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Matrix view of graphs and direct manipulation of cluster hierarchies

Published: 25 November 2003 Publication History

Abstract

This paper describes VisAdj, a tool for visualizing graphs as adjacency matrices. Although unfamiliar, this technique displays each link without occlusion and lends itself well to direct manipulation. Row and column permutations are a necessary step towards revealing the underlying structure of a graph. Since individual manipulation of vertices would take too much time in large graphs, VisAdj makes it possible to compute cluster hierarchies and manipulate them interactively. Aggregated views of the graphs can be accessed through these clusters and provide better understanding of their structure.

References

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1. Barlow, T. and Neville, P. A Comparison of 2-D Visualisations of Hierarchies. IEEE Symposium on Information Visualization 2001 (Infovis'2001), 22-23 October 2001, San Diego, CA, USA. IEEE Computer Society, pp. 131-138.
[2]
2. Berkhin, P. Survey of Clustering Data Mining Techniques . Accrue Software, Inc. San Jose, CA, 2002.
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3. Bertin, J. Sémiologie graphique : Les diagrammes - Les réseaux - Les cartes. 1967. Editions de l'EHESS 1998.
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4. Carpendale, M. S. T. and Montagnese, C. A framework for unifying presentation space. Proceedings of the 14th annual ACM symposium on User interface software and technology November 2001, ACM Press, pp. 61-70.
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5. Fekete, J.-D. and Plaisant, C. Excentric Labeling: Dynamic Neighborhood Labeling for Data Visualization . Proceedings of the International Conference on Human Factors in Computing Systems (CHI 99), pp. 512-519. Ed. Kate Ehrlich and William Newman, ACM mai 1999.

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IHM '03: Proceedings of the 15th Conference on l'Interaction Homme-Machine
November 2003
313 pages
ISBN:1581138032
DOI:10.1145/1063669
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • AFIHM: Ass. Francophone d'Interaction Homme-Machine

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 November 2003

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Author Tags

  1. adjacency matrix
  2. aggregation
  3. clustering
  4. graphs
  5. networks vgraphs
  6. visualization

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Overall Acceptance Rate 103 of 199 submissions, 52%

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