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Proceedings Paper

Focus-based filtering + clustering technique for power-law networks with small world phenomenon
Author(s): François Boutin; Jérôme Thièvre; Mountaz Hascoët
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Paper Abstract

Realistic interaction networks usually present two main properties: a power-law degree distribution and a small world behavior. Few nodes are linked to many nodes and adjacent nodes are likely to share common neighbors. Moreover, graph structure usually presents a dense core that is difficult to explore with classical filtering and clustering techniques. In this paper, we propose a new filtering technique accounting for a user-focus. This technique extracts a tree-like graph with also power-law degree distribution and small world behavior. Resulting structure is easily drawn with classical force-directed drawing algorithms. It is also quickly clustered and displayed into a multi-level silhouette tree (MuSi-Tree) from any user-focus. We built a new graph filtering + clustering + drawing API and report a case study.

Paper Details

Date Published: 16 January 2006
PDF: 12 pages
Proc. SPIE 6060, Visualization and Data Analysis 2006, 60600Q (16 January 2006); doi: 10.1117/12.649625
Show Author Affiliations
François Boutin, LIRMM, CNRS (France)
Jérôme Thièvre, INA (France)
Mountaz Hascoët, LIRMM, CNRS (France)


Published in SPIE Proceedings Vol. 6060:
Visualization and Data Analysis 2006
Robert F. Erbacher; Jonathan C. Roberts; Matti T. Gröhn; Katy Börner, Editor(s)

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