file}, editor = {de M\'{a}ntaras, R. L\'{o}pez and Saitta, L.}, interhash = {a4a689514b6e17348567007131f4495b}, intrahash = {4bd0112fd8bdc6e98576ef12a9384245}, keywords = {alignment matching owl semantic_web}, pages = {333-337}, publisher = {IOS Press}, timestamp = {2007-03-24T13:15:49.000+0100}, title = {Similarity-based Ontology Alignment in OWL-Lite}, year = 2004 }