Continuously monitoring top-k uncertain data streams: a probabilistic threshold method

Ming Hua, Jian Pei
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
more » ... zed method, and their space-efficient versions using quantile summaries. An extensive empirical study using real data sets and synthetic data sets is reported to verify the effectiveness and the efficiency of our methods.
doi:10.1007/s10619-009-7043-x fatcat:ti4uiuns7rgrjensmqgoypmvsi