Scalable Network Visualization
STEPHEN G. EICK, SSS Research;, National Center for Data Mining, University of Illinois
42.1 Introduction
Many problems can be represented as networks and analyzed using network visualization. Unfortunately, however, the sizes of datasets that are easily collected overwhelm existing visualizations. The problem is that network visualizations become visually confusing and cluttered. This chapter defines the concept of visual scalability for networks, illustrates it with three examples, and proposes techniques to increase network visualization scalability.
Many analysis problems involve understanding network data. Familiar examples include monitoring electronic communications, tracking money flows, understanding ...
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