Abstract:
With the maturity of Geographical
Positioning System (GPS), wireless, and Web
technologies, increasing amounts of movement
data collected from various moving objects, such
as animals, vehicles, mobile devices, and climate
radars, has become widely available. Analyzing
such data has broad applications, such as, in
ecological study, vehicle control, mobile
communication management, and climatological
forecast. MoveMine is designed for sophisticated
moving object data mining by integrating several
attractive functions including moving object
pattern mining and trajectory mining. Trajectory
clustering is one of the major functions in
trajectory mining. Existing trajectory clustering
algorithms group similar trajectories as a whole,
thus discovering common trajectories. In this
paper, moving object trajectory clustering is
presented. In trajectory segmentation, the global
optimum segmentation can be found by dynamic
programming. We present a pattern based
clustering algorithm that extends k-means
algorithm for clustering moving object trajectory
data. The system will be evaluated on elk, deer
and cattle’s movement dataset which has been
generated by the Starkey project for effectiveness
of the system.
