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Persistent Homology Guided Force-Directed Graph Layouts.
IEEE Transactions on Visualization and Computer Graphics ( IF 4.7 ) Pub Date : 2019-08-20 , DOI: 10.1109/tvcg.2019.2934802
Ashley Suh , Mustafa Hajij , Bei Wang , Carlos Scheidegger , Paul Rosen

Graphs are commonly used to encode relationships among entities, yet their abstractness makes them difficult to analyze. Node-link diagrams are popular for drawing graphs, and force-directed layouts provide a flexible method for node arrangements that use local relationships in an attempt to reveal the global shape of the graph. However, clutter and overlap of unrelated structures can lead to confusing graph visualizations. This paper leverages the persistent homology features of an undirected graph as derived information for interactive manipulation of force-directed layouts. We first discuss how to efficiently extract 0-dimensional persistent homology features from both weighted and unweighted undirected graphs. We then introduce the interactive persistence barcode used to manipulate the force-directed graph layout. In particular, the user adds and removes contracting and repulsing forces generated by the persistent homology features, eventually selecting the set of persistent homology features that most improve the layout. Finally, we demonstrate the utility of our approach across a variety of synthetic and real datasets.

中文翻译:

持久同源性指导的力导向图布局。

图通常用于对实体之间的关系进行编码,但其抽象性使其难以分析。节点链接图通常用于绘制图形,力导向布局为节点布置提供了一种灵活的方法,该方法使用局部关系来尝试显示图形的整体形状。但是,无关结构的混乱和重叠可能导致图形可视化混乱。本文利用无向图的持久同源性特征作为派生信息来进行力导向布局的交互操作。我们首先讨论如何有效地从加权和未加权无向图中提取0维持久性同源特征。然后,我们介绍用于操作力导向图布局的交互式持久性条形码。特别是,用户添加和删除由持久性同源性特征产生的收缩力和排斥力,最终选择最能改善布局的一组持久性同源性特征。最后,我们展示了我们的方法在各种综合和真实数据集中的实用性。
更新日期:2019-11-01
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