Nagy, Miklos; Vargas-Vera, Maria and Motta, Enrico
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|DOI (Digital Object Identifier) Link:||http://dx.doi.org/10.1109/ICCP.2008.4648382|
|Google Scholar:||Look up in Google Scholar|
Software agents that assess similarities between concepts on the Semantic Web has to deal with scenarios 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 IEEE|
|Extra Information:||4th International Conference on Intelligent Computer Communication and Processing, 2008. ICCP 2008.
Edited by Ioan Alfred Letia
|Academic Unit/Department:||Mathematics, Computing and Technology > Computing & Communications
Knowledge Media Institute
|Interdisciplinary Research Centre:||Centre for Research in Computing (CRC)|
|Depositing User:||Kay Dave|
|Date Deposited:||17 Nov 2010 10:19|
|Last Modified:||05 Dec 2010 05:39|
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