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2012 IEEE 12th International Conference on Data Mining Workshops
Mining Trajectories for Spatio-temporal Analytics
Brussels, Belgium Belgium
December 10-December 10
ISBN: 978-1-4673-5164-5
Mining high resolution trajectories from moving vehicles can provide insightful analytics and enable location based decision making. In this paper, we introduce a trajectory mining prototype system to generate the trajectory heat map at aggregated level for the online spatial-temporal analytics. The proposed method is scalable and efficient since we develop a mechanism using a small subset of trajectory points to capture all trajectory patterns. We experimentally verified the applicability and scalability of this system with large scale real world dataset.
Index Terms:
Trajectory,Heating,Vehicles,Roads,Global Positioning System,Data mining,Scalability,Spatio-temporal analytics,Trajectory mining,Transit point
Citation:
Songhua Xing, Xuan Liu, Qing He, Arun Hampapur, "Mining Trajectories for Spatio-temporal Analytics," icdmw, pp.910-913, 2012 IEEE 12th International Conference on Data Mining Workshops, 2012
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