Proceedings of the International Conference on Artificial Intelligence
BayesOWL: A Prototype System for Uncertainty in Semantic Web
July 1, 2009
Previously we have proposed a theoretical framework, called BayesOWL, to model uncertainty in semantic web ontologies based on Bayesian networks. In particular, we have developed a set of rules and algorithms to translate an OWL taxonomy into a BN. In this paper, we describe our implementation of BayesOWL framework together with examples of its use.
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