Probabilistic Databases for All
Dan Suciu
Abstract
In probabilistic databases the data is uncertain and is modeled by a probability distribution. The central problem in probabilistic databases is query evaluation, which requires performing not only traditional data processing such as joins, projections, unions, but also probabilistic inference in order to compute the probability of each item in the answer. At their core, probabilistic databases are a proposal to integrate logic with probability theory. This paper accompanies a talk given as part of the Gems of PODS series, and describes several results in probabilistic databases, explaining their significance in the broader context of model counting, probabilistic inference, and Statistical Relational Models.
Topics & Concepts
Probabilistic databaseProbabilistic logicComputer scienceProbabilistic relevance modelDatabaseJoinsProbabilistic argumentationInferenceProbabilistic CTLProbability distributionDivergence-from-randomness modelRelational databaseStatistical modelDatabase theoryContext (archaeology)Probabilistic logic networkData miningProbabilistic analysis of algorithmsTheoretical computer scienceArtificial intelligenceMathematicsProgramming languageStatisticsDescription logicBiologyMultimodal logicAutoepistemic logicPaleontologyBayesian Modeling and Causal InferenceData Management and AlgorithmsAdvanced Database Systems and Queries