A Fast Multi-level Layout for Social Network Visualization

Xiaolin Du, Yunming Ye, Yueping Li, Ge Song
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Abstract

We describe a fast multi-level layout for visualizing social networks, which can visualize social networks high quality and rapidly. There are two innovations in our fast multi-level layout. Firstly, we proposed a new graph multi-layered compression method based on random walk. The multi-layered compression process groups vertices to form “planet” systems and then abstract these “planet” systems as new vertices to define a new graph and is repeated until the graph size falls below some threshold. And we also proposed a new single level force-directed layout based on sampling. The multi-level layout process can be accelerated based on these two innovations. Finally, we have evaluated our layout on several well-known data sets. The experimental results show that our layout outperforms the state-ofthe-art method.
一个快速多层次布局的社会网络可视化
本文描述了一种快速多层次的社交网络可视化布局,可以实现高质量、快速的社交网络可视化。我们的快速多层次布局有两个创新。首先,我们提出了一种新的基于随机游走的图层压缩方法。多层压缩过程将顶点分组形成“行星”系统,然后将这些“行星”系统抽象为新的顶点来定义新的图形,并重复此过程,直到图形大小低于某个阈值。并提出了一种基于采样的单层力定向布局。通过这两项创新,可以加快多层次布局的进程。最后,我们在几个众所周知的数据集上评估了我们的布局。实验结果表明,我们的布局优于目前最先进的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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