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Movement similarity assessment using symbolic representation of trajectories


Dodge, S; Laube, P; Weibel, Robert (2012). Movement similarity assessment using symbolic representation of trajectories. International Journal of Geographical Information Science, 26(9):1563-1588.

Abstract

This paper describes a novel approach for finding similar trajectories, using trajectory segmentation based on movement parameters such as speed, acceleration, or direction. First, a segmentation technique is applied to decompose trajectories into a set of segments with homogeneous characteristics with respect to a particular movement parameter. Each segment is assigned to a movement parameter class, representing the behavior of the movement parameter. Accordingly, the segmentation procedure transforms a trajectory to a sequence of class labels, that is, a symbolic representation. A modified version of edit distance, called Normalized Weighted Edit Distance (NWED) is introduced as a similarity measure between different sequences. As an application, we demonstrate how the method can be employed to cluster trajectories. The performance of the approach is assessed in two case studies using real movement datasets from two different application domains, namely, North Atlantic Hurricane trajectories and GPS tracks of couriers in London. Three different experiments have been conducted that respond to different facets of the proposed techniques, and that compare our NWED measure to a related method.

Abstract

This paper describes a novel approach for finding similar trajectories, using trajectory segmentation based on movement parameters such as speed, acceleration, or direction. First, a segmentation technique is applied to decompose trajectories into a set of segments with homogeneous characteristics with respect to a particular movement parameter. Each segment is assigned to a movement parameter class, representing the behavior of the movement parameter. Accordingly, the segmentation procedure transforms a trajectory to a sequence of class labels, that is, a symbolic representation. A modified version of edit distance, called Normalized Weighted Edit Distance (NWED) is introduced as a similarity measure between different sequences. As an application, we demonstrate how the method can be employed to cluster trajectories. The performance of the approach is assessed in two case studies using real movement datasets from two different application domains, namely, North Atlantic Hurricane trajectories and GPS tracks of couriers in London. Three different experiments have been conducted that respond to different facets of the proposed techniques, and that compare our NWED measure to a related method.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Date:2012
Deposited On:02 Apr 2012 09:00
Last Modified:05 Apr 2016 15:33
Publisher:Taylor & Francis
ISSN:1365-8816 (P) 1365-8824 (E)
Additional Information:This is an electronic version of an article published in Dodge, S; Laube, P; Weibel, R (2012). Movement similarity assessment using symbolic representation of trajectories. International Journal of Geographical Information Science:online. Journal of Geographical Information Science: http://www.tandfonline.com/loi/tgis20.
Publisher DOI:https://doi.org/10.1080/13658816.2011.630003

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