Several hierarchical clustering techniques have been proposed to visualize large graphs, but fewer solutions suggest a focus based approach. We propose a multilevel clustering technique that produces in linear time a contextual clustered view depending on a user-focus. We get a tree of clusters where each cluster - called meta-silhouette - is itself hierarchically clustered into an inclusion tree of silhouettes. Resulting Multilevel Silhouette Tree (MuSi-Tree) has a specific structure called multilevel compound tree. This work builds upon previous work on a compound tree structure called MO-Tree. The work presented in this paper is a major improvement over previous work by (1) defining multilevel compound tree as a more generic structure, (2) proposing original space-filling visualization techniques to display it, (3) defining relevant interaction model based on both focus changes and graph filtering techniques and (4) reporting from case studies in various fields: co-citation graphs, related-document graphs and social graphs. © IFIP International Federation for Information Processing 2005.
CITATION STYLE
Boutin, F., Thièvre, J., & Hascoët, M. (2005). Multilevel compound tree - Construction visualization and interaction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3585 LNCS, pp. 847–860). https://doi.org/10.1007/11555261_67
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