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Fast Graph Drawing Algorithm Revealing Networks Cores

机译:快速图绘图算法揭示网络核心

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Graph is a powerful tool to model relationships between elements and has been widely used in different research areas. Size and complexity of newly acquired graphs prohibit manual representations and urge a need for automatic visualization methods. We are interested with the node-links diagram which represents each node as a glyph and edge as a line between the corresponding nodes. % We present a novel layout algorithm that emphasizes the cores of very large networks (up to several hundred thousand of nodes and million of edges) in few seconds or minutes. Our method uses a hierarchical coreness decomposition of the graph and a combination of existing layout algorithms according to the clusters topologies. Area-aware drawing algorithms which produce node overlap-free drawings are used to reduce the visual clutter. Edges are bundled along the hierarchy of clusters to highlight the network communities and reduce edge visual clutter. % We validated our approach by comparing our method against one of the fastest method of the state of the art on a benchmark of 23 large graphs extracted from various sources. We have statistically proved that our method performs faster while providing meaningful results.
机译:图表是一种强大的工具,可以在不同的研究领域广泛应用于元素之间的关系。新收购图表的大小和复杂性禁止手动表示,并敦促需要自动可视化方法。我们对Node-Links的乐趣图感兴趣,它表示每个节点作为字形和边缘作为相应节点之间的一行。 %我们提出了一种新颖的布局算法,在几秒钟或几分钟内强调了非常大的网络的核心(高达数十万节点和百万的边缘)。我们的方法使用图形的分层验光分解和根据簇拓扑的现有布局算法的组合。产生节点无重叠图形的区域感知绘图算法用于减少视觉杂波。边缘沿集群的层次捆绑在一起,突出显示网络社区并减少边缘视觉杂乱。 %我们通过将我们的方法与从各种来源提取的23个大图的基准测试到最快的方法中的最快方法之一来验证了我们的方法。我们在统计上证明我们的方法在提供有意义的结果时表现更快。

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