Discovering Closed Frequent Patterns in Moving Trajectory Database

摘要：

　　The increasing availability of tracking devices bring larger amounts of trajectories representing peoples moving location histories.In this paper,we aimed to mine closed frequent patterns in moving trajectory database.Such closed frequent patterns can help us to understand general mobile behaviors in compact representation.In this work,we first presented a conception of spatiotemporal region of interesting (STROI) to capture the attribute of moving trajectory in spatial and temporal dimensions.Second,based on the set of STROIs distributing in given geospatial region,we transformed trajectory data into STROI element sequence data at different time slice with respect to corresponding STROIs.Third,we modified the closed sequence pattern mining algorithm CloSpan to adapt to closed moving trajectory pattern discovery.Finally,the approaches are then validated by a range of synthetic data sets to evaluate the usefulness and efficiency.

关键词： closed frequent pattern moving trajectory databse spatiotemporal region of interesting CloSpan algorithm

作者: Liang Wang Kunyuan Hu Tao Ku

作者单位: Shenyang Institute of Automation Chinese Academy of Sciences Graduate School of the Chinese Academy Shenyang Institute of Automation Chinese Academy of Sciences

会议类型: 国际会议

会议名称: 2012 IEEE 14th International Conference on Communication Technology(2012年第十四届通信技术国际会议(ICCT 2012))

会议地点: 成都

会议语种:英文

页码: 1546-1551

在线出版日期: 2012-11-09（万方平台首次上网日期，不代表论文的发表时间）