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...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Ji suan ji gong cheng Ročník 46; číslo 7; s. 72 - 77,83
Hlavní autor: GUO Yu, CHEN Jinyong, ZHANG Xinyu, LI Liang, SUN Weiwei
Médium: Journal Article
Jazyk:čínština
angličtina
Vydáno: Editorial Office of Computer Engineering 01.07.2020
Témata:
spatio-temporal trajectory clustering|density clustering|optics algorithm|offline batch processing|traclus algorithm
ISSN:1000-3428
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí: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