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 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.