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(Approximate) Uncertain Skylines

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Given a set of points with uncertain locations, we consider the problem of computing the probability of each point lying on the skyline, that is, the probability that it is not dominated by any other input point. If each point’s uncertainty is described as a probability distribution over a discrete set of locations, we improve the best known exact solution. We also suggest why we believe our solution might be optimal. Next, we describe simple, near-linear time approximation algorithms for computing the probability of each point lying on the skyline. In addition, some of our methods can be adapted to construct data structures that can efficiently determine the probability of a query point lying on the skyline
Original languageEnglish
JournalTheory of Computing Systems
Pages (from-to)342-366
Number of pages25
Publication statusPublished - 2013

    Research areas

  • dat structures, approximation algorithms, computational geometry

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