TraClass: trajectory classification using hierarchical region-based and trajectory-based clustering

Trajectory classification, i.e., model construction for predicting the class labels of moving objects based on their trajectories and other features, has many important, real-world applications. A number of methods have been reported in the literature, but due to using the shapes of whole trajectories for classification, they have limited classification capability when discriminative features appear at parts of trajectories or are not relevant to the shapes of trajectories. These situations are often observed in long trajectories spreading over large geographic areas. Since an essential task for effective classification is generating discriminative features, a feature generation framework TraClass for trajectory data is proposed in this paper, which generates a hierarchy of features by partitioning trajectories and exploring two types of clustering: (1) region-based and (2) trajectory-based. The former captures the higher-level region-based features without using movement patterns, wh...

• Type: Journal
• Year: 2008
• Where: PVLDB
• Authors: Jae-Gil Lee, Jiawei Han, Xiaolei Li, Hector Gonzalez
• Keywords: PVLDB 2008, Trajectories, Trajectory, Trajectory Classification