scholarly journals Representation of Bayesian networks as relational databases

Author(s):  
S. K. M. Wong ◽  
Y. Xiang ◽  
X. Nie
Author(s):  
DAN WU ◽  
MICHAEL WONG

Bayesian networks have been well established as an effective framework for uncertainty management using probability. Various methods for probabilistic reasoning in Bayesian networks have been developed and matured. Recently, research has shown that there exists an intriguing relationship between Bayesian networks and relational databases. Adding to that intriguing relationship, in this paper, we reveal that the global propagation method for probabilistic reasoning in Bayesian networks has a close tie with the well known semijoin programs for query answering in relational databases. This linkage between these two apparently different but closely related knowledge representations suggests that well developed techniques for query answering in relational databases could be applied to probabilistic reasoning in Bayesian networks for large and complex domains.


2011 ◽  
Vol 34 (2) ◽  
pp. 291-303 ◽  
Author(s):  
Li YAN ◽  
Zong-Min MA ◽  
Jian LIU ◽  
Fu ZHANG

2009 ◽  
Vol 31 (10) ◽  
pp. 1814-1825 ◽  
Author(s):  
Dong LIU ◽  
Chun-Yuan ZHANG ◽  
Wei-Yan XING ◽  
Rui LI

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