Abstract
Relation mappings are important for interoperations between heterogeneous ontologies. Several current methods employ string similarity matching or heuristic rules to find them, but often produce low quality results. We propose a novel approach based on best approximations. The core idea is to find least upper bounds and greatest lower bounds of a relation, and then use them to get upper and lower approximations of the relation. These approximations are the relation mappings between ontologies. To discovery the best mappings, we extend the definition of least upper(/greatest lower) bounds as multielement least upper(/greatest lower) bounds, that not only containing separate relations, but also disjunctions or conjunctions of relations and the related concepts. The simplified multielement bounds are also defined to avoid redundancy. An effective algorithm for finding the relation mappings is proposed.
This work was supported in part by the NSFC (60373066, 60425206, 90412003, 60403016), National Grand Fundamental Research 973 Program of China (2002CB312000), National Research Foundation for the Doctoral Program of Higher Education of China (20020286004), Foundation for Excellent Doctoral Dissertation of Southeast University, and Advanced Armament Research Project (51406020105JB8103).
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References
Gruber, T.R.: A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition 5, 199–220 (1993)
Uschold, M., Gruninger, M.: Ontologies: Principles, Methods, and Applications. Knowledge Engineering Review 11, 93–155 (1996)
Kalfoglou, Y., Schorlemmer, M.: Ontology mapping: the state of the art. The Knowledge Engineering Review 18, 1–31 (2003)
Noy, N.F., Musen, M.: The PROMPT suite: interactive tools for ontology merging and mapping. Int. J. Human-Computer Studies 59, 983–1024 (2003)
Doan, A., Madhavan, J., Dhamankar, R., Domingos, P., Halevy, A.: Learning to map ontologies on the semantic web. The VLDB journal 12, 303–319 (2003)
Ehrig, M., Staab, S.: QOM-Quick Ontology Mapping. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 683–697. Springer, Heidelberg (2004)
Vargas-Vera, M., Motta, E.: An Ontology-Driven Similarity Algorithm. Technical Report, kmi-04-16, Knowledge Media Institute, The Open University (2004)
Lu, J.J., Xu, B.W., Kang, D.Z., Li, Y.H., Wang, P.: Approximations of concept based on Multielement Bounds. In: Andersen, K.V., Debenham, J., Wagner, R. (eds.) DEXA 2005. LNCS, vol. 3588, pp. 676–685. Springer, Heidelberg (2005)
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Wang, P., Xu, B., Lu, J., Kang, D., Zhou, J. (2006). Mapping Ontology Relations: An Approach Based on Best Approximations. In: Zhou, X., Li, J., Shen, H.T., Kitsuregawa, M., Zhang, Y. (eds) Frontiers of WWW Research and Development - APWeb 2006. APWeb 2006. Lecture Notes in Computer Science, vol 3841. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11610113_97
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DOI: https://doi.org/10.1007/11610113_97
Publisher Name: Springer, Berlin, Heidelberg
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