K-Dominant Skyline Computation by Using Sort-Filtering Method

Siddique Md. Anisuzzaman

Morimoto Yasuhiko

Advances in Knoeledge Didcovery and Data Mining, Proceedings

Skyline queries are useful in many applications such as multi-criteria decision making, data mining, and user preference queries. A skyline query returns a set of interesting data objects that are not dominated in all dimensions by any other objects. For a high-dimensional database, sometimes it returns too many data objects to analyze intensively. To reduce the number of returned objects and to find more important and meaningful objects, we consider a problem of k-dominant skyline queries. Given an n-dimensional database, an object p is said to k-dominates another object q if there are (k <= n) dimensions in which p is better than or equal to q. A k-dominant, skyline object is an object that is not k-dominated by any other objects. In contrast, conventional skyline objects are n-dominant objects. We propose an efficient method for computing k-dominant skyline queries. Intensive performance study using real and synthetic datasets demonstrated that our method is efficient and scalable.

k-Dominant Skyline

Domination Power

Sort-Filtering

General works [ 000 ]

eng

Springer-Verlag Berlin

Copyright (c) 2009 Springer

The original publication is available at www.springerlink.com

[ISSN] 0302-9743

[DOI] 10.1007/978-3-642-01307-2_87

[NCID] AA0071599X

[DOI] http://dx.doi.org/10.1007/978-3-642-01307-2_87