Proceedings of the 17th International Conference on Data Engineering
Efficient Progressive Skyline Computation
Proceedings of the 27th International Conference on Very Large Data Bases
Preference formulas in relational queries
ACM Transactions on Database Systems (TODS)
Progressive skyline computation in database systems
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
Optimization of relational preference queries
ADC '05 Proceedings of the 16th Australasian database conference - Volume 39
Efficient computation of the skyline cube
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Catching the best views of skyline: a semantic approach based on decisive subspaces
VLDB '05 Proceedings of the 31st international conference on Very large data bases
SUBSKY: Efficient Computation of Skylines in Subspaces
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Progressive skylining over web-accessible databases
Data & Knowledge Engineering
Towards multidimensional subspace skyline analysis
ACM Transactions on Database Systems (TODS)
Foundations of preferences in database systems
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Preference SQL: design, implementation, experiences
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
Telescope: zooming to interesting skylines
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Evaluating top-k skyline queries over relational databases
DEXA'07 Proceedings of the 18th international conference on Database and Expert Systems Applications
Semi-skyline optimization of constrained skyline queries
ADC '11 Proceedings of the Twenty-Second Australasian Database Conference - Volume 115
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There is a strong demand for a deep personalization of search systems for many Internet applications. In this respect the proper handling of user preferences plays an important role. Here we focus on the efficient evaluation of the Pareto preference operator for structured data in very large databases. The result set of such a Pareto query, also known as the “skyline”, tends to become very large for higher dimensionalities. Often it is too time-consuming or just not necessary to compute the entire skyline, instead only some fraction of it, called a “snippet”, is sufficient. In this paper we contribute a novel algorithm for a fast computation of such skyline snippets. Our solutions do not rely on the availability of specialized pre-computed indexes, hence are generally applicable. We demonstrate the performance of our approach by several benchmarks studies. The presented results suggest that even for complex Pareto queries, yielding very large skylines, snippets can be computed sufficiently fast, and therefore can be integrated into online Web services.