¹Dept. of Computer Science and Eng.,University of Rajshahi, Rajshahi, Bangladesh
²Graduate School of Eng., Hiroshima University, Higashi-Hiroshima, Japan

---

Abstract—Skyline queries have recently attracted a lot of attention for its intuitive query formulation. It can act as a filter to discard sub-optimal objects. However, a major drawback of skyline is that, in datasets with many dimensions, the number of skyline objects becomes large and no longer offer any interesting insights. To solve the problem, recently k-dominant skyline queries have been introduced, which can reduce the number of skyline objects by relaxing the definition of the dominance. This paper addresses the problem of k-dominant skyline objects for high dimensional dataset. We propose algorithms for k- dominant skyline computation. Our algorithms reduce the pairwise comparison between the k-dominant skyline objects and the dataset. Through extensive experiments with real and synthetic datasets, we confirm that our algorithms can efficiently compute k-dominant skyline queries.

Index Terms—Skyline, k-dominant skyline, domination power, dataset.

[PDF]

Cite: Md. Anisuzzaman Siddique, Yasuhiko Morimoto, "Efficient k-dominant Skyline Computation for High Dimensional Space with Domination Power Index," Journal of Computers vol. 7, no. 3, pp. 608-615, 2012.