Tra-DBScan:a Algorithm of Clustering Trajectories

摘要：

　　Accompany with fast development of location technology,more and more trajectories datasets are collected on the real applications.So it is something of value in the theory and applied research to mine the clusters from these datasets.In this paper,a trajectory clustering algorithm,called Density-Based Spatial Clustering of Application with noise (Tra-DBSCAN for short),based on DBSCAN that is a classic clustering algorithm.In this framework,each trajectory firstly partitions into sub-trajectories as clustering object,and then line hausdorff distance is used to measure the distance between two sub-trajectories.Next,DBSCAN is introduced to cluster sub-trajectory to form cluster area,and then connecting different moments of clustering area is regarded as trajectory movement patterns.Finally,the experimental results show our frameworks effective.

关键词： Trajectory data Hausdorff distance Clustering analysis

作者: Liangxu Liu Jiatao Song Bo Guan Zhaoxiao Wu Kejia He

作者单位: School of Electronic and Information Engineering, Ningbo University of Technology, Ningbo,Zhejiang, 315016,China

会议类型: 国际会议

会议名称: the Second International Conference on Frontiers of Manufacturing and Design Science(第二届制造与设计科学国际会议(ICFMD 2011))

会议地点: 台湾

会议语种:英文

页码: 4875-4879

在线出版日期: 2011-12-11（万方平台首次上网日期，不代表论文的发表时间）