Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICDMW.2009.31
Title: FARM: Feature-assisted aggregate route mining in trajectory data
Authors: Kashyap, S.
Roy, S.
Lee, M.L. 
Hsu, W. 
Issue Date: 2009
Citation: Kashyap, S., Roy, S., Lee, M.L., Hsu, W. (2009). FARM: Feature-assisted aggregate route mining in trajectory data. ICDM Workshops 2009 - IEEE International Conference on Data Mining : 604-609. ScholarBank@NUS Repository. https://doi.org/10.1109/ICDMW.2009.31
Abstract: An aggregate route of a set of trajectories is the representative movement direction of the set. Existing solutions address the problem of finding representative routes by finding clusters in the data with minimum intra-cluster deviation and then deriving a simplified trajectory to represent each cluster. However, existing similarity measures for trajectories are not discriminative and are sensitive to noise. This paper presents FARM, a framework for extracting aggregate routes from trajectory data. FARM first transforms the trajectories into a feature space. Next, it applies spectral clustering to find clusters in the feature space. Finally, we find a representative route for each cluster obtained. Experimental studies demonstrate the effectiveness of the proposed method. © 2009 IEEE.
Source Title: ICDM Workshops 2009 - IEEE International Conference on Data Mining
URI: http://scholarbank.nus.edu.sg/handle/10635/40959
ISBN: 9780769539027
DOI: 10.1109/ICDMW.2009.31
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