Attentiveness assessment in learning based on fuzzy logic analysis
Expert Systems with Applications: An International Journal
Design of an intrusion detection system based on Bayesian networks
WSEAS Transactions on Computers
Sensor selection for active information fusion
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Efficient sensor selection for active information fusion
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
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In a Bayesian network, a probabilistic inference is the procedure of computing the posterior probability of query variables given a collection of evidences. In this paper, we propose an algorithm that efficiently carries out the inferences whose query variables and evidence variables are restricted to a subset of the set of the variables in a BN. The algorithm successfully combines the advantages of two popular inference algorithms 驴 variable elimination and clique tree propagation. We empirically demonstrate its computational efficiency in an affective computing domain.