Representing Probabilistic Relations in RDF

Probabilistic inference will be of special importance when one needs to know how much we can say with what all we know given new observations. Bayesian Network is a graphical probabilistic model with which one can represent probabilistic relations intuitively and several effective algorithms for inference are developed. This paper reports a now ongoing work in its design stage which provides a vocabulary for representing probabilistic knowledge in a RDF graph which is to be mapped to a Bayesian Network to do inference on it.