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One Graph, Multiple Drawings

机译:一幅图,多幅图

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Being able to produce a wide variety of layouts for a same graphs may prove useful when users have no preferred visual encoding for their data. The first contribution of this paper is a enhanced force-directed layout capable of producing different layouts of a same graph. We turn a well known force-directed algorithm (GEM) into a highly parametrizable layout and control it from a genetic algorithm framework. The genetic algorithm allows to efficiently explore the parameter space of this highly parametrisable layout. The search process relies on the capability of the system to evaluate the similarity between two drawings. The second contribution of this paper is a similarity metric used as a fitness function for the genetic algorithm. Its main features are its computational cost and its insensitivity to planar homotheties.
机译:当用户对数据没有首选的视觉编码时,能够为相同的图形生成各种各样的布局可能会很有用。本文的第一个贡献是一种增强的力导向布局,该布局能够生成同一图形的不同布局。我们将众所周知的力导向算法(GEM)转换为高度可参数化的布局,并通过遗传算法框架对其进行控制。遗传算法可以有效地探索这种高度可参数化布局的参数空间。搜索过程依赖于系统评估两个图形之间相似性的能力。本文的第二个贡献是用作遗传算法的适应度函数的相似性度量。它的主要特点是计算量大,对平面相似性不敏感。

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