Voronoï Mobile Cellular Networks: Topological Properties
ISPDC '04 Proceedings of the Third International Symposium on Parallel and Distributed Computing/Third International Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Networks
INFOVIS '05 Proceedings of the Proceedings of the 2005 IEEE Symposium on Information Visualization
Worldmapper: The World as You've Never Seen it Before
IEEE Transactions on Visualization and Computer Graphics
Spatial Analysis of News Sources
IEEE Transactions on Visualization and Computer Graphics
Hotmap: Looking at Geographic Attention
IEEE Transactions on Visualization and Computer Graphics
Legible Cities: Focus-Dependent Multi-Resolution Visualization of Urban Relationships
IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Visualization and Computer Graphics
Digital Footprinting: Uncovering Tourists with User-Generated Content
IEEE Pervasive Computing
Vector field k-means: clustering trajectories by fitting multiple vector fields
EuroVis '13 Proceedings of the 15th Eurographics Conference on Visualization
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The large amount of phone call records from mobile operators in a city can inform us how many people are present in any given area and how many are entering or leaving. Each phone call record usually contains the caller and callee IDs, date and time, and the base station where the phone calls are made. As mobile phones are widely used in our daily life, many human behaviors can be revealed by analyzing mobile phone data. In this paper, we propose a comprehensive visual analysis system which can be used to analyze the population's mobility patterns from millions of phone call records. Our system consists of three major components: 1) visual analysis of user groups in a base station; 2) visual analysis of the mobility patterns on different user groups making phone calls in certain base stations; 3) visual analysis of handoff phone call records. Some well-established visualization techniques such as parallel coordinates and pixel-based representations have been integrated into our system. We also develop a novel visualization schemes, Voronoi-diagram-based visual encoding to reveal the unique features of mobile phone data. We have applied our system to real mobile phone data collected in a large city and obtained some interesting findings regarding people's mobility pattern.