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Title:
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FEASIBLE UNCERTAIN REASONING FOR MULTI AGENT ONTOLOGY MAPPING |
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Author(s):
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Miklos Nagy , Maria Vargas-vera , Enrico Motta |
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ISBN:
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978-972-8924-62-1 |
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Editors:
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Hans Weghorn and Ajith P. Abraham |
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Year:
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2008 |
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Edition:
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Single |
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Keywords:
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Uncertain reasoning, Multi-agent systems, Semantic Web, Genetic Algorithm |
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Type:
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Full Paper |
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First Page:
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19 |
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Last Page:
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26 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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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. |
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