Title :
Generator-Recognizer Networks: A unified approach to probabilistic databases
Author :
Chen, Ruiwen ; Mao, Yongyi ; Kiringa, Iluju
Author_Institution :
SITE, Univ. of Ottawa, Ottawa, ON, Canada
Abstract :
Under the tuple-level uncertainty paradigm, we introduce a novel graphical model, Generator-Recognizer Network (GRN), as a model for probabilistic databases. The GRN modeling framework extends existing graphical models of probabilistic databases and is capable of representing a much wider range of dependence structures.
Keywords :
statistical databases; uncertainty handling; dependence structures; generator recognizer networks; probabilistic databases; tuple level uncertainty paradigm; Databases; Graphical models; Power measurement; Random variables; Uncertainty;
Conference_Titel :
Data Engineering (ICDE), 2010 IEEE 26th International Conference on
Conference_Location :
Long Beach, CA
Print_ISBN :
978-1-4244-5445-7
Electronic_ISBN :
978-1-4244-5444-0
DOI :
10.1109/ICDE.2010.5447925
