Proceedings of the 17th International Conference on Data Engineering
Mining thick skylines over large databases
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
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
Probabilistic skylines on uncertain data
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Efficient computation of reverse skyline queries
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
MOOLAP: Towards Multi-Objective OLAP
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Aggregate Skyline: Analysis for Online Users
SAINT '09 Proceedings of the 2009 Ninth Annual International Symposium on Applications and the Internet
Reverse skyline search in uncertain databases
ACM Transactions on Database Systems (TODS)
Regret-minimizing representative databases
Proceedings of the VLDB Endowment
Ranking uncertain sky: The probabilistic top-k skyline operator
Information Systems
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part II
Measuring the Sky: On Computing Data Cubes via Skylining the Measures
IEEE Transactions on Knowledge and Data Engineering
A survey of skyline processing in highly distributed environments
The VLDB Journal — The International Journal on Very Large Data Bases
Fuzzy dominance skyline queries
DEXA'07 Proceedings of the 18th international conference on Database and Expert Systems Applications
Proceedings of the 21st ACM international conference on Information and knowledge management
SkyView: a user evaluation of the skyline operator
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
| Hi-index | 0.00 |
The skyline operator extracts relevant records from multidimensional databases according to multiple criteria. This operator has received a lot of attention because of its ability to identify the best records in a database without requiring to specify complex parameters like the relative importance of each criterion. However, it has only been defined with respect to single records, while one fundamental functionality of database query languages is aggregation, enabling operations over sets of records. In this paper we introduce aggregate skylines, where the skyline works as a filtering predicate on sets of records. This operator can be used to express queries in the form: return the best groups depending on the features of their elements, and thus provides a powerful combination of grouping and skyline functionality. We define a semantics for aggregate skylines based on a sound theoretical framework and study its computational complexity. We propose efficient algorithms to implement this operator and test them on real and synthetic data, showing that they outperform a direct SQL implementation of up to two orders of magnitude.