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arXiv · 1708.08659

Drawing Big Graphs using Spectral Sparsification

Peter Eades·Quan Nguyen·Seok-Hee Hong
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Abstract

Spectral sparsification is a general technique developed by Spielman et al. to reduce the number of edges in a graph while retaining its structural properties. We investigate the use of spectral sparsification to produce good visual representations of big graphs. We evaluate spectral sparsification approaches on real-world and synthetic graphs. We show that spectral sparsifiers are more effective than random edge sampling. Our results lead to guidelines for using spectral sparsification in big graph visualization.

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Peter Eades, Quan Nguyen, Seok-Hee Hong. 2017-08-29. Drawing Big Graphs using Spectral Sparsification. https://arxiv.org/abs/1708.08659

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