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Compressing Trajectory for Trajectory Indexing


Authors: K. Feng and Z. Shen
Title: Compressing Trajectory for Trajectory Indexing
Abstract: Nowadays, as many devices like mobile phones and smart watch/band are equipped with GPS-devices, a large volume of trajectory data is generated every day. With the availability of such trajectory data, many mining tasks have been proposed and investigated in the past decade. Since the raw trajectory data is usually very large, it is a big challenge to analyse and mine the raw data directly. In order to address this issue, a branch of research has been done to compress the trajectory data. This paper surveys recent research about trajectory compression. An overview of existing techniques for trajectory compression is provided.
Keywords: Trajectory; Trajectory compression; Survey
Conference Name: 2nd International Conference on Crowd Science and Engineering (ICCSE'17)
Location: Beijing, China
Publisher: ACM
Year: 2017
Accepted PDF File: Compressing_Trajectory_for_Trajectory_Indexing_accepted.pdf
Permanent Link: https://doi.org/10.1145/3126973.3126979
Reference: K. Feng and Z. Shen, “Compressing trajectory for trajectory indexing,” in Proceedings of the 2nd International Conference on Crowd Science and Engineering (ICCSE’17). ACM, July 2017, pp. 68–71.
bibtex: 
@inproceedings{LILY-c123, 
   author = {Feng, Kaiyu and Shen, Zhiqi},
   title  = {Compressing Trajectory for Trajectory Indexing},  
   booktitle = {Proceedings of the 2nd International Conference on Crowd Science and Engineering (ICCSE'17)}, 
   year  = {2017}, 
   month = {July}, 
   pages = {68-71}, 
   location = {Beijing, China},
   publisher = {ACM},
}