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- W2625601144 abstract "Trajectory clustering is an important method to achieve moving object data mining, multi-sensor information fusion and trajectory knowledge discovery. Sub-trajectory clustering is an important method to extract useful information from a large number of trajectory data in trajectory analysis. In this paper, comparative experiments are made on the time consumption, similarity measure and clustering performance based on the existing sub-trajectory clustering methods. Based on the comparisons, the advantages and disadvantages of different methods are presented and an improved method is proposed for dealing with trajectories with low positioning accuracy and correlating tracklets from asynchronous sensors. Besides, a general framework of trajectory data mining is discussed." @default.
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- W2625601144 date "2017-06-01" @default.
- W2625601144 modified "2023-10-16" @default.
- W2625601144 title "Comparison study of sub-trajectory clustering in data mining" @default.
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- W2625601144 doi "https://doi.org/10.1088/1755-1315/69/1/012143" @default.
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