Title :
A density-based approach for mining movement patterns from semantic trajectories
Author :
Renhe Jiang; Jing Zhao; Tingting Dong;Yoshiharu Ishikawa; Chuan Xiao;Yuya Sasaki
Author_Institution :
Graduate School of Information Science, Nagoya University, Japan
Abstract :
In this paper, we study the problem of discovering all movement patterns from semantic trajectory databases. We propose a two-step method to solve this problem efficiently. We first retrieve frequent movement patterns of categories from the transformed database of sequential categories, and then cluster dense trajectories in a growth-type way for all movement patterns. Moreover, we define a new metric distance function on trajectories. We also use M-tree to cluster trajectories more efficiently. Our experimental results demonstrate the efficiency of the proposed method.
Keywords :
"Trajectory","Semantics","Databases","Euclidean distance","Clustering algorithms","History"
Conference_Titel :
TENCON 2015 - 2015 IEEE Region 10 Conference
Print_ISBN :
978-1-4799-8639-2
Electronic_ISBN :
2159-3450
DOI :
10.1109/TENCON.2015.7373034