Maximal Vector Computation in Large Data Sets

By Parke Godfrey, Ryan Shipley, Jarek Gryz. Very Large Data Bases Conference, 2005

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Selecting Stars: The k Most Representative Skyline Operator (2007, background): “full skyline) have been reported in the literature [4, 9, 13, 22, 29, 33].”
Finding k-dominant skylines in high dimensional space (2006, background): “To determine if a point p is k-dominant, property P2 implies that it is not sufficient to use only k-dominant skyline points to compare against p since it is possible for p to be not k-dominant even though it is not k-dominated by any of the k-dominant points.”
Efficient Computation of the Skyline Cube (2005, methodology): “As we do not have the real datasets, we employ the three most popular synthetic benchmark datasets, correlated, independent, and anti-correlated [6], with dimensionality d in the range [4, 10] and cardinality n in the range [100k, 500k] in our experiment study.”
Probabilistic Skylines on Uncertain Data (2007, methodology): “The SFS algorithm was further signiﬁcantly improved by Godfrey et al. [13].”