Integrating Multi Dependency Structure of Bayesian Network Based on Generalized Relation Model
Wei Li · 2004
A Bayesian Network is a directed acyclic graph (DAG) with conditional probabilities for each node. 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 times. Based on generalized relation and the conditional independences defined by the Bayesian Network we present an algorithm that integrates multi Bayesian network and construct a large Bayesian Network preserving as much information as possible.