Integrating dependency structures of multi Bayesian networks

Bayesian network is a powerful common knowledge representation and reasoning tool for partial beliefs under uncertainty. However, knowledge-based system sometimes must be able to "intelligently" manage a large amount of information coming from different sources and at different moments in time. From the point of view of graph, we suggest a more intuitive algorithm that combines multi Bayesian networks and constructs the dependency structure preserving as much information as possible.