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The usefulness of Bayesian network technology for expert-systems for diagnosis, prediction, and analysis of complex technical systems has been shown by several examples in the past. Yet, diagnosis systems using Bayesian networks are still not being deployed on an industrial scale. One reason for this is that it is seldom feasible to generate networks for thousands of systems either by manual construction or by learning from data.

Systematic Generation of Bayesian Networks from Systems Specifications