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Managing conflicting beliefs with fuzzy trust on the Semantic Web

Nagy, Miklos; Vargas-Vera, Maria and Motta, Enrico (2008). Managing conflicting beliefs with fuzzy trust on the Semantic Web. In: MICAI 2008: Advances in Artificial Intelligence.

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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.

Item Type: Conference Item
Copyright Holders: 2008 Springer-Verlag Berlin Heidelberg
ISSN: 0302-9743
Academic Unit/Department: Knowledge Media Institute
Mathematics, Computing and Technology > Computing & Communications
Mathematics, Computing and Technology
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Item ID: 23486
Depositing User: Kay Dave
Date Deposited: 12 Oct 2010 11:45
Last Modified: 24 Mar 2016 20:27
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