论文标题
使用力定向算法对复杂图的快照可视化
Snapshot Visualization of Complex Graphs with Force-Directed Algorithms
论文作者
论文摘要
力定向算法被广泛用于可视化图。但是，这些算法在为复杂图的生成高质量的布局时在计算上昂贵。布局质量在很大程度上受到执行时间和方法的输入参数的影响，尤其是对于大型复杂图。这些算法生成的可视化快照可用于介绍有关时录的当前视图或过去的信息的过去状态。因此，研究人员通常需要在可视化质量和选择适当的力定向算法之间做出权衡。在本文中，我们评估了从7个力定向算法产生的快照的质量，从边缘交叉数和边缘长度的标准偏差表示。我们的实验结果表明，KK，FA2和DH算法无法在时间限制内为大图产生令人满意的可视化。 KK-MS-DS算法可以处理较大的平面图，但对于平均度较低的图形表现不佳。 KK-MS算法比KK-MS-DS算法可为稀疏和非簇图产生更好的可视化。
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.
