Competitive learning of network diagram layout

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 wine range of graphs is that they often put an extremely high demand on computational resources. This 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.