BayesOWL: A Prototype System for Uncertainty in Semantic Web

Abstract

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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@inproceedings{Zhang2009BayesOWLAP, title={BayesOWL: A Prototype System for Uncertainty in Semantic Web}, author={Shenyong Zhang and Yi Sun and Yun Peng and Xiaopu Wang}, booktitle={IC-AI}, year={2009} }