Many real-world networks are globally sparse but locally dense. Typical examples are social networks, biological networks, and information networks. This double structural nature makes it difficult to adopt a homogeneous visualization model that clearly conveys both an overview of the network and the internal structure of its communities at the same time. As a consequence, the use of hybrid visualizations has been proposed. For instance, NodeTrix combines node-link and matrix-based representations (Henry et al. , 2007). In this article we describe ChordLink , a hybrid visualization model that embeds chord diagrams, used to represent dense subgraphs, into a node-link diagram, which shows the global network structure. The visualization makes it possible to interactively highlight the structure of a community while keeping the rest of the layout stable. We discuss the intriguing algorithmic challenges behind the ChordLink model, present a prototype system that implements it, and illustrate case studies on real-world networks.

中文翻译：

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使用 ChordLink 进行混合图形可视化：算法、实验和应用

许多现实世界的网络是全局稀疏但局部密集的。典型的例子是社交网络、生物网络和信息网络。这种双重结构的性质使得采用同质的可视化模型很难同时清楚地传达网络的概述和其社区的内部结构。因此，已经提出使用混合可视化。例如，NodeTrix 结合了节点链接和基于矩阵的表示（Henry 等。, 2007)。在这篇文章中，我们描述ChordLink ，一种混合​​可视化模型，将用于表示密集子图的和弦图嵌入到节点链接图中，显示全局网络结构。可视化可以在保持其余布局稳定的同时，以交互方式突出显示社区的结构。我们讨论了背后有趣的算法挑战ChordLink 模型，展示了一个实现它的原型系统，并举例说明了真实世界网络的案例研究。