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Sublinear-Time Attraction Force Computation for Large Complex Graph Drawing

机译:大型复杂图形绘图的Sublinear-Time吸引力计算

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Recent works in graph visualization attempt to reduce the runtime of repulsion force computation of force-directed algorithms using sampling, however they fail to reduce the runtime for attraction force computation to sublinear in the number of edges.We present new sublinear-time algorithms for the attraction force computation of force-directed algorithms and integrate them with sublinear-time repulsion force computation.Extensive experiments show that our algorithms, operated as part of a fully sublinear-time force computation framework, compute graph layouts on average 80% faster than existing linear-time force computation algorithm, with surprisingly significantly better quality metrics on edge crossing and shape-based metrics.
机译:近期工程在图形可视化尝试使用采样减少力定向算法的排斥力计算的运行时间,但是它们无法将吸引力计算的运行时间减少到边缘的数量.WE为其呈现了新的Sublinear-Time算法 强制算法的吸引力计算和与乘以时级排斥力计算集成它们。扩展实验表明,我们的算法作为完全级级级别力计算框架的一部分,平均计算图形布局的速度比现有线性快80% -time力计算算法,令人惊讶的是边缘交叉和基于形状的度量的质量指标。

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