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PODS
2008
ACM

Approximating predicates and expressive queries on probabilistic databases

14 years 3 months ago
Approximating predicates and expressive queries on probabilistic databases
We study complexity and approximation of queries in an expressive query language for probabilistic databases. The language studied supports the compositional use of confidence computation. It allows for a wide range of new use cases, such as the computation of conditional probabilities and of selections based on predicates that involve marginal and conditional probabilities. These features have important applications in areas such as data cleaning and the processing of sensor data. We establish techniques for efficiently computing approximate query results and for estimating the error incurred by queries. The central difficulty is due to selection predicates based on approximated values, which may lead to the unreliable selection of tuples. A database may contain certain singularities at which approximation of predicates cannot be achieved; however, the paper presents an algorithm that provides efficient approximation otherwise. Categories and Subject Descriptors H.2.3 [DATABASE MANAG...
Christoph Koch
Added 08 Dec 2009
Updated 08 Dec 2009
Type Conference
Year 2008
Where PODS
Authors Christoph Koch
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