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
Mining thick skylines over large databases
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
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
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
Maintaining Sliding Window Skylines on Data Streams
IEEE Transactions on Knowledge and Data Engineering
Monitoring Top-k Query inWireless Sensor Networks
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Progressive skylining over web-accessible databases
Data & Knowledge Engineering
Refreshing the sky: the compressed skycube with efficient support for frequent updates
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Finding k-dominant skylines in high dimensional space
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Efficient Skyline and Top-k Retrieval in Subspaces
IEEE Transactions on Knowledge and 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 processing of top-k dominating queries on multi-dimensional data
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
On Skylining with Flexible Dominance Relation
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Estimation of the maximum domination value in multi-dimensional data sets
ADBIS'10 Proceedings of the 14th east European conference on Advances in databases and information systems
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Skyline query has its own advantages and are useful in many multi-criteria decision support applications. But for the rigidity of skyline dominance relationship, the cardinality of skyline result cannot be controlled, either too big or too small to satisfy users' requirements. By relaxing the dominance relationship to k-skyline or general skyline, we propose a unified approach to find a given number of skyline. We call our output of skyline as *** -skyline, in which *** indicates the number of skyline result. Without any user interference such as assigned weights or scoring functions, we are the first to propose a method to tune the cardinality of skyline operator in both directions, to either increase or decrease according to the requirement of user. To tune the cardinality of skyline, we adopt the concept of k-dominate and also we propose a new concept of general skyline. A point p is in general skyline if p is skyline in some subspace. General skyline have their meaning for they are the best at some aspects and are good alternatives to fullspace skyline. Finally, we present two algorithms to compute *** -skyline. Extensive experiments are conducted to examine the effectiveness and efficiency of the proposed algorithms on both synthetic and real data sets.