Group skyline computation
Group skyline computation
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DOI：
10.1016/j.ins.2011.11.014
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发表时间：
2012-04
期刊：
影响因子：
--
通讯作者：
Hyeonseung Im;Sungwoo Park
中科院分区：
文献类型：
--
作者：
Hyeonseung Im;Sungwoo Park
给定一个多维元组数据集，skyline计算返回一个元组子集，当所有维度一起考虑时，该元组子集不受任何其他元组支配。然而，传统的skyline计算不足以回答各种查询，这些查询不仅需要分析数据集的单个元组，还需要分析它们的组合。本文研究了基于相同元组数的群之间的支配关系的群天际线计算。它通过比较两个组之间的聚合值（例如单个维度元素的总和或平均值）来确定它们之间的支配关系，并确定一组不受任何其他组支配的天际线组。我们研究了群组天际线计算的性质，并提出了一个群组天际线算法GDynamic，它等价于一个动态填充天际线群组表的算法。实验结果表明，GDynamic是一种实用的群组天际线算法.
Given a multi-dimensional dataset of tuples, skyline computation returns a subset of tuples that are not dominated by any other tuples when all dimensions are considered together. Conventional skyline computation, however, is inadequate to answer various queries that need to analyze not just individual tuples of a dataset but also their combinations. In this paper, we study group skyline computation which is based on the notion of dominance relation between groups of the same number of tuples. It determines the dominance relation between two groups by comparing their aggregate values such as sums or averages of elements of individual dimensions, and identifies a set of skyline groups that are not dominated by any other groups. We investigate properties of group skyline computation and develop a group skyline algorithm GDynamic which is equivalent to a dynamic algorithm that fills a table of skyline groups. Experimental results show that GDynamic is a practical group skyline algorithm.