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Title: Incorporating duration information for trajectory classification
Authors: Patel, D. 
Sheng, C.
Hsu, W. 
Lee, M.L. 
Issue Date: 2012
Citation: Patel, D., Sheng, C., Hsu, W., Lee, M.L. (2012). Incorporating duration information for trajectory classification. Proceedings - International Conference on Data Engineering : 1132-1143. ScholarBank@NUS Repository.
Abstract: Trajectory classification has many useful applications. Existing works on trajectory classification do not consider the duration information of trajectory. In this paper, we extract duration-aware features from trajectories to build a classifier. Our method utilizes information theory to obtain regions where the trajectories have similar speeds and directions. Further, trajectories are summarized into a network based on the MDL principle that takes into account the duration difference among trajectories of different classes. A graph traversal is performed on this trajectory network to obtain the top-k covering path rules for each trajectory. Based on the discovered regions and top-k path rules, we build a classifier to predict the class labels of new trajectories. Experiment results on real-world datasets show that the proposed duration-aware classifier can obtain higher classification accuracy than the state-of-the-art trajectory classifier. © 2012 IEEE.
Source Title: Proceedings - International Conference on Data Engineering
ISSN: 10844627
DOI: 10.1109/ICDE.2012.72
Appears in Collections:Staff Publications

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