Abstract
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.
Supported by grant HKU 7149/03E from Hong Kong RGC.
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Dai, X., Yiu, M.L., Mamoulis, N., Tao, Y., Vaitis, M. (2005). Probabilistic Spatial Queries on Existentially Uncertain Data. In: Bauzer Medeiros, C., Egenhofer, M.J., Bertino, E. (eds) Advances in Spatial and Temporal Databases. SSTD 2005. Lecture Notes in Computer Science, vol 3633. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11535331_23
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DOI: https://doi.org/10.1007/11535331_23
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