Nagy, Miklos; Vargas-Vera, Maria and Motta, Enrico
(2008).
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| DOI (Digital Object Identifier) Link: | http://dx.doi.org/doi:10.1007/978-3-540-88636-5_78 |
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| Google Scholar: | Look up in Google Scholar |
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.
| Item Type: | Conference Item |
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| Copyright Holders: | 2008 Springer-Verlag Berlin Heidelberg |
| ISSN: | 0302-9743 |
| Academic Unit/Department: | Mathematics, Computing and Technology > Computing Knowledge Media Institute |
| 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: | 04 Dec 2010 07:35 |
| URI: | http://oro.open.ac.uk/id/eprint/23486 |
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