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Drawing Big Graphs Using Spectral Sparsification
[chapter]
2018
Lecture Notes in Computer Science
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.
doi:10.1007/978-3-319-73915-1_22
fatcat:rp7dtzl4hjczbnhlgt5ojsmgje