DocumentCode :
3752522
Title :
A method of latent semantic information mining for trajectory data
Author :
Lyu-Chao Liao;Xin-Hua Jiang;Fu-Min Zou;Pei-Wei Tsai;Yan-Ling Deng
Author_Institution :
Key Laboratory for Automotive Electronics and Electric Drive of Fujian Province, Fujian University of Technology, Fuzhou, Fujian, China
fYear :
2015
Firstpage :
353
Lastpage :
353
Abstract :
To explore the potential characteristics of trajectory data, this paper presents a method of latent semantic information mining for trajectory data (T-LSD. We aim to solve the problem of structuring the spatio-temporal data and discovering potential patterns from the trajectory data. First, a vector space model is proposed for trajectory data. Then, by the singular value decomposition of the trajectory matrix, we extract its low-dimensional semantic subspace to further mining its latent semantic information. Finally, we evaluate this research method with a mass of practical trajectory data, which has a total mileage of more than three million kilometers. The experimental results showed that this approach can be employed to analyze the potential characteristics of road network with trajectory data, and can be further used to uncover the driving behavior patterns.
Keywords :
"Semantics","Data mining","Trajectory","Matrix decomposition","Roads","Data models"
Publisher :
ieee
Conference_Titel :
Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2015 International Conference on
Type :
conf
DOI :
10.1109/IIH-MSP.2015.120
Filename :
7415829
Link To Document :
بازگشت