Proceedings of the 2016 International Conference on Computer Science and Electronic Technology

A Novel Algorithm for Detecting Spatial-Temporal Trajectory Outlier

Authors
Shenglan Lv, Yifan Zhang, Genlin Ji, Bin Zhao
Corresponding Author
Shenglan Lv
Available Online August 2016.
DOI
https://doi.org/10.2991/cset-16.2016.44How to use a DOI?
Keywords
Spatial-temporal trajectory, outlier detection, parallel data mining
Abstract
As an important area of spatial-temporal data mining, trajectory outlier detection has already attracted broad attention in recent years. In this paper, we present a novel distance measurement between spatial-temporal sub-trajectories and propose algorithm STOD for detecting outliers in both spatial and temporal dimensions jointly. Each trajectory is divided into line segments at first, and the corresponding minimal boundary boxes are constructed. After combination, the outlier index is computed with our distance measurements including overlapping volume, angle and speed. To improve the efficiency of algorithm STOD, we present algorithm PSTOD for parallel detecting spatial-temporal trajectory outlier, which is implemented using Spark framework. The experiment results on real taxi dataset show that the two algorithms are effective and efficient.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
Part of series
Advances in Computer Science Research
Publication Date
August 2016
ISBN
978-94-6252-213-8
ISSN
2352-538X
DOI
https://doi.org/10.2991/cset-16.2016.44How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Shenglan Lv
AU  - Yifan Zhang
AU  - Genlin Ji
AU  - Bin Zhao
PY  - 2016/08
DA  - 2016/08
TI  - A Novel Algorithm for Detecting Spatial-Temporal Trajectory Outlier
PB  - Atlantis Press
SP  - 184
EP  - 190
SN  - 2352-538X
UR  - https://doi.org/10.2991/cset-16.2016.44
DO  - https://doi.org/10.2991/cset-16.2016.44
ID  - Lv2016/08
ER  -