Self-organizing graphs ― a neural network perspective of graph layout

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25 Citations (Scopus)


The paper presents self-organizing graphs, a novel approach to graph layout based on a competitive learning algorithm. This method is an extension of self-organization strategies known from unsupervised neural networks, namely from Kohonen's self-organizing map. Its main advantage is that it is very flexibly adaptable to arbitrary types of visualization spaces, for it is explicitly parameterized by a metric model of the layout space. Yet the method consumes comparatively little computational resources and does not need any heavy-duty preprocessing. Unlike with other stochastic layout algorithms, not even the costly repeated evaluation of an objective function is required. To our knowledge this is the first connectionist approach to graph layout. The paper presents applications to 2D-layout as well as to 3D-layout and to layout in arbitrary metric spaces, such as networks on spherical surfaces.

Original languageEnglish
Title of host publicationGraph Drawing - 6th International Symposium, GD 1998, Proceedings
EditorsSue H. Whitesides
Number of pages17
ISBN (Print)3540654739, 9783540654735
Publication statusPublished - 1998
Externally publishedYes
EventGraph Drawing 1998 - Montreal, Canada
Duration: 13 Aug 199815 Aug 1998
Conference number: 6th (Proceedings)

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceGraph Drawing 1998
Abbreviated titleGD 1998
Internet address

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