  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.
