Handbook of computational geometry
Handbook of computational geometry
Proceedings of the 17th International Conference on Data Engineering
Efficient Progressive Skyline Computation
Proceedings of the 27th International Conference on Very Large Data Bases
Geometric transforms for fast geometric algorithms
Geometric transforms for fast geometric algorithms
Progressive skyline computation in database systems
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
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
Tentative Prune-And-Search For Computing Fixed-Points With Applications To Geometric Computation
Fundamenta Informaticae
Optimized skyline queries on road networks using nearest neighbors
Personal and Ubiquitous Computing
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We discuss in this paper a method of finding skyline or non-dominated points in a set P of n points with respect to a set S of m sites. A point pi∈P is non-dominated if and only if for each pj∈P, $j \not= i$, there exists at least one point s∈S that is closer to pi than pj. We reduce this problem of determining non-dominated points to the problem of finding sites that have non-empty cells in an additively weighted Voronoi diagram under convex distance function. The weights of the said Voronoi diagram are derived from the co-ordinates of the points of P and the convex distance function is derived from S. In the 2-dimensional plane, this reduction gives a O((m+n)logm+n logn)-time randomized incremental algorithm to find the non-dominated points.