Further Towards Unambiguous Edge Bundling: Investigating Power-Confluent Drawings for Network Visualization

IF 4.7 1区计算机科学 Q1 COMPUTER SCIENCE, SOFTWARE ENGINEERING

IEEE Transactions on Visualization and Computer Graphics Pub Date : 2018-10-23 DOI:10.1109/TVCG.2019.2944619

Jonathan X. Zheng, S. Pawar, Dan F. M. Goodman

引用次数: 4

Abstract

Bach et al. [1] recently presented an algorithm for constructing confluent drawings, by leveraging power graph decomposition to generate an auxiliary routing graph. We identify two issues with their method which we call the node split and short-circuit problems, and solve both by modifying the routing graph to retain the hierarchical structure of power groups. We also classify the exact type of confluent drawings that the algorithm can produce as ‘power-confluent’, and prove that it is a subclass of the previously studied ‘strict confluent’ drawing. A description and source code of our implementation is also provided, which additionally includes an improved method for power graph construction.

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进一步走向明确的边缘捆绑:研究网络可视化的功率融合图

Bach等人[1]最近提出了一种构建融合图的算法，通过利用幂图分解生成辅助路由图。我们用他们的方法识别了两个问题，我们称之为节点分裂和短路问题，并通过修改路由图来保留功率组的层次结构来解决这两个问题。我们还将算法可以生成的融合图的确切类型归类为“幂融合”，并证明它是先前研究的“严格融合”图的子类。还提供了我们实现的描述和源代码，其中还包括一种改进的幂图构造方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Visualization and Computer Graphics 工程技术-计算机：软件工程

CiteScore

10.40

自引率

19.20%

发文量

946

审稿时长

4.5 months

期刊介绍： TVCG is a scholarly, archival journal published monthly. Its Editorial Board strives to publish papers that present important research results and state-of-the-art seminal papers in computer graphics, visualization, and virtual reality. Specific topics include, but are not limited to: rendering technologies; geometric modeling and processing; shape analysis; graphics hardware; animation and simulation; perception, interaction and user interfaces; haptics; computational photography; high-dynamic range imaging and display; user studies and evaluation; biomedical visualization; volume visualization and graphics; visual analytics for machine learning; topology-based visualization; visual programming and software visualization; visualization in data science; virtual reality, augmented reality and mixed reality; advanced display technology, (e.g., 3D, immersive and multi-modal displays); applications of computer graphics and visualization.