Using Learning Features to Find Similar Trajectories

摘要：

　　In the last decade,the trajectories data have been collected by many applications and such trajectories contain rich information that can be used to detect events especially for anomaly event detections.However,there are still many challenges on this problem,the major one is how to identify the similar trajectories on semantic level.In this work,we extract the nature features from raw trajectories and use them to do the semantic trajectory similarity search.To achieve this,we propose a PLS algorithm to detect such semantic similar trajectories efficiently and effectively.We also leverage the DBSCAN to help extract the information from large trajectory data.The results of our algorithm are demonstrated by the real world dataset.

关键词： Feature extraction Trajectory compression Trajectory partition Similarity calculation

作者: Peiguo Fu Haozhou Wang Kuien Liu Xiaohui Hu Hui Zhang

作者单位: Science and Technology on Integrated Information System Laboratory,Institute of Software Chinese Aca Pivotal.inc,San Francisco,USA

会议类型: 国际会议

会议名称: International Asia-Pacific Web Conference(第18届国际亚太互联网大会)

会议地点: 苏州

会议语种:英文

页码: 298-309

在线出版日期: 2016-09-23（万方平台首次上网日期，不代表论文的发表时间）