Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Optimal decomposition by clique separators
Discrete Mathematics
An Extended Relational Data Model For Probabilistic Reasoning
Journal of Intelligent Information Systems
Hierarchical schemata for relational databases
ACM Transactions on Database Systems (TODS)
Multivalued dependencies and a new normal form for relational databases
ACM Transactions on Database Systems (TODS)
On the Equivalence of Database Models
Journal of the ACM (JACM)
Constructing the Dependency Structure of a Multiagent Probabilistic Network
IEEE Transactions on Knowledge and Data Engineering
Triangulation of Bayesian Networks: A Relational Database Perspective
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
Theory of Relational Databases
Theory of Relational Databases
Lazy propagation in junction trees
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Maximal prime subgraph decomposition of Bayesian networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On the implication problem for probabilistic conditional independency
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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A maximal prime subgraph decomposition junction tree (MPD-JT) is a useful computational structure that facilitates lazy propagation in Bayesian networks (BNs). A graphical method was proposed to construct an MPD-JT from a BN. In this paper, a new method is presented from a relational database (RDB) perspective which sheds light on the semantic meaning of the previously proposed graphical algorithm.