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.
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References
Euzenat, J., Shvaiko, P.: Ontology Alignment. Springer, Heidelberg (2013)
Ehrig, M.: Ontology Alignment: Bridging the Semantic Gap. Springer (2007)
Schopman, B., Wang, S., Isaac, A., Schlobach, S.: Instance-Based Ontology Alignment by Instance Enrichment. Springer, Vrije Universiteit Amsterdam, Netherlands (2012)
Rahm, E.: Towards large-scale schema and ontology Alignment. ReCALL (2011)
Wang, Z., Zhang, X., Hou, L., Zhao, Y., Li, J., Qi, Y., Tang, J.: Rimom: a dynamic multistrategy ontology alignment framework. OAEI (2010)
Li, J., Tang, J., Li, Y., Luo, Q.: Rimom: a dynamic multistrategy ontology alignment framework. IEEE Trans. Knowl. (2009)
Bouquet, P., Euzenat, J., Franconi, E., Serafini, L., Stamou, G., Tessaris, S.: Specification of a common framework for characterizing alignment (2004)
Maedche, A., Motik, B., Silva, N., Volz, R.: Mafra – A mapping framework for distributed ontologies. In: Gómez-Pérez, A., Benjamins, V.R. (eds.) EKAW 2002. LNCS (LNAI), vol. 2473, pp. 235–250. Springer, Heidelberg (2002)
Doan, A., Madhavan, J., Domingos, P., Halevy, A.: Ontology Alignment: a machine learning approach. Springer, Berlin (2004)
Stumme, G., Maedche, A.: Fca-merge: bottom-up merging of ontologies. In: Proceedings of the 17th International Conference on Artificial Intelligence (IJCAI 2001), Seattle (2001)
Zaiss, K.S.: Instance-based ontology Alignment and the evaluation of Alignment systems. Ph.D. thesis, Heinrich Heine Universität Düsseldorf (2010)
Todorov, K., Geibel, P., Kühnberger, K.-U.: Mining concept similarities for heterogeneous ontologies. In: Perner, P. (ed.) ICDM 2010. LNCS (LNAI), vol. 6171, pp. 86–100. Springer, Heidelberg (2010)
Tellier, I.: Introduction au TALN et à l’ingénierie linguistique (2012)
Pustejovsky, J., Boguraev, B.: Lexical Knowledge Representation and Natural Language Processing. In: Artificial Intelligence (1993)
Tran, Q., Ichise, R., Ho, B.: Cluster-based Similarity Aggregation for Ontology Matching (2011)
Pustejovsky, J.: The Generative Lexicon. MIT Press, Cambridge (1996)
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Khiat, A., Benaissa, M. (2014). Approach for Instance-Based Ontology Alignment: Using Argument and Event Structures of Generative Lexicon. In: Closs, S., Studer, R., Garoufallou, E., Sicilia, MA. (eds) Metadata and Semantics Research. MTSR 2014. Communications in Computer and Information Science, vol 478. Springer, Cham. https://doi.org/10.1007/978-3-319-13674-5_12
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DOI: https://doi.org/10.1007/978-3-319-13674-5_12
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13673-8
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