Nagy, Miklos; Vargas-Vera, Maria and Motta, Enrico
(2008).
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Abstract
One of the main disadvantages of using Dempster-Shafer theory for uncertain reasoning is the computational complexity of the belief combination. Large number of variables can easily make the applicability unfeasible due to the exponential growth of the problem space. Semantic Web applications like ontology mapping usually exploits different kind of background knowledge in order to augment the available information which increases the number of variables considerably in the reasoning process. Therefore optimalisation is necessary in order to provide a feasible uncertain reasoning for ontology mapping with large number of variables. In this paper we introduce a novel genetic algorithm solution which is based on distributed junction tree optimalisation for a multi agent system.
| Item Type: | Conference Item |
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| Copyright Holders: | 2008 IADIS |
| Extra Information: | IADIS International Conference Informatics 2008
Editors: Hans Weghorn and Ajith P. Abraham ISBN: 978-972-8924-62-1 |
| Keywords: | uncertain reasoning; multi-agent systems; semantic web; genetic algorithm |
| Academic Unit/Department: | Mathematics, Computing and Technology > Computing Knowledge Media Institute |
| Interdisciplinary Research Centre: | Centre for Research in Computing (CRC) |
| Related URLs: | |
| Item ID: | 23493 |
| Depositing User: | Kay Dave |
| Date Deposited: | 18 Nov 2010 10:00 |
| Last Modified: | 05 Dec 2010 05:51 |
| URI: | http://oro.open.ac.uk/id/eprint/23493 |
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