Proceedings of the 17th International Conference on Data Engineering
Efficient Progressive Skyline Computation
Proceedings of the 27th International Conference on Very Large Data Bases
Progressive skyline computation in database systems
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
Aggregate nearest neighbor queries in spatial databases
ACM Transactions on Database Systems (TODS)
VLDB '06 Proceedings of the 32nd international conference 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
Spatial Skyline Queries: An Efficient Geometric Algorithm
SSTD '09 Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases
Direction-based spatial skylines
Proceedings of the Ninth ACM International Workshop on Data Engineering for Wireless and Mobile Access
MSSQ: manhattan spatial skyline queries
SSTD'11 Proceedings of the 12th international conference on Advances in spatial and temporal databases
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
In-Route skyline querying for location-based services
W2GIS'04 Proceedings of the 4th international conference on Web and Wireless Geographical Information Systems
General spatial skyline operator
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications - Volume Part I
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Given a set of points of interest (POIs), the spatial skyline query for a set of locations returns the POIs that are close to all locations. Answering spatial skyline query can find many applications in Geographical Information Systems. In this paper, we consider the problem of spatial skyline query with uncertainty. Two types of uncertainty are investigated. First, location uncertainty arises when query point (user) locations are not known exactly either due to privacy concerns or measurement limitations. Second, error margins can be used to model tolerance to distance measurement errors between POIs and query points. We devise efficient polynomial-time algorithms to address both types of uncertainty, and rigorously prove their correctness.