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TrammelGraph: visual graph abstraction for comparison

机译：Trammelgraph：Visual Graph抽象进行比较

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摘要

Network data, represented by graph-based structures, are used in a variety of applications such as social networks and disease complication networks. A crucial task in many applications is graph comparison, with the goal of understanding the structural differences between pairs of graphs. However, traditional graph visualization techniques, node-link diagrams, and adjacency matrices are not intrinsically designed for comparison tasks. In this paper, we present TrammelGraph, a novel visual graph abstraction technique for graph comparison. TrammelGraph uses graph embedding and node alignment methods to create a map-based representation that eliminates visual clutter and thus facilities graph comparison. The design results in a planar graph with a regularly-spaced, crossing-free layout that helps users identify high-level topological information for graph comparison tasks. To evaluate the effectiveness of TrammelGraph, we conducted a controlled user study with 20 participants that compares TrammelGraph with node-link diagrams and adjacency matrices on a variety of common graph comparison tasks. We also conducted an expert interview with a physician using the MIMIC dataset. Both the quantitative and qualitative results from the study and interview highlighted the key strengths of TrammelGraph as a tool for visual graph comparison.
机译：由基于图形的结构表示的网络数据用于各种应用，例如社交网络和疾病并发症网络。许多应用中的一个重要任务是曲线图比较，目标是了解图对的结构差异。但是，传统的图形可视化技术，节点链路图和邻接矩阵没有本质上设计用于比较任务。在本文中，我们呈现了Trammelgraph，一种用于图表比较的新型视觉图形抽象技术。 Trammelgraph使用曲线图嵌入和节点对齐方法来创建基于地图的表示，消除了Visual Clutter和因此设施图比较。该设计导致平面图，具有定期间隔的无横性布局，可帮助用户识别图表比较任务的高级拓扑信息。为了评估Trammelgraph的有效性，我们进行了一个受控用户学习，其中20名与会者将倾斜度与节点链路图和邻接矩阵进行比较各种公共曲线图比较任务。我们还使用模仿数据集与医生进行专家面试。研究和面试的定量和定性结果均突出了Trammelgraph作为视觉图比较的工具的关键优势。

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