Efficient Processing of the Skyline-CL Query

Abstract

Given a set of k-dimensional objects, the skyline-CL query returns all clusters over skyline objects according to their cardinalities. A naive solution to this problem can be implemented in two phases: (1) using existing skyline query algorithms to obtain all skyline objects and (2) utilizing the DBSCAN algorithm to cluster these skyline objects. However, it is extremely inefficient in real applications because phases 1 and 2 are all CPU-sensitive. Motivated by the above facts, in this paper, we present Algorithm for Efficient Processing of the Skyline-CL Query (AEPSQ), an efficient sound and complete algorithm for returning all skyline clusters. During the process of obtaining skyline objects, the AEPSQ algorithm organizes these objects as a novel k-ary tree SI(k)-Tree which is first proposed in our paper, and employs several interesting properties of SI(k)-Tree to produce skyline clusters fast. Furthermore, we present detailed theoretical analyses and extensive experiments that demonstrate our algorithm is both efficient and effective.