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ivga: A fast force-directed method for interactive visualization of complex networks

机译:ivga:一种用于复杂网络交互可视化的快速力导向方法

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Complex networks play a very important role in various fields of science as data structures, which aggregate information about mutual relationships between numerous objects. The structural properties of these large graphs can be scrutinized throughout their interactive visualization. However, visual analysis of complex networks consisting of vertical bar V vertical bar similar to 10(6+) vertices represents a great challenge for nowadays computer systems both from computational and storage perspective. Therefore, the existing graph drawing methods involving greater than O(vertical bar V vertical bar) time and space complexity cannot be regarded as promising tools in the advent of the Big Data era. We present here a new and very fast graph drawing method with O(vertical bar V vertical bar) time and space complexity - ivga (interactive visualization of graphs). We evaluate its usefulness and performance by testing ivga on the large complex networks from the Stanford Large Network Dataset Collection. We demonstrate that ivga allows for very fast interactive visualization of large graphs consisting of up to a few million vertices on a regular laptop what makes it very competitive to other state-of-art graph drawing methods. Particularly, we recommend ivga method for interactive visualization of large non-planar complex networks such as small-world and scale-free social networks. The main concept of ivga can be seriously considered in developing tools for visualization and analysis of really huge networks, with billions of vertices and edges, on Big Data systems. (C) 2016 Elsevier B.V. All rights reserved.
机译:复杂的网络作为数据结构在科学的各个领域中发挥着非常重要的作用,这些数据结构聚集了有关众多对象之间相互关系的信息。可以在整个交互式可视化过程中仔细检查这些大图的结构特性。然而,从计算和存储的角度来看,对于当今的计算机系统来说,由类似于10(6+)个顶点的垂直线V垂直线组成的复杂网络的可视化分析都面临着巨大的挑战。因此,在大数据时代到来之际,现有的涉及大于O(垂直线V垂直线)时间和空间复杂度的图形绘制方法不能被视为有前途的工具。我们在这里提出了一种新的非常快速的图形绘制方法,它具有O(垂直条V垂直条)的时间和空间复杂性-ivga(图形的交互式可视化)。我们通过在斯坦福大型网络数据集集合中的大型复杂网络上测试ivga,评估其有用性和性能。我们证明了ivga可以对大型图形进行非常快速的交互式可视化,而在常规笔记本电脑上,该图形最多可以包含数百万个顶点,这使其与其他最新图形绘制方法相比具有非常大的竞争力。特别是,我们建议使用ivga方法对大型非平面复杂网络(例如小世界和无标度的社交网络)进行交互式可视化。在开发用于可视化和分析大数据系统上具有数十亿个顶点和边缘的巨大网络的工具时,可以认真考虑ivga的主要概念。 (C)2016 Elsevier B.V.保留所有权利。

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