Incremental Clustering for Trajectories

Trajectory clustering has played a crucial role in data analysis since it reveals underlying trends of moving objects. Due to their sequential nature, trajectory data are often received incrementally, e.g., continuous new points reported by GPS system. However, since existing trajectory clustering algorithms are developed for static datasets, they are not suitable for incremental clustering with the following two requirements. First, clustering should be processed efficiently since it can be frequently requested. Second, huge amounts of trajectory data must be accommodated, as they will accumulate constantly. An incremental clustering framework for trajectories is proposed in this paper. It contains two parts: online micro-cluster maintenance and offline macro-cluster creation. For online part, when a new bunch of trajectories arrives, each trajectory is simplified into a set of directed line segments in order to find clusters of trajectory subparts. Micro-clusters are used to stor...

• Type: Conference
• Year: 2010
• Where: DASFAA
• Authors: Zhenhui Li, Jae-Gil Lee, Xiaolei Li, Jiawei Han
• Keywords: DASFAA 2010, Database, Trajectory, Trajectory Clustering, Trajectory Data