New data structures for orthogonal range queries
SIAM Journal on Computing
Computational geometry: an introduction
Computational geometry: an introduction
Optimal point location in a monotone subdivision
SIAM Journal on Computing
Randomized algorithms
On Finding the Maxima of a Set of Vectors
Journal of the ACM (JACM)
Multidimensional binary search trees used for associative searching
Communications of the ACM
Proceedings of the 17th International Conference on Data Engineering
Efficient Progressive Skyline Computation
Proceedings of the 27th International Conference on Very Large Data Bases
An optimal and progressive algorithm for skyline queries
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Evaluating probabilistic queries over imprecise data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Indexing multi-dimensional uncertain data with arbitrary probability density functions
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Finding k-dominant skylines in high dimensional space
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Approximately dominating representatives
Theoretical Computer Science
Efficient query evaluation on probabilistic databases
The VLDB Journal — The International Journal on Very Large Data Bases
Shooting stars in the sky: an online algorithm for skyline queries
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Probabilistic skylines on uncertain data
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Computational Geometry: Algorithms and Applications
Computational Geometry: Algorithms and Applications
Monochromatic and bichromatic reverse skyline search over uncertain databases
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Delaunay triangulations of imprecise pointsin linear time after preprocessing
Proceedings of the twenty-fourth annual symposium on Computational geometry
Probabilistic Skyline Operator over Sliding Windows
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Histograms and Wavelets on Probabilistic Data
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Semantics of Ranking Queries for Probabilistic Data and Expected Ranks
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Computing all skyline probabilities for uncertain data
Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Randomized multi-pass streaming skyline algorithms
Proceedings of the VLDB Endowment
A unified approach to ranking in probabilistic databases
Proceedings of the VLDB Endowment
Probabilistic histograms for probabilistic data
Proceedings of the VLDB Endowment
Regret-minimizing representative databases
Proceedings of the VLDB Endowment
Representative skylines using threshold-based preference distributions
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Asymptotically efficient algorithms for skyline probabilities of uncertain data
ACM Transactions on Database Systems (TODS)
Closest pair and the post office problem for stochastic points
WADS'11 Proceedings of the 12th international conference on Algorithms and data structures
Closest pair and the post office problem for stochastic points
Computational Geometry: Theory and Applications
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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.