An Efficient Method for Processing Top-n Skyline Queries
Weiwei Bao, Su-Min Jang, Jaesoo Yoo · 2011
The top-n skyline query is to find more interesting n points among skyline results retrieved according to user preference in multiple attributes data. The k-dominant skyline method is a representative one of the top-n skyline query processing methods. The k-dominant skyline includes points that are not dominated by any other points in terms of any k attributes. As the value k is smaller, the k-dominant skyline represents more important and meaningful data. However, the existing top-n skyline query processing method should repeatedly retrieve k-dominant skylines as the value k increases from 1 through n points. Therefore, the existing method is very inefficient. In this paper, we propose a new method that efficiently processes top-n skyline queries using the special relation of the sub-dimensional skyline and the k-dominant skyline. An extensive performance study verifies the merits of our proposed method.