Mining trajectory corridors using Fréchet distance and meshing grids
Haohan Zhu; Jun Luo; Hang Yin; Xiaotao Zhou; Joshua Zhexue Huang; F. Benjamin Zhan
2010
会议名称14th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2010
英文摘要With technology advancement and increasing popularity of location-aware devices, trajectory data are ubiquitous in the real world. Trajectory corridor, as one of the moving patterns, is composed of concatenated sub-trajectory clusters which help analyze the behaviors of moving objects. In this paper we adopt a three-phase approach to discover trajectory corridors using Fre織chet distance as a dissimilarity measurement. First, trajectories are segmented into sub-trajectories using meshing-grids. In the second phase, a hierarchical method is utilized to cluster intra-grid sub-trajectories for each grid cell. Finally, local clusters in each single grid cell are concatenated to construct trajectory corridors. By utilizing a grid structure, the segmentation and concatenation need only single traversing of trajectories or grid cells. Experiments demonstrate that the unsupervised algorithm correctly discovers trajectory corridors from the real trajectory data. The trajectory corridors using Fre織chet distance with temporal information are different from those having only spatial information. By choosing an appropriate grid size, the computing time could be reduced significantly because the number of sub-trajectories in a single grid cell is a dominant factor influencing the speed of the algorithms
收录类别EI
语种英语
内容类型会议论文
源URL[http://ir.siat.ac.cn:8080/handle/172644/3136]  
专题深圳先进技术研究院_数字所
作者单位2010
推荐引用方式
GB/T 7714
Haohan Zhu,Jun Luo,Hang Yin,et al. Mining trajectory corridors using Fréchet distance and meshing grids[C]. 见:14th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2010.
个性服务
查看访问统计
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。


©版权所有 ©2017 CSpace - Powered by CSpace