TY - JOUR
T1 - Efficient Evaluation of Probabilistic Advanced Spatial Queries on Existentially Uncertain Data
AU - Yiu, Man Lung
AU - Mamoulis, Nikos
AU - Dai, Xiangyuan
AU - Tao, Yufei
AU - Vaitis, Michail
PY - 2009
Y1 - 2009
N2 - 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, nearest neighbors, spatial skylines, and reverse nearest neighbors and conduct an extensive experimental study, which evaluates the effectiveness of proposed solutions.
AB - 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, nearest neighbors, spatial skylines, and reverse nearest neighbors and conduct an extensive experimental study, which evaluates the effectiveness of proposed solutions.
U2 - 10.1109/TKDE.2008.135
DO - 10.1109/TKDE.2008.135
M3 - Journal article
SN - 1041-4347
VL - 21
SP - 108
EP - 122
JO - IEEE Transactions on Knowledge and Data Engineering
JF - IEEE Transactions on Knowledge and Data Engineering
IS - 1
ER -