Abstract
Cellular signaling data is a type of traffic data, which contains rich spatio-temporal information. Rather than studying the trajectories of individuals, we propose a visual analytics methodology to analyze the crowd flows among a geographical network extracted from real-time cellular signaling data. We design a suite of visualization techniques to explore and reveal mobility patterns over the networks of spatiotemporal clustering. The feasibility of our approach was verified on a real real-time cellular signaling dataset in one week.
Published Version
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