Graph Drawing in Motion II

Friedrich, Carsten and Houle, Michael E. (2002) Graph Drawing in Motion II. In: Graph Drawing 9th International Symposium, GD 2001, September 23-26, 2001, Vienna, Austria , pp. 220-231 (Official URL:

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Enabling the user of a graph drawing system to preserve the mental map between two different layouts of a graph is a major problem. Whenever a layout in a graph drawing system is modified, the mental map of the user must be preserved. One way in which the user can be helped in understanding a change of layout is through animation of the change. In this paper, we present clustering-based strategies for identifying groups of nodes sharing a common, simple motion from initial layout to final layout. Transformation of these groups is then handled separately in order to generate a smooth animation.

Item Type:Conference Paper
Additional Information:10.1007/3-540-45848-4_18
Classifications:G Algorithms and Complexity > G.999 Others
G Algorithms and Complexity > G.350 Clusters
M Methods > M.200 Animation
ID Code:512

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M.S. Aldenderfer and R.K. Blashfield. Cluster analysis. Sage Publications, Beverly Hills, USA, 1984.

G. Di Battista, P. Eades, R. Tamassia, and I. G. Tollis. Graph Drawing: Algorithms for the Visualization of Graphs. Prentice-Hall, New Jersey, 1999.

F. Bertault. A force-directed algorithm that preserves edge-crossing properties. Information Processing Letters, 74(1-2):7-13, 2000.

Mark de Berg, Marc van Kreveld, and Mark Overmars. Computational Geometry: Algorithms and Applications, chapter 9, pages 188-200. Springer Verlag, 2nd edition, 1998.

C. Friedrich. The ffGraph library. Technical Report 9520, Universität Passau, Dezember 1995.

C. Friedrich and P. Eades. The Marey graph animation tool demo. In Joe Marks, editor, Graph Drawing '00, volume

1984 of Lecture Notes in Computer Science, pages 396-406. Springer-Verlag, 2001.

C. Friedrich and P. Eades. Graph drawing in motion. Submitted to Journal of Graph Algorithms and Applications, 2001.

R.P. Haining. Spatial data analysis in the social and enviromental sciences. Cambridge University Press, UK, 1990. The AGD-Algorithms Library User Manual Version 1.1.2. Max-Planck Institut für Informatik.

M. Huang and P. Eades. A fully animated interactive system for clustering and navigating huge graphs. In Sue H. Whitesides, editor, Graph Drawing '98, volume 1547 of Lecture Notes in Computer Science, pages 374-383, Montreal, Canada, 1999. Springer-Verlag.

L. Kaufmann and P.J. Rousseeuw. Finding groups in data: An introduction to cluster analysis. John Wiley & Sons, NY, USA, 1990.

J. MacQueen. Some methods for classification and analysis of multivariate observations. In L. Le Cam, and J. Neyman, editor, 5th Berkley Symposium on Mathematical Statistics and Probability, pages 281-297, 1967.

G.A. Miller. The magical number seven, plus or minus two: some limits on our capacity for processing information. The Psychological Review, pages 63:81-97, 1956.

U. Fayyad, P.S. Bradley, and C. Reina. Scaling clustering algorithms to large databases. In R. Agrawal and P. Stolorz, editor, Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, pages 9-15, 1998.

C. Reina, U. Fayyad, and P.S. Bradley. Initialization of iterative refinement clustering algorithms. In R. Agrawal and P. Stolorz, editor, Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, pages 194-198, 1998.