Abstract
Automated ontology mapping approaches often combine similarity measures in order to increase the quality of the proposed mappings. When the mapping process of human experts is modeled with software agents that assess similarities, it can lead to situations where the beliefs in the assessed similarities becomes contradicting. The combination of these contradicting beliefs can easily worsen the mapping precision and recall, which leads to poor performance of any ontology mapping algorithm. Typically mapping algorithms, which use different similarities and combine them into a more reliable and coherent view can easily become unreliable when these contradictions are not managed effectively between the different sources. In this paper we propose a solution based on the fuzzy voting model for managing such situations by introducing trust and voting between software agents that resolve contradicting beliefs in the assessed similarities.
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
Nagy, M., Vargas-Vera, M., Motta, E.: Dssim - managing uncertainty on the semantic web. In: Proceedings of the 2nd International Workshop on Ontology Matching (2007)
Nagy, M., Vargas-Vera, M., Motta, E.: Multi-agent ontology mapping with uncertainty on the semantic web. In: Proceedings of the 3rd IEEE International Conference on Intelligent Computer Communication and Processing (2007)
Baldwin, J.F.: Mass assignment Fundamentals for computing with words. In: L. Ralescu, A. (ed.) IJCAI-WS 1997. LNCS, vol. 1566, pp. 22–44. Springer, Heidelberg (1999)
Lawry, J.: A voting mechanism for fuzzy logic. International Journal of Approximate Reasoning 19, 315–333 (1998)
Richardson, M., Agrawal, R., Domingos, P.: Trust management for the semantic web. In: Proceedings of the 2nd International Semantic Web Conference, pp. 351–368 (2003)
Gil, Y., Ratnakar, V.: Trusting information sources one citizen at a time. In: Proceedings of the 1st International Semantic Web Conference, pp. 162–176 (2002)
Finin, T., Joshi, A.: Agents, turst, and information access on the semantic web. ACM SIGMOD Record, Special section on semantic web and data management 31, 30–35 (2002)
Griffiths, N.: A fuzzy approach to reasoning with trust, distrust and insufficient trust. In: Proceedings of the 10th International Workshop on Cooperative Information Agents, pp. 360–374 (2006)
Rehak, M., Pechoucek, M., Benda, P., Foltyn, L.: Trust in coalition environment: Fuzzy number approach. In: Proceedings of The 4th International Joint Conference on Autonomous Agents and Multi Agent Systems - Workshop Trust in Agent Societies, pp. 119–131 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Nagy, M., Vargas-Vera, M., Motta, E. (2008). Managing Conflicting Beliefs with Fuzzy Trust on the Semantic Web. In: Gelbukh, A., Morales, E.F. (eds) MICAI 2008: Advances in Artificial Intelligence. MICAI 2008. Lecture Notes in Computer Science(), vol 5317. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88636-5_78
Download citation
DOI: https://doi.org/10.1007/978-3-540-88636-5_78
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88635-8
Online ISBN: 978-3-540-88636-5
eBook Packages: Computer ScienceComputer Science (R0)