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Competitive learning of network diagram layout

机译:网络图布局的竞争学习

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For applications which generate diagrammatic representations, automatic layout techniques are a crucial component. Since graph-like network diagrams are among the most commonly used and most important types of diagrammatic displays, layout techniques for graphs have been extensively studied. However a problem with current graph layout methods which are capable of producing satisfactory results for a wide range of graphs is that they often put an extremely high demand on computational resources. The paper introduces a new layout method that consumes only little computational resources and does not need any heavy duty preprocessing. Unlike other declarative layout algorithms, not even the costly repeated evaluation of an objective function is required. The method presented is based on a competitive learning algorithm which is an extension of self organization strategies known from unsupervised neural networks.
机译:对于生成图形表示的应用程序,自动布局技术是重要组件。由于类似图形的网络图是最常用的和最重要类型的图解显示器之一,因此已经广泛研究了图形的布局技术。然而,当前图表布局方法的问题能够为广泛的图表产生令人满意的结果,它们通常对计算资源进行极高的需求。本文介绍了一种新的布局方法,该方法仅消耗几乎没有计算资源,不需要任何重型预处理。与其他声明性布局算法不同,甚至不需要对客观函数的昂贵重复评估。所呈现的方法基于竞争学习算法,该算法是来自无监督神经网络已知的自组织策略的扩展。

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