ProbView: a flexible probabilistic database system
ACM Transactions on Database Systems (TODS)
Supporting valid-time indeterminacy
ACM Transactions on Database Systems (TODS)
Efficient computation of temporal aggregates with range predicates
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Probabilistic temporal databases, I: algebra
ACM Transactions on Database Systems (TODS)
A Parametric Approach to Deductive Databases with Uncertainty
IEEE Transactions on Knowledge and Data Engineering
Reasoning about actions in a probabilistic setting
Eighteenth national conference on Artificial intelligence
Parallel Algorithms for Computing Temporal Aggregates
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Incremental computation and maintenance of temporal aggregates
The VLDB Journal — The International Journal on Very Large Data Bases
Aggregate operators in probabilistic databases
Journal of the ACM (JACM)
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Dyreson and Snodgrass as well as Dekhtyar et. al. have provided a probabilistic model (as well as compelling example applications) for why there may be temporal indeterminacy in databases. In this paper, we first propose a formal model for aggregate computation in such databases when there is uncertainty not just in the temporal attribute, but also in the ordinary (non-temporal) attributes. We identify two types of aggregates: event correlated aggregates, and non event correlated aggregations, and provide efficient algorithms for both of them. We prove that our algorithms are correct, and we present experimental results showing that the algorithms work well in practice.