Network Layout Visualization Based on Sammon's Projection

M. Radvanský, M. Kudelka, Z. Horak, V. Snás̃el
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引用次数: 4

Abstract

Visualization is an important part of Network Analysis. It helps to find features of the network that are not easily identifiable. In this paper we present our approach to the visualization of weighted networks based on Sammon's projection. The network may be seen as a set of data points in the space induced by the incidence relation or as a symmetric matrix of vertex distances. We propose several methods for construction of the input for the Sammon's projection and discuss the effect of the particular methods on the final layout. Results are illustrated using several networks in the 2D layout. Presented experiments use the well-known Karate club network and weighted co-authors network based on the DBLP database.
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基于Sammon投影的网络布局可视化
可视化是网络分析的重要组成部分。它有助于发现网络中不易识别的特征。本文提出了一种基于Sammon投影的加权网络可视化方法。网络可以看作是由关联关系引起的空间中的一组数据点,也可以看作是顶点距离的对称矩阵。我们提出了几种构建Sammon投影输入的方法,并讨论了特定方法对最终布局的影响。结果用二维布局中的几个网络来说明。本实验采用了著名的空手道俱乐部网络和基于DBLP数据库的加权合著者网络。
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