Selecting Stars: The k Most Representative Skyline Operator (2007)
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| Venue: | In Proc. of the Int. IEEE Conf. on Data Engineering (ICDE |
| Citations: | 39 - 1 self |
BibTeX
@INPROCEEDINGS{Lin07selectingstars:,
author = {Xuemin Lin and Yidong Yuan and Qing Zhang and Ying Zhang},
title = {Selecting Stars: The k Most Representative Skyline Operator},
booktitle = {In Proc. of the Int. IEEE Conf. on Data Engineering (ICDE},
year = {2007}
}
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Abstract
Skyline computation has many applications including multi-criteria decision making. In this paper, we study the problem of selecting k skyline points so that the number of points, which are dominated by at least one of these k skyline points, is maximized. We first present an efficient dynamic programming based exact algorithm in a 2d-space. Then, we show that the problem is NP-hard when the dimensionality is 3 or more and it can be approximately solved by a polynomial time algorithm with the guaranteed approximation ratio 1 − 1 e. To speed-up the computation, an efficient, scalable, index-based randomized algorithm is developed by applying the FM probabilistic counting technique. A comprehensive performance evaluation demonstrates that our randomized technique is very efficient, highly accurate, and scalable. 1.
