Discovering regular groups of mobile objects using incremental clustering

• Published in: 2008 5th Workshop on Positioning, Navigation and Communication pp. 197 - 205
• Main Authors: Elnekave, S., Last, M., Maimon, O., Ben-Shimol, Y., Einsiedler, H., Friedman, M., Siebert, M.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-03-2008
• Subjects: Clustering; Clustering algorithms; Data mining; Extraterrestrial measurements; Global Positioning System; Humans; Mobile communication; Mobile objects; Navigation; Partitioning algorithms; Spatio-temporal data mining; Time measurement; Vehicles
• ISBN: 9781424417988; 1424417988
• DOI: 10.1109/WPNC.2008.4510375

As technology advances, detailed data on the position of moving objects, such as humans and vehicles is available. In order to discover groups of mobile objects that usually move in similar ways we propose an incremental clustering algorithm that clusters mobile objects according to similarity of their movement patterns. The proposed clustering algorithm uses a new, "data-amount-based" similarity measure between mobile trajectories. The clustering algorithm is evaluated on two spatio-temporal datasets using clustering validity measures.