Feasible uncertain reasoning for multi agent ontology mapping

Nagy, Miklos; Vargas-Vera, Maria and Motta, Enrico (2008). Feasible uncertain reasoning for multi agent ontology mapping. In: IADIS International Conference Informatics 2008, 22-27 Jul 2008, Amsterdam, The Netherlands.

URL: http://iadisportal.org/digital-library


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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