The Community for Technology Leaders
2013 IEEE 29th International Conference on Data Engineering (ICDE) (2010)
Long Beach, CA, USA
Mar. 1, 2010 to Mar. 6, 2010
ISBN: 978-1-4244-5445-7
pp: 145-156
Jiewen Huang , Oxford University Computing Laboratory, OX1 3QD, UK
Christoph Koch , Department of Computer Science, Cornell University, Ithaca, NY 14853, USA
Dan Olteanu , Oxford University Computing Laboratory, OX1 3QD, UK
ABSTRACT
This paper introduces a deterministic approximation algorithm with error guarantees for computing the probability of propositional formulas over discrete random variables. The algorithm is based on an incremental compilation of formulas into decision diagrams using three types of decompositions: Shannon expansion, independence partitioning, and product factorization. With each decomposition step, lower and upper bounds on the probability of the partially compiled formula can be quickly computed and checked against the allowed error.
INDEX TERMS
CITATION
Jiewen Huang, Christoph Koch, Dan Olteanu, "Approximate confidence computation in probabilistic databases", 2013 IEEE 29th International Conference on Data Engineering (ICDE), vol. 00, no. , pp. 145-156, 2010, doi:10.1109/ICDE.2010.5447826
103 ms
(Ver )