基于多层图布局算法的不确定性网络可视化方法

摘要

由于越来越多的数据包含了不确定性,可视化不确定性网络最近几年成为了数据可视化领域中的一个热点.在现有的不确定性可视化研究中,基于概率图布局的方法取得了比较好的效果,通过一种固定采样图算法,可以很好地可视化不确定性网络,并反映出网络中的概率分布情况.针对基于概率图布局的方法存在运行时间过长、图布局不稳定等问题,提出了一种基于多层图布局的方法,改进了多层图布局算法并与固定采样图算法相结合,弥补基于概率图布局的不确定性网络可视化方法的缺陷.实验证明改进之后的算法与原来的方法相比具有更高的时间效率,而且生成的图结构更加稳定.%Visualizing uncertainty networks has become a hot topic in the field of data visualization in recent years, because more and more data contains uncertainties. In the uncertainty visualization research, a method based on the probability graph layout is fairly effective by using an anchoring algorithm to make good visualization of uncertain networks and reflect the probability distribution of the networks. However, the method has two limitations, the high time complexity and unstable layout. To address these issues, we propose an uncertainty network visualization method based on multilevel graph layout algorithm. This method combines the multilevel graph layout algorithm with anchoring algorithm, and improves the limitations of the original method. Experimental results demonstrate that our improved algorithm has higher time efficiency compared with the original method, and the generated graph structure is more stable.