Title :
An algebra for probabilistic databases
Author :
Pittarelli, Michael
Author_Institution :
SUNY Inst. of Technol., Utica, NY, USA
fDate :
4/1/1994 12:00:00 AM
Abstract :
An algebra is presented for a simple probabilistic data model that may be regarded as an extension of the standard relational model. The probabilistic algebra is developed in such a way that (restricted to α-acyclic database schemes) the relational algebra is a homomorphic image of it. Strictly probabilistic results are emphasized. Variations on the basic probabilistic data model are discussed. The algebra is used to explicate a commonly used statistical smoothing procedure and is shown to be potentially very useful for decision support with uncertain information
Keywords :
Bayes methods; Markov processes; algebra; data structures; database management systems; database theory; decision support systems; probability; relational algebra; uncertainty handling; α-acyclic database schemes; Bayes networks; Markov networks; decision support; homomorphic image; probabilistic algebra; probabilistic data model; probabilistic databases; relational algebra; statistical smoothing procedure; uncertain information; Algebra; Data models; Image databases; Image reconstruction; Markov random fields; Power system modeling; Probability; Relational databases; Smoothing methods; Transaction databases;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
