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Continuously monitoring top-k uncertain data streams: a probabilistic threshold method
2009
Distributed and parallel databases
Recently, uncertain data processing has become more and more important. Although a significant amount of previous research explores various continuous queries on data streams, continuous queries on uncertain data streams have seldom been investigated. In this paper, we formulate a novel and challenging problem of continuously monitoring top-k uncertain data streams, and propose a probabilistic threshold method. We develop four algorithms systematically: a deterministic exact algorithm, a
doi:10.1007/s10619-009-7043-x
fatcat:ti4uiuns7rgrjensmqgoypmvsi