Querying continuous recurrent convoys of interest
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. Existing studies on mining co-moving obj...
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sg-smu-ink.sis_research-56742020-01-02T06:18:03Z Querying continuous recurrent convoys of interest YADAMJAV, Munkh-Erdene BAO, Zhifeng CHOUDURY, Farhana Murtaza SAMET, Hanan ZHENG, Baihua 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. Existing studies on mining co-moving objects do not consider an important correlation between co-moving objects, which is the reoccurrence of the movement pattern. In this study, we define a problem of finding recurrent pattern of co-moving objects from streaming trajectories and propose an efficient solution that enables us to discover recent co-moving object patterns repeated within a given time period. Experimental results on a real-life trajectory database show the efficiency of our method. 2019-11-05T08:00:00Z text https://ink.library.smu.edu.sg/sis_research/4671 info:doi/10.1145/3347146.3359083 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Databases and Information Systems |
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Databases and Information Systems YADAMJAV, Munkh-Erdene BAO, Zhifeng CHOUDURY, Farhana Murtaza SAMET, Hanan ZHENG, Baihua Querying continuous recurrent convoys of interest |
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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. Existing studies on mining co-moving objects do not consider an important correlation between co-moving objects, which is the reoccurrence of the movement pattern. In this study, we define a problem of finding recurrent pattern of co-moving objects from streaming trajectories and propose an efficient solution that enables us to discover recent co-moving object patterns repeated within a given time period. Experimental results on a real-life trajectory database show the efficiency of our method. |
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YADAMJAV, Munkh-Erdene BAO, Zhifeng CHOUDURY, Farhana Murtaza SAMET, Hanan ZHENG, Baihua |
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YADAMJAV, Munkh-Erdene BAO, Zhifeng CHOUDURY, Farhana Murtaza SAMET, Hanan ZHENG, Baihua |
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YADAMJAV, Munkh-Erdene |
title |
Querying continuous recurrent convoys of interest |
title_short |
Querying continuous recurrent convoys of interest |
title_full |
Querying continuous recurrent convoys of interest |
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Querying continuous recurrent convoys of interest |
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Querying continuous recurrent convoys of interest |
title_sort |
querying continuous recurrent convoys of interest |
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Institutional Knowledge at Singapore Management University |
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2019 |
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https://ink.library.smu.edu.sg/sis_research/4671 |
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