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Efficient Processing of the Skyline-CL Query

机译:高效处理Skyline-Cl查询

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摘要

Given a set of k-dimensional objects, the skyline- CL query returns all clusters over skyline objects according to their cardinalities. A naïve 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.
机译:给定一组K维对象,Skyyline-Cl查询根据其基数返回所有群集在天际线对象上。对于此问题的天真解决方案可以分两看:(1)使用现有的天际线查询算法来获取所有天际线对象和(2)利用DBSCAN算法纳入这些天际线对象。然而,实际应用中的效率极低,因为阶段1和2都是CPU敏感的。在本文中,通过上述事实,我们提供了用于高效处理Skyline-Cl查询(AEPSQ)的算法,一种有效的声音和完整算法,用于返回所有天际线集群。在获得地平线对象的过程中,AEPSQ算法将这些物体组织为首次在本文中提出的新型K-ary树Si〜(k)-tree,并且采用了几种有趣的Si〜(k)-tree特性快速生产天际线簇。此外,我们提出了详细的理论分析和广泛的实验,证明了我们的算法既有效又有效。

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