R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Proceedings of the 17th International Conference on Data Engineering
Optimal aggregation algorithms for middleware
Journal of Computer and System Sciences - Special issu on PODS 2001
Stabbing the Sky: Efficient Skyline Computation over Sliding Windows
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Progressive skyline computation in database systems
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
Maximal vector computation in large data sets
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Maintaining Sliding Window Skylines on Data Streams
IEEE Transactions on Knowledge and Data Engineering
Parallel Computation of Skyline Queries
HPCS '07 Proceedings of the 21st International Symposium on High Performance Computing Systems and Applications
Efficient continuous skyline computation
Information Sciences: an International Journal
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
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)
Distance-Based Representative Skyline
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Parallel Skyline Computation on Multicore Architectures
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Computing all skyline probabilities for uncertain data
Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Scalable skyline computation using object-based space partitioning
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Proceedings of the 18th ACM conference on Information and knowledge management
Group-by skyline query processing in relational engines
Proceedings of the 18th ACM conference on Information and knowledge management
Proceedings of the VLDB Endowment
Continuous monitoring of skylines over uncertain data streams
Information Sciences: an International Journal
Parallelizing skyline queries for scalable distribution
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Top-k combinatorial skyline queries
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part II
Highly scalable multiprocessing algorithms for preference-based database retrieval
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part II
TJJE: An efficient algorithm for top-k join on massive data
Information Sciences: an International Journal
Skyline queries on keyword-matched data
Information Sciences: an International Journal
Skyline queries, front and back
ACM SIGMOD Record
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Given a multi-dimensional dataset of tuples, skyline computation returns a subset of tuples that are not dominated by any other tuples when all dimensions are considered together. Conventional skyline computation, however, is inadequate to answer various queries that need to analyze not just individual tuples of a dataset but also their combinations. In this paper, we study group skyline computation which is based on the notion of dominance relation between groups of the same number of tuples. It determines the dominance relation between two groups by comparing their aggregate values such as sums or averages of elements of individual dimensions, and identifies a set of skyline groups that are not dominated by any other groups. We investigate properties of group skyline computation and develop a group skyline algorithm GDynamic which is equivalent to a dynamic algorithm that fills a table of skyline groups. Experimental results show that GDynamic is a practical group skyline algorithm.