Increasing representational power and scaling reasoning in probabilistic databases


Increasing numbers of real-world application domains are generating data that is inherently noisy, incomplete, and probabilistic in nature. Statistical analysis and probabilistic inference, widely used in those domains, often introduce additional layers of uncertainty. Examples include sensor data analysis, data integration and information extraction on the… (More)
DOI: 10.1145/1804669.1804671