Snapshot Visualization of Complex Graphs with Force-Directed Algorithms

Se-Hang Cheong, Yain-Whar Si
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引用次数: 1

Abstract

Force-directed algorithms are widely used for visualizing graphs. However, these algorithms are computationally expensive in producing good quality layouts for complex graphs. The layout quality is largely influenced by execution time and methods' input parameters especially for large complex graphs. The snapshots of visualization generated from these algorithms are useful in presenting the current view or a past state of an information on timeslices. Therefore, researchers often need to make a trade-off between the quality of visualization and the selection of appropriate force-directed algorithms. In this paper, we evaluate the quality of snapshots generated from 7 force-directed algorithms in terms of number of edge crossing and the standard deviations of edge length. Our experimental results showed that KK, FA2 and DH algorithms cannot produce satisfactory visualizations for large graphs within the time limit. KK-MS-DS algorithm can process large and planar graphs but it does not perform well for graphs with low average degrees. KK-MS algorithm produces better visualizations for sparse and non-clustered graphs than KK-MS-DS algorithm.
用力导向算法实现复杂图的快照可视化
力导向算法被广泛用于图形的可视化。然而,这些算法在为复杂图形生成高质量布局时计算成本很高。布局质量在很大程度上受执行时间和方法输入参数的影响,特别是对于大型复杂图形。从这些算法生成的可视化快照对于在时间片上显示信息的当前视图或过去状态非常有用。因此,研究人员经常需要在可视化质量和选择合适的力导向算法之间做出权衡。在本文中,我们从边缘交叉的次数和边缘长度的标准差方面评估了7种力导向算法生成的快照的质量。我们的实验结果表明,KK、FA2和DH算法不能在限定时间内对大图形产生满意的可视化效果。KK-MS-DS算法可以处理大型平面图形,但对于平均度较低的图形处理效果不佳。KK-MS算法对稀疏和非聚类图的可视化效果优于KK-MS- ds算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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