NEAT: Road Network Aware Trajectory Clustering

Mining trajectory data has been gaining significant interest in recent years. However, existing approaches to trajectory clustering are mainly based on density and Euclidean distance measures. The authors argue that when the utility of spatial clustering of mobile object trajectories is targeted at road network aware location based applications, density and Euclidean distance are no longer the effective measures. This is because traffic flows in a road network and the flow-based density characterization become important factors for finding interesting trajectory clusters of mobile objects travelling in road networks. In this paper, they propose NEAT - road network aware approach for fast and effective clustering of spatial trajectories of mobile objects travelling in road networks.

Provided by: Georgia Institute of Technology Topic: Mobility Date Added: Mar 2012 Format: PDF

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