Probabilistic Spatial Queries on Existentially Uncertain Data

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We study the problem of answering spatial queries in databases where objects exist with some uncertainty and they are associated with an existential probability. The goal of a thresholding probabilistic spatial query is to retrieve the objects that qualify the spatial predicates with probability that exceeds a threshold. Accordingly, a ranking probabilistic spatial query selects the objects with the highest probabilities to qualify the spatial predicates. We propose adaptations of spatial access methods and search algorithms for probabilistic versions of range queries and nearest neighbors and conduct an extensive experimental study, which evaluates the effectiveness of proposed solutions.

Xiangyuan Dai, Man Lung Yiu, Nikos Mamoulis, Yufei

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Added	28 Jun 2010
Updated	28 Jun 2010
Type	Conference
Year	2005
Where	SSD
Authors	Xiangyuan Dai, Man Lung Yiu, Nikos Mamoulis, Yufei Tao, Michail Vaitis

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Probabilistic Spatial Queries on Existentially Uncertain Data

Probabilistic Spatial Query | Spatial | Spatial Predicates | SSD 2005 |

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