Controllable and Progressive Edge Clustering for Large Networks

Qu, Huamin and Zhou, Hong and Wu, Yingcai (2007) Controllable and Progressive Edge Clustering for Large Networks. In: Graph Drawing 14th International Symposium, GD 2006, September 18-20, 2006, Karlsruhe, Germany , pp. 399-404 (Official URL: http://dx.doi.org/10.1007/978-3-540-70904-6_38).

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Abstract

Node-link diagrams are widely used in information visualization to show relationships among data. However, when the size of data becomes very large, node-link diagrams will become cluttered and visually confusing for users. In this paper, we propose a novel controllable edge clustering method based on Delaunay triangulation to reduce visual clutter for node-link diagrams. Our method uses curves instead of straight lines to represent links and these curves can be grouped together according to their relative positions and directions. We further introduce progressive edge clustering to achieve continuous level-of-details for large networks.

Item Type:Conference Paper
Additional Information:10.1007/978-3-540-70904-6_38
Classifications:P Styles > P.180 Cluster
G Algorithms and Complexity > G.350 Clusters
ID Code:795

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