作　　者： ;

机构地区： 华南师范大学计算机学院

出　　处： 《计算机系统应用》 2020年第4期214-219,共6页

摘　　要： 轨迹中的停留点识别是将空间轨迹转换为语义轨迹的关键步骤.当前轨迹停留点识别方法缺少对轨迹记录点时间连续性的考虑,导致识别出的停留点缺乏时间信息.同时,在轨迹点缺失的情况下,停留点信息也无法被准确识别.针对上述问题,本文提出一种基于速度的时空聚类方法,首先通过缺失轨迹的时空特性确定真实缺失子轨迹,并根据缺失轨迹的平均速度对其进行插值填充,再结合轨迹速度特征和时空特性识别轨迹中的停留点.实验采用GeoLife轨迹数据集对所提出的方法进行验证,结果表明,该算法能够有效地识别用户的停留点,并对轨迹中的干扰具有一定的鲁棒性. The recognition of stop point in trajectory is the key step to transform spatial trajectory into semantic trajectory. At present, the recognition method of the stop point lacks the consideration of the time continuity of the record point, which leads to the lack of time information of the identified stop point. At the same time, in the scenario of missing track points, the information of stop point cannot be accurately identified. In order to solve these problems, this study proposes a velocity based spatio-temporal clustering method. Firstly, the real missing sub trajectories are determined by the spatio- temporal characteristics of the missing trajectories, and then the missing trajectories are interpolated according to the average velocity of the missing trajectories. In the experiment, GeoLife trajectory data is used to verify the proposed method. The results show that the algorithm can effectively identify the user's stop point, and has relatively sound robustness to the interference in the trajectory.

关 键 词： 时空轨迹 语义轨迹 时空聚类 停留点

领　　域： []