K-dominance in multidimensional data: Theory and applications

被引：3
|
作者：
Schibler, Thomas [1 ]
Suri, Subhash [1 ]
机构：
[1] Univ Calif Santa Barbara, Dept Comp Sci, Santa Barbara, CA 93106 USA
来源：
COMPUTATIONAL GEOMETRY-THEORY AND APPLICATIONS | 2020年 / 87卷 / 87期
基金：
美国国家科学基金会;
关键词：
Dominance; Multi-dimensional data; Skylines; Average case analysis; SKYLINE CARDINALITY; AVERAGE NUMBER; MAXIMA; SET; VECTORS;
D O I：
10.1016/j.comgeo.2019.101594
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
We study the problem of k-dominance in a set of d-dimensional vectors, prove bounds on the number of maxima (skyline vectors), under both worst-case and average-case models, perform experimental evaluation using synthetic and real-world data, and explore an application of k-dominant skyline for extracting a small set of top-ranked vectors in high dimensions where the full skylines can be unmanageably large. (C) 2019 Elsevier B.V. All rights reserved.
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页数：11
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