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)
An optimal and progressive algorithm for skyline queries
Proceedings of the 2003 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
Shooting stars in the sky: an online algorithm for skyline queries
VLDB '02 Proceedings of the 28th 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
Efficient sort-based skyline evaluation
ACM Transactions on Database Systems (TODS)
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
QSkycube: efficient skycube computation using point-based space partitioning
Proceedings of the VLDB Endowment
SkyMap: a trie-based index structure for high-performance skyline query processing
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part II
Multi-attribute optimization in service selection
World Wide Web
Skyline operator on anti-correlated distributions
Proceedings of the VLDB Endowment
Scalable skyline computation using a balanced pivot selection technique
Information Systems
Toward efficient multidimensional subspace skyline computation
The VLDB Journal — The International Journal on Very Large Data Bases
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Skyline queries have gained a lot of attention for multi-criteria analysis in large-scale datasets. While existing skyline algorithms have focused mostly on exploiting data dominance to achieve efficiency, we propose that data incomparability should be treated as another key factor in optimizing skyline computation. Specifically, to optimize both factors, we first identify common modules shared by existing non-index skyline algorithms, and then analyze them to develop a cost model to guide a balanced pivot point selection. Based on the cost model, we lastly implement our balanced pivot selection in two algorithms, BSkyTree-S and BSkyTree-P, treating both dominance and incomparability as key factors. Our experimental results demonstrate that proposed algorithms outperform state-of-the-art skyline algorithms up to two orders of magnitude.