弹道
计算机科学
分割
特征(语言学)
过程(计算)
语义学(计算机科学)
人工智能
计算机视觉
数据挖掘
天文
语言学
操作系统
物理
哲学
程序设计语言
作者
Minshi Liu,Guifang He,Yi Long
标识
DOI:10.1007/s41651-021-00088-5
摘要
Abstract With the development of mobile positioning technology, a large amount of mobile trajectory data has been generated. Therefore, to store, process and mine trajectory data in a better way, trajectory data simplification is imperative. Current trajectory data simplification methods are either based on spatiotemporal features or semantic features, such as road network structure, but they do not consider semantic features of a trajectory stop. To overcome this limitation, this study presents a trajectory segmentation simplification method based on stop features. The proposed method first extracts the stop feature of a trajectory, then divides the trajectory into move segments and stop segments based on the stop features, and finally simplifies the obtained segments. The proposed method is verified by experiments on personal trajectory data and taxi trajectory data. Compared with the classic spatiotemporal simplification method, the proposed method has higher spatiotemporal and semantic accuracy under different simplification scales. The proposed method is especially suitable for trajectory data with more stop features.
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