Placement and Movement Episodes Detection using Mobile Trajectories Data
Name
Mariano Hedberto Jofré
Abstract
This thesis presents a trajectory episode matrix to enable the detection of placement and movement episodes from mobile location data. The data used in this work is very sparse in time and space. Therefore, the estimation of user’s placement and movement patterns poses a big challenge. The presented approach performs data analysis to find meaningful locations and introduces an algorithm to detect movement and placement episodes. To perform the analysis and visualize the results a statistical analysis tool was developed with R. The work done as a result of this thesis can be used to improve the identification of the meaningful locations and to help predicting the semantic meanings of mobile user’s patterns.
Graduation Thesis language
English
Graduation Thesis type
Master - Software Engineering
Supervisor(s)
Dr. Amnir Hadachi & Msc. Elis Kõivumägi
Defence year
2015