Proceedings of the International Conference on Artificial Intelligence

BayesOWL: A Prototype System for Uncertainty in Semantic Web

Shenyong Zhang, Yi Sun, Yun Peng, and Xiaopu Wang

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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Tags: knowledge representation, semantic web, uncertainty

Type: InProceedings

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