Approximation algorithms for NP-hard problems
Approximation algorithms for NP-hard problems
Fast linear expected-time alogorithms for computing maxima and convex hulls
SODA '90 Proceedings of the first annual ACM-SIAM symposium on Discrete algorithms
On Finding the Maxima of a Set of Vectors
Journal of the ACM (JACM)
On the Average Number of Maxima in a Set of Vectors and Applications
Journal of the ACM (JACM)
Proceedings of the 17th International Conference on Data Engineering
Efficient Progressive Skyline Computation
Proceedings of the 27th International Conference on Very Large Data Bases
An optimal and progressive algorithm for skyline queries
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Stabbing the Sky: Efficient Skyline Computation over Sliding Windows
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Stratified computation of skylines with partially-ordered domains
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Maximal vector computation in large data sets
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Robust Cardinality and Cost Estimation for Skyline Operator
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Finding k-dominant skylines in high dimensional space
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Algorithms and analyses for maximal vector computation
The VLDB Journal — The International Journal on Very Large Data Bases
Processing relaxed skylines in PDMS using distributed data summaries
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Shooting stars in the sky: an online algorithm for skyline queries
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Probabilistic skylines on uncertain data
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Efficient skyline computation over low-cardinality domains
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Approaching the skyline in Z order
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Angle-based space partitioning for efficient parallel skyline computation
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Efficient sort-based skyline evaluation
ACM Transactions on Database Systems (TODS)
Efficient skyline querying with variable user preferences on nominal attributes
Proceedings of the VLDB Endowment
Personalized top-k skyline queries in high-dimensional space
Information Systems
Parallel Skyline Computation on Multicore Architectures
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Scalable skyline computation using object-based space partitioning
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
SkyTree: scalable skyline computation for sensor data
Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data
BSkyTree: scalable skyline computation using a balanced pivot selection
Proceedings of the 13th International Conference on Extending Database Technology
Efficient computation of trade-off skylines
Proceedings of the 13th International Conference on Extending Database Technology
Telescope: zooming to interesting skylines
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
Z-SKY: an efficient skyline query processing framework based on Z-order
The VLDB Journal — The International Journal on Very Large Data Bases
Efficient skyline evaluation over partially ordered domains
Proceedings of the VLDB Endowment
ZINC: efficient indexing for skyline computation
Proceedings of the VLDB Endowment
Efficient parallel skyline processing using hyperplane projections
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
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Skyline queries have recently received considerable attention as an alternative decision-making operator in the database community. The conventional skyline algorithms have primarily focused on optimizing the dominance of points in order to remove non-skyline points as efficiently as possible, but have neglected to take into account the incomparability of points in order to bypass unnecessary comparisons. To design a scalable skyline algorithm, we first analyze a cost model that copes with both dominance and incomparability, and develop a novel technique to select a cost-optimal point, called a pivot point, that minimizes the number of comparisons in point-based space partitioning. We then implement the proposed pivot point selection technique in the existing sorting- and partitioning-based algorithms. For point insertions/deletions, we also discuss how to maintain the current skyline using a skytree, derived from recursive point-based space partitioning. Furthermore, we design an efficient greedy algorithm for the k representative skyline using the skytree. Experimental results demonstrate that the proposed algorithms are significantly faster than the state-of-the-art algorithms.