Abstract
Ontology Alignment is the process of identifying semantic correspondences between their entities. It is proposed to enable semantic interoperability between various knowledge sources that are distributed and heterogeneous. Most existing ontology alignment systems are based on the calculation of similarities and often proceed by their combination. The work presented in this paper consists of an approach denoted PBW (Precision Based Weighting) which estimates the weights to assign to matchers for aggregation. This approach proposes to measure the confidence accorded to a matcher by estimating its precision. The experimental study that we have carried out has been conducted on the Conference track of the evaluation campaign OAEI 2012. We have compared our approach with two methods considered as the most performed in recent years, namely those based on the concepts harmony and local confidence trust respectively. The results show the good performance of our approach. Indeed, it is better in terms of precision, than existing methods with which it has been compared.
Chapter PDF
Similar content being viewed by others
Keywords
References
Bellahsene, Z., Duchateau, F.: Tuning for Schema Matching Schema Matching and Mapping. In: Bellahsene, Z., Bonifati, A., Rahm, E. (eds.) Data-Centric Systems and Applications. Springer (2011)
Cruz, I., Antonelli, F.P., Stroe, C.: Efficient selection of mappings and automatic quality-driven combination of matching methods. In: International Workshop on Ontology Matching (2009)
Do, H., Rahm, E.: COMA - A system for flexible combination of schema matching approaches. In: Proceedings of the 28th VLDB Conference, Hong Kong, China (2002)
Ehrig, M.: Ontology Alignment: Bridging the Semantic Gap. Springer (2007)
Euzénat, J., Shvaiko, P.: Ontology Matching. Springer (2013)
Ichise, R.: Machine learning approach for ontology mapping using multiple concept similarity measures. In: ACIS-ICIS. IEEE Computer Society (2008)
Li, J., Tang, J., Li, Y., Luo, Q.: RiMOM: A Dynamic Multistrategy Ontology Alignment Framework. IEEE Transactions on Knowledge and Data Engineering 21 (2009)
Mao, M., Peng, Y., Spring, M.: A harmony based adaptive ontology mapping approach. In: Proceedings of International Conference on Semantic Web and Web Services, SWWS (2008)
Martinez-Gil, J., Alba, E., Aldana-Montes, J.: Optimizing Ontology Alignments by Using Genetic Algorithms. In: Gueret, C., Hitzler, P., Schlobach, S. (eds.) Nature Inspired Reasoning for the Semantic Web, CEUR Workshop Proceedings (2008)
Ngo, D.: Enhancing Ontology Matching by Using Machine Learning, Graph Matching and Information Retrieval Techniques. Thèse de doctorat de l’université de Grenoble (2012)
Rahm, E.: Towards Large-Scale Schema and Ontology Matching. Schema Matching and Mapping. In: Bellahsene, Z., Bonifati, A., Rahm, E. (eds.) Data-Centric Systems and Applications. Springer (2011)
Silvana, C., Ferrara, A., Montannelli, S., Varese, G.: Ontology and Instance Matching. In: Paliouras, G., Spyropoulos, C.D., Tsatsaronis, G. (eds.) Multimedia Information Extraction. LNCS (LNAI), vol. 6050, pp. 167–195. Springer, Heidelberg (2011)
Wang, J., Ding, Z., Jiang, C.: GAOM: Genetic Algorithm based Ontology Matching. In: Proceedings of IEEE Asia-Pacific Conference on Services Computing (2006)
Wang, R., Wu, J., Liu, L.: Strategies Prediction and Combination of Multi-strategy Ontology Mapping. In: Zhu, R., Zhang, Y., Liu, B., Liu, C. (eds.) ICICA 2010. CCIS, vol. 106, pp. 220–227. Springer, Heidelberg (2010)
(Site 1), http://oaei.ontologymatching.org/2011/results/oaei2011.pdf (accessed January 2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 IFIP International Federation for Information Processing
About this paper
Cite this paper
Benaissa, M., Khiat, A. (2015). A New Approach for Combining the Similarity Values in Ontology Alignment. In: Amine, A., Bellatreche, L., Elberrichi, Z., Neuhold, E., Wrembel, R. (eds) Computer Science and Its Applications. CIIA 2015. IFIP Advances in Information and Communication Technology, vol 456. Springer, Cham. https://doi.org/10.1007/978-3-319-19578-0_28
Download citation
DOI: https://doi.org/10.1007/978-3-319-19578-0_28
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19577-3
Online ISBN: 978-3-319-19578-0
eBook Packages: Computer ScienceComputer Science (R0)