Spatio-temporal Similarity Measure for Network Constrained Trajectory Data

DOI

10.2991/ijcis.2011.4.5.30How to use a DOI?

Keywords

constrained trajectory, road network, spatio-temporal similarity measure, trajectory clustering.

Abstract

Trajectory similarity measure is an important issue for analyzing the behavior of moving objects. In this paper, a similarity measure method for network constrained trajectories is proposed. It considers spatial and temporal features simultaneously in calculating spatio-temporal distance. The crossing points of network and semantic information of trajectory are used to extract the characteristic points for trajectory partition. Experiment results show that the storage space is decreased after trajectory partition and the similarity measure method is valid and efficient for trajectory clustering.

Copyright

© 2011, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Ying Xia
AU  - Guo-Yin Wang
AU  - Xu Zhang
AU  - Gyoung-Bae Kim
AU  - Hae-Young Bae
PY  - 2011
DA  - 2011/09/01
TI  - Spatio-temporal Similarity Measure for Network Constrained Trajectory Data
JO  - International Journal of Computational Intelligence Systems
SP  - 1070
EP  - 1079
VL  - 4
IS  - 5
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2011.4.5.30
DO  - 10.2991/ijcis.2011.4.5.30
ID  - Xia2011
ER  -