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Creators/Authors contains: "Bao, Zhifeng"

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  1. ; ; ; ; (, ACM International Conference on Management of Data {SIGMOD})
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  2. ; ; ; ; (, ACM Transactions on Intelligent Systems and Technology)
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    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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  3. ; ; ; ; (, Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems)
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