Querying Recurrent Convoys over Trajectory Data
AuthorYadamjav, ME; Bao, Z; Zheng, B; Choudhury, FM; Samet, H
Source TitleACM Transactions on Intelligent Systems and Technology
AffiliationComputing and Information Systems
Document TypeJournal Article
CitationsYadamjav, M. E., Bao, Z., Zheng, B., Choudhury, F. M. & Samet, H. (2020). Querying Recurrent Convoys over Trajectory Data. ACM Transactions on Intelligent Systems and Technology, 11 (5), pp.1-24. https://doi.org/10.1145/3400730.
Access StatusAccess this item via the Open Access location
Open Access URLhttps://ink.library.smu.edu.sg/sis_research/5277
ARC Grant codeARC/DP180102050
Moving objects equipped with location-positioning devices continuously generate a large amount of spatio-Temporal trajectory data. An interesting finding over a trajectory stream is a group of objects that are travelling together for a certain period of time. We observe that existing studies on mining co-moving objects do not consider an important correlation between co-moving objects, which is the reoccurrence of the co-moving pattern. In this study, we propose the problem of finding recurrent co-moving patterns from streaming trajectories, enabling us to discover recent co-moving patterns that are repeated within a given time period. Experimental results on real-life trajectory data verify the efficiency and effectiveness of our method.
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