MLSEB: Edge Bundling Using Moving Least Squares Approximation

Wu, Jieting and Zeng, Jianping and Zhu, Feiyu and Yu, Hongfeng (2017) MLSEB: Edge Bundling Using Moving Least Squares Approximation. In: Graph Drawing and Network Visualization. GD 2017, September 25-27 , pp. 379-393(Official URL: https://doi.org/10.1007/978-3-319-73915-1_30).

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Abstract

Edge bundling methods can effectively alleviate visual clutter and reveal high-level graph structures in large graph visualization. Researchers have devoted significant efforts to improve edge bundling according to different metrics. As the edge bundling family evolve rapidly, the quality of edge bundles receives increasing attention in the literature accordingly. In this paper, we present MLSEB, a novel method to generate edge bundles based on moving least squares (MLS) approximation. In comparison with previous edge bundling methods, we argue that our MLSEB approach can generate better results based on a quantitative metric of quality, and also ensure scalability and the efficiency for visualizing large graphs.

Item Type: Conference Paper
Classifications: P Styles > P.300 Curved
S Software and Systems > S.120 Visualization
URI: http://gdea.informatik.uni-koeln.de/id/eprint/1618

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