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Probabilistic Reasoning in Bayesian Networks: A Relational Database Approach

S. K. Michael Wong5, Dan Wu5 and Cory J. Butz5

(5)  Department of Computer Science, University of Regina, Regina Saskatchewan, Canada, S4S 0A2
Abstract
Probabilistic reasoning in Bayesian networks is normally conducted on a junction tree by repeatedly applying the local propagation whenever new evidence is observed. In this paper, we suggest to treat probabilistic reasoning as database queries. We adapt a method for answering queries in database theory to the setting of probabilistic reasoning in Bayesian networks. We show an effective method for probabilistic reasoning without repeated application of local propagation whenever evidence is observed.

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