Focus-based filtering + clustering technique for power-law networks with small world phenomenon

François Boutin; Jérôme Thièvre; Mountaz Hascoët

doi:10.1117/12.649625

16 January 2006 Focus-based filtering + clustering technique for power-law networks with small world phenomenon

François Boutin, Jérôme Thièvre, Mountaz Hascoët

Proceedings Volume 6060, Visualization and Data Analysis 2006; 60600Q (2006) https://doi.org/10.1117/12.649625
Event: Electronic Imaging 2006, 2006, San Jose, California, United States

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.

Citation Download Citation

François Boutin, Jérôme Thièvre, and Mountaz Hascoët "Focus-based filtering + clustering technique for power-law networks with small world phenomenon", Proc. SPIE 6060, Visualization and Data Analysis 2006, 60600Q (16 January 2006); https://doi.org/10.1117/12.649625

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