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
Source: 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
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

3
checked on Dec 6, 2017

Page view(s)

57
checked on Dec 10, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.