Cayley图G(s/sub n/,p/sub n/)的数据融合研究

D. Hsu, A. Palumbo
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引用次数: 7

摘要

在本文中,我们研究了一种在Cayley图背景下的排序数据融合方法。我们研究了基于等级组合的Cayley图模型。提出了一种结合加权排名的数据融合方法。信息系统在凯利图中被表示为节点。我们的目标是在这个图中确定一个多样性和性能的度量,以便建立一个通过排名组合优化融合的模型。我们使用对称组S/sub n/的Cayley图中节点之间的肯德尔距离作为性能度量。通过这样做,我们证明了在S/sub / 6/中,两个信息系统融合的权重与抽象空间中融合的性能之间存在二次关系。从这种关系出发,我们提出了一组用于外推对称群S/sub / n/中最优融合权值的函数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A study of data fusion in Cayley graphs G(s/sub n/,p/sub n/)
In this paper, we examine a method for the fusion of ranked data in the context of a Cayley graph. We investigate this Cayley graph model for optimization of fusion by rank combination. We outline a method of data fusion by combination of weighted rankings. Information systems are represented as nodes in a Cayley graph. Our goal is to determine a metric of diversity and performance in this graph in order to build a model for optimizing fusion by rank combination. We use the Kendall distance between nodes in the Cayley graph of the symmetric group S/sub n/ as a measure of performance. In doing so we demonstrate that in S/sub 6/ there is a quadratic relationship between the weights of the fusion of two information systems and the performance of the fusion in our abstract space. From such a relationship we propose a set of functions for extrapolating optimal fusion weights in the symmetric group S/sub n/.
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