Abstract
Ontology matching has played a great role in many well-known applications. It can identify the elements corresponding to each other. At present, with the rapid development of ontology applications, domain ontologies became very large in scale. Solving large scale ontology matching problems is beyond the reach of the existing matching methods. To improve this situation a modularization-based approach (called MOM) was proposed in this paper. It tries to decompose a large matching problem into several smaller ones and use a method to reduce the complexity dramatically. Several large and complex ontologies have been chosen and tested to verify this approach. The results show that the MOM method can significantly reduce the time cost while keeping the high matching accuracy.
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Jayant, M., Philip, A.B., Erhard, R.: Generic Schema Matching with Cupid. In: Proceedings of the 27th International Conference on Very Large Data Bases. Morgan Kaufmann Publishers Inc, San Francisco (2001)
Do, H.H., Rahm, E.: COMA - a system for flexible combination of schema matching approaches. In: Proceedings of VLDB 2001, pp. 610–621 (2001)
AnHai, D., Jayant, M., Robin, D., Pedro, D., Alon, H.: Learning to match ontologies on the Semantic Web. The VLDB Journal 12(4), 303–319 (2003)
Sergey, M., Erhard, R., Philip, A.B.: Rondo: a programming platform for generic model management. In: Proceedings of the 2003 ACM SIGMOD international conference on Management of data, San Diego, California. ACM Press, New York (2003)
Giunchiglia, F., Shvaiko, P., Yatskevich, M.: S-match: an algorithm and an implementation of semantic matching. In: Bussler, C.J., Davies, J., Fensel, D., Studer, R. (eds.) ESWS 2004. LNCS, vol. 3053, pp. 61–75. Springer, Heidelberg (2004)
Grau, B.C., Parsia, B., Sirin, E., Kalyanpur, A.: Modularizing OWL Ontologies. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729. Springer, Heidelberg (2005)
Hopcroft, J., Karp, R.: An n5/2 algorithm for maximum matchings in bipartite graphs. SIAM Journal on Computing 2(4), 225–231 (1973)
Maedche, A., Staab, S.: Measuring similarity between ontologies. In: Gómez-Pérez, A., Benjamins, V.R. (eds.) EKAW 2002. LNCS (LNAI), vol. 2473, p. 251. Springer, Heidelberg (2002)
Wang, Z., Wang, Y., Zhang, S., Shen, G., Du, T.: Ontology Pasing Graph-based Mapping: A Parsing Graph-based Algorithm for Ontology Mapping. Journal of Donghua University 23(6) (2006)
Do, H.H., Melnik, S., Rahm, E.: Comparison of schema matching evaluations. In: Proceedings of workshop on Web and Databases (2002)
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Wang, Z., Wang, Y., Zhang, S., Shen, G., Du, T. (2006). Matching Large Scale Ontology Effectively. In: Mizoguchi, R., Shi, Z., Giunchiglia, F. (eds) The Semantic Web – ASWC 2006. ASWC 2006. Lecture Notes in Computer Science, vol 4185. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11836025_10
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DOI: https://doi.org/10.1007/11836025_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-38329-1
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