Drawing Big Graphs Using Spectral Sparsification

Eades, Peter and Nguyen, Quan and Hong, Seok-Hee (2017) Drawing Big Graphs Using Spectral Sparsification. In: Graph Drawing and Network Visualization. GD 2017, September 25-27 , pp. 272-286(Official URL: https://doi.org/10.1007/978-3-319-73915-1_22).

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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.

Item Type: Conference Paper
Classifications: M Methods > M.400 Force-directed / Energy-based
P Styles > P.720 Straight-line
URI: http://gdea.informatik.uni-koeln.de/id/eprint/1609

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