Journal article

Querying Recurrent Convoys over Trajectory Data

ME Yadamjav, Z Bao, B Zheng, FM Choudhury, H Samet

ACM Transactions on Intelligent Systems and Technology | ACM | Published : 2020


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..

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Funding Acknowledgements

This work was partially supported by ARC under Grants DP180102050, and DP200102611, a Google Faculty Research Award, the NSFC grant 91646204, the National Research Foundation, Prime Minister's Office, Singapore under its International Research Centres in Singapore Funding Initiative, and the National Science Foundation of the US under grant IIS-1816889.