Application of OPTICS and Offline Batch Processing in Trajectory Clustering

Trajectory clustering is an important step in spatio-temporal trajectory processing.Common trajectory clustering algorithms,such as TRACLUS algorithm,usually have high time complexity and are sensitive to input parameters,thus consuming a lot of time to find optimal parameters.In order to solve this...

Full description

Saved in:
Bibliographic Details
Published in:Ji suan ji gong cheng Vol. 46; no. 7; pp. 72 - 77,83
Main Author: GUO Yu, CHEN Jinyong, ZHANG Xinyu, LI Liang, SUN Weiwei
Format: Journal Article
Language:Chinese
English
Published: Editorial Office of Computer Engineering 01.07.2020
Subjects:
spatio-temporal trajectory clustering|density clustering|optics algorithm|offline batch processing|traclus algorithm
ISSN:1000-3428
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Trajectory clustering is an important step in spatio-temporal trajectory processing.Common trajectory clustering algorithms,such as TRACLUS algorithm,usually have high time complexity and are sensitive to input parameters,thus consuming a lot of time to find optimal parameters.In order to solve this problem,this paper improves the TRACLUS algorithm by using offline batch processing technology and OPTICS algorithm.This optimization reduces the sensitivity of input parameters and the time for trajectory clustering of multiple sets of parameters,so the workload of the manual parameter debugging is reduced.Experimental results show that the time efficiency of the algorithm has been greatly improved when the optimal parameters are unknown and multiple sets of parameters need to be tested.
ISSN:1000-3428
DOI:10.19678/j.issn.1000-3428.0054309