Abstract
Considering the high heterogeneity of the ontologies published on the web, ontology matching is a crucial issue whose aim is to establish links between an entity of a source ontology and one or several entities from a target ontology. Perfectible similarity measures, considered as sources of information, are combined to establish these links. The theory of belief functions is a powerful mathematical tool for combining such uncertain information. In this paper, we introduce a decision process based on a distance measure to identify the best possible matching entities for a given source entity.
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
Preview
Unable to display preview. Download preview PDF.
References
Appriou, A.: Approche Générique de la Gestion de l’Incertain dans les Processus de Fusion Multisenseur. Traitement du Signal 22, 307–319 (2005)
Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Scientific American 284(5), 34–43 (2001)
Besana, P.: A Framework for Combining Ontology and Schema Matchers with Dempster Shafer. In: International Semantic Web Conference. LNCS, vol. 4273, pp. 196–200. Springer, HeidelBerg (2006)
Dempster, A.P.: Upper and Lower Probabilities Induced by a Multivalued Mapping. Annals of Mathematical Statistics 38, 325–339 (1967)
Denoeux, T.: Analysis of Evidence-theoretic Decision Rules for Pattern Classification. Pattern Recognition 30(7), 1095–1107 (1997)
Essaid, A., Martin, A., Smits, G., Ben Yaghlane, B.: Processus de Décision Crédibiliste pour l’Alignement des Ontologies. LFA, Reims, France (2013)
Euzenat, J., Shvaiko, P.: Ontology Matching. Springer (2007)
Jousselme, A.L., Grenier, D., Bossé, E.: A New Distance Between Two Bodies of Evidence. Information Fusion 2, 91–101 (2001)
Martin, A., Quidu, I.: Decision Support with Belief Functions Theory for Seabed Characterization. In: International Conference on Information Fusion, Cologne, Germany (2008)
Nagy, M., Vargas-Vera, M., Motta, E.: DSSIM-Ontology mapping with uncertainty. In: International Semantic Web Conference. LNCS, vol. 4273. Springer, HeidelBerg (2006)
Pan, R., Ding, Z., Yu, Y., Peng, Y.: A bayesian network approach to ontology mapping. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 563–577. Springer, Heidelberg (2005)
Shafer, G.: A Mathematical Theory of Evidence. Princeton University Press (1976)
Smarandache, F., Martin, A., Osswald, C.: Contradiction Measures and Specificity Degrees of Basic Belief Assignments. In: International Conference on Information Fusion, Chicago, USA (2011)
Smets, P.: The Combination of Evidence in the Transferable Belief Model. IEEE Transactions on Pattern Analysis and Machine Intelligence 12(5), 447–458 (1990)
Smets, P.: Decision Making in the TBM: the Necessity of the Pignistic Transformation. International Journal of Approximate Reasonning 38, 133–147 (2005)
Wang, Y., Liu, W., Bell, D.: Combining Uncertain Outputs from Multiple Ontology Matchers. In: Prade, H., Subrahmanian, V.S. (eds.) SUM 2007. LNCS (LNAI), vol. 4772, pp. 201–214. Springer, Heidelberg (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Essaid, A., Martin, A., Smits, G., Ben Yaghlane, B. (2014). Uncertainty in Ontology Matching: A Decision Rule-Based Approach. In: Laurent, A., Strauss, O., Bouchon-Meunier, B., Yager, R.R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2014. Communications in Computer and Information Science, vol 442. Springer, Cham. https://doi.org/10.1007/978-3-319-08795-5_6
Download citation
DOI: https://doi.org/10.1007/978-3-319-08795-5_6
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08794-8
Online ISBN: 978-3-319-08795-5
eBook Packages: Computer ScienceComputer Science (R0)