Mining Thick Skylines over Large Databases

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Mining Thick Skylines over Large Databases
Abstract. People recently are interested in a new operator, called skyline [3], which returns the objects that are not dominated by any other objects with regard to certain measures in a multi-dimensional space. Recent work on the skyline operator [3, 15, 8, 13, 2] focuses on efficient computation of skylines in large databases. However, such work gives users only thin skylines, i.e., single objects, which may not be desirable in some real applications. In this paper, we propose a novel concept, called thick skyline, which recommends not only skyline objects but also their nearby neighbors within ε-distance. Efficient computation methods are developed including (1) two efficient algorithms, Sampling-andPruning and Indexing-and-Estimating, to find such thick skyline with the help of statistics or indexes in large databases, and (2) a highly efficient Microcluster-based algorithm for mining thick skyline. The Microclusterbased method not only leads to substantial savings in computation...
Wen Jin, Jiawei Han, Martin Ester
Added 02 Jul 2010
Updated 02 Jul 2010
Type Conference
Year 2004
Where PKDD
Authors Wen Jin, Jiawei Han, Martin Ester
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