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Fast Graph Drawing Algorithm Revealing Networks Cores

机译:显示网络核心的快速图绘制算法

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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:图是建模元素之间关系的强大工具,已广泛用于不同的研究领域。新获取的图形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。我们对节点链接图感兴趣,该图将每个节点表示为字形,将边缘表示为对应节点之间的线。 %我们提出了一种新颖的布局算法,该算法可以在几秒钟或几分钟内强调超大型网络(多达数十万个节点和数百万个边缘)的核心。我们的方法根据聚类拓扑结构使用图的分层核心分解和现有布局算法的组合。产生节点无重叠图纸的区域感知图纸算法用于减少视觉混乱。沿群集的层次结构将边缘捆绑在一起,以突出显示网络社区并减少边缘的视觉混乱。 %我们通过将我们的方法与最新技术中最快的方法之一进行比较,验证了我们的方法,该方法以从各种来源提取的23张大图为基准。我们已经通过统计证明了我们的方法在提供有意义的结果的同时执行速度更快。

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