Anytime approximation in probabilistic databases

Anytime approximation in probabilistic databases This article describes an approximation algorithm for computing the probability of propositional formulas over discrete random variables. It incrementally refines lower and upper bounds on the probability of the formulas until the desired absolute or relative error guarantee is reached. This algorithm is used by the SPROUT query engine to approximate the probabilities of results to relational algebra queries on expressive probabilistic databases. The VLDB Journal Springer Journals

Anytime approximation in probabilistic databases

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Springer Berlin Heidelberg
Copyright © 2013 by Springer-Verlag Berlin Heidelberg
Computer Science; Database Management
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