k-dominant Skyline query algorithm for dynamic datasets

Abstract

At present, most k-dominant Skyline query algorithms are oriented to static datasets, this paper proposes a k-dominant Skyline query algorithm for dynamic datasets. The algorithm is recursive circularly. First, we compute the dominant ability of each object and sort objects in descending order by dominant ability. Then, we maintain an inverted index of the dominant index by k-dominant Skyline point calculation algorithm. When the data changes, it is judged whether the update point will affect the k-dominant Skyline point set. So the k-dominant Skyline point of the newdata set is obtained by inserting and deleting algorithm. The proposed algorithm resolves maintenance issue of a frequently updated database by dynamically updating the data sets. The experimental results show that the query algorithm can effectively improve query efficiency.

Keywords

multi-objective decision / Skyline queries / k-dominant Skyline queries / dynamic datasets

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