Abstract
Bio-ontologies are characterized by large sizes, and there is a large number of smaller ontologies derived from them. Determining semantic correspondences across these smaller ones can be based on this “upper” ontology. To this end, we introduce a new fuzzy inference-based ontology matching approach exploiting upper ontologies as semantic bridges in the matching process. The approach comprises two main steps: first, a fuzzy inference-based matching method is used to determine the confidence values in the ontology matching process. To learn the fuzzy system parameters and to enhance the adaptability of fuzzy membership function parameters, we exploit a gradient discriminate learning technique. Second, the achieved results are then composed and combined to derive the final match result. The experimental results show that the performance of the proposed approach compared to one of the famous benchmark research is acceptable.
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References
Algergawy, A., Massmann, S., Rahm, E.: A clustering-based approach for large-scale ontology matching. In: Eder, J., Bielikova, M., Tjoa, A.M. (eds.) ADBIS 2011. LNCS, vol. 6909, pp. 415–428. Springer, Heidelberg (2011)
Algergawy, A., Nayak, R., Siegmund, N., Köppen, V., Saake, G.: Combining schema and level-based matching for web service discovery. In: Benatallah, B., Casati, F., Kappel, G., Rossi, G. (eds.) ICWE 2010. LNCS, vol. 6189, pp. 114–128. Springer, Heidelberg (2010)
Bellahsene, Z., Bonifati, A., Rahm, E.: Schema Matching and Mapping. Springer Verlag (2011)
Castro-Schez, J.J., Murillo, J.M., Miguel, R., Luo, X.: Knowledge acquisition based on learning of maximal structure fuzzy rules. Knowledge-Based Systems 44, 112–120 (2013)
Euzenat, J., Shvaiko, P.: Ontology Matching, 2nd edn. Springer (2013)
Gangemi, A., Guarino, N., Masolo, C., Oltramari, A., Schneider, L.: Sweetening ontologies with DOLCE. In: Gómez-Pérez, A., Benjamins, V.R. (eds.) EKAW 2002. LNCS (LNAI), vol. 2473, p. 166. Springer, Heidelberg (2002)
Hertling, S., Paulheim, H.: WikiMatch - using wikipedia for ontology matching. In: 7th International Workshop on Ontology Matching (2012)
Hung, N.Q.V., Tam, N.T., Mikls, Z., Aberer, K., Gal, A., Weidlich, M.: Pay-as-you-go reconciliation in schema matching networks. In: ICDE (2014)
Hung, N.Q.V., Wijaya, T.K., Mikls, Z., Aberer, K., Levy, E., Shafran, V., Gal, A., Weidlich, M.: Minimizing human effort in reconciling match networks. In: ER 2013, pp. 212–226 (2013)
Jain, P., Yeh, P.Z., Verma, K., Vasquez, R.G., Damova, M., Hitzler, P., Sheth, A.P.: Contextual ontology alignment of LOD with an upper ontology: a case study with proton. In: Antoniou, G., Grobelnik, M., Simperl, E., Parsia, B., Plexousakis, D., De Leenheer, P., Pan, J. (eds.) ESWC 2011, Part I. LNCS, vol. 6643, pp. 80–92. Springer, Heidelberg (2011)
Jimenez-Ruiz, E., Grau, B.C., Zhou, Y., Horrocks, I.: Large-scale interactive ontology matching: algorithms and implementation. In: 20th European Conference on Artificial Intelligence, pp. 444–449 (2012)
Lambrix, P., Tan, H.: SAMBOA system for aligning and merging biomedical ontologies. Web Semantics: Science, Services and Agents on the World Wide Web 4, 196–206 (2006)
Lenat, D.B.: Cyc: a large-scale investment in knowledge infrastructure. Communications of the ACM 38(11), 33–38 (1995)
Li-Quan, Z., Cheng, S.: An adaptive learning method for the generation of fuzzy inference system from data. Acta Automatica Sinica 34(1) (2008)
Mascardi, V., Cord, V., Rosso, P.: A comparison of upper ontologies. WOA 2007, 55–64 (2007)
Mascardi, V., Locoro, A., Rosso, P.: Automatic ontology matching via upper ontologies: A systematic evaluation. IEEE Trans. Knowl. Data Eng. 22(5), 609–623 (2010)
Matos, P., Alcntara, R., Dekker, A., Ennis, M., Hastings, J., Haug, K., Spiteri, I., Turner, S., Steinbeck, C.: Chemical entities of biological interest: an update. Nucleic Acids Res. 38, D249–D254 (2010)
Noy, N.F., Klein, M.: Ontology evolution: Not the same as schema evolution. Knowledge and Information Systems 6, 428–440 (2004)
Rahm, E., Bernstein, P.A.: A survey of approaches to automatic schema matching. VLDB Journal 10(4), 334–350 (2001)
Shvaiko, P., Euzenat, J.: Ontology matching: State of the art and future challenges. IEEE Trans. Knowl. Data Eng. 25(1), 158–176 (2013)
Smith, B., Ashburner, M., Rosse, C., Bard, J., Bug, W., et al.: The OBO foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol 25, 1251–1255 (2007)
Snyman, J.A.: Practical mathematical optimization: an introduction to basic optimization theory and classical and new gradient-based algorithms. Springer (2005)
Stoilos, G., Stamou, G., Kollias, S.D.: A string metric for ontology alignment. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 624–637. Springer, Heidelberg (2005)
The Gene Ontology Consortium: Gene ontology: tool for the unification of biology. Nat. Genet. 25 (2000)
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Davarpanah, S.H., Algergawy, A., Babalou, S. (2015). Fuzzy Inference-Based Ontology Matching Using Upper Ontology. In: Morzy, T., Valduriez, P., Bellatreche, L. (eds) New Trends in Databases and Information Systems. ADBIS 2015. Communications in Computer and Information Science, vol 539. Springer, Cham. https://doi.org/10.1007/978-3-319-23201-0_40
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DOI: https://doi.org/10.1007/978-3-319-23201-0_40
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