Abstract
An ontology matching system can usually be run with different configurations to optimize the system’s performance, namely precision, recall, or F-measure, depending on the given ontologies to be matched. Changing the configuration has potentially high impact on the obtained matching results. This paper applies particle swarm optimization to automatically tune these configuration parameters through proactively sampling the parameters space and find high-impact parameters and high-performance parameter settings. We show the effectiveness and efficiency of our approach through extensive evaluation on the OAEI 2009 tasks using Lily ontology matching system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Cruz, I.F., Fabiani, A., Caimi, F., Stroe, C., Palmonari, M.: Automatic configuration selection using ontology matching task profiling. In: Simperl, E., Cimiano, P., Polleres, A., Corcho, O., Presutti, V. (eds.) ESWC 2012. LNCS, vol. 7295, pp. 179–194. Springer, Heidelberg (2012)
Kennedy, J., Eberhart, R., et al.: Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks, pp. 1942–1948 (1995)
Wang, P., Xu, B.: Lily: ontology alignment results for OAEI 2008. In: Proceedings of the 3rd International Workshop on Ontology Matching, pp. 167–175 (2008)
Wang, P.: Lily results on SEALS platform for OAEI. In: Proceedings of the 6th International Workshop on Ontology Matching, pp. 156–162 (2011)
Wang, P., Zhou, Y., Xu, B.: Matching large ontologies based on reduction anchors. In: Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI’11), pp. 2343–2348 (2011)
Hicks, C.R., Turner, K.V.: Fundamental concepts in the design of experiments (1999)
Lee, Y., Sayyadian, M., Doan, A., et al.: eTuner: tuning schema matching software using synthetic scenarios. VLDB J. - Int. J. Very Large Data Bases 16(1), 97–122 (2007)
Duan, S., Thummala, V., Babu, S.: Tuning database configuration parameters with iTuned. Proc. VLDB Endowment 2(1), 1246–1257 (2009)
Thummala, V., Babu, S.: iTuned: a tool for configuring and visualizing database parameters. In: Proceedings of the 2010 ACM SIGMOD International Conference on Management of Data, pp. 1231–1234 (2010)
Peukert, E., Eberius, J., Rahm, E.: A self-configuring schema matching system. In: 2012 IEEE 28th International Conference on Data Engineering (ICDE), pp. 306–317 (2012)
Shvaiko, P., Euzenat, J.: Ten challenges for ontology matching. In: Meersman, R., Tari, Z. (eds.) OTM 2008, Part II. LNCS, vol. 5332, pp. 1164–1182. Springer, Heidelberg (2008)
Mochol, M., Jentzsch, A.: Towards a rule-based matcher selection. In: Gangemi, A., Euzenat, J. (eds.) EKAW 2008. LNCS (LNAI), vol. 5268, pp. 109–119. Springer, Heidelberg (2008)
Eckert, K., Meilicke, C., Stuckenschmidt, H.: Improving ontology matching using meta-level learning. In: Aroyo, L., Traverso, P., Ciravegna, F., Cimiano, P., Heath, T., Hyvönen, E., Mizoguchi, R., Oren, E., Sabou, M., Simperl, E. (eds.) ESWC 2009. LNCS, vol. 5554, pp. 158–172. Springer, Heidelberg (2009)
Zhou, Y.: Extensions of an empirical automated tuning framework. Master Thesis. University of Maryland, College Park (2013)
Bock, J., Hettenhausen, J.: Discrete particle swarm optimisation for ontology alignment. Inf. Sci. 192, 152–173 (2012)
Acknowledgments
This work was supported by the National Natural Science Foundation of China (61472077).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yang, P., Wang, P., Ji, L., Chen, X., Huang, K., Yu, B. (2014). Ontology Matching Tuning Based on Particle Swarm Optimization: Preliminary Results. In: Zhao, D., Du, J., Wang, H., Wang, P., Ji, D., Pan, J. (eds) The Semantic Web and Web Science. CSWS 2014. Communications in Computer and Information Science, vol 480. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45495-4_13
Download citation
DOI: https://doi.org/10.1007/978-3-662-45495-4_13
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-45494-7
Online ISBN: 978-3-662-45495-4
eBook Packages: Computer ScienceComputer Science (R0)