Feb. 28, 2024, 5:41 a.m. | Zhipeng Ma, Zheyan Tu, Xinhai Chen, Yan Zhang, Deguo Xia, Guyue Zhou, Yilun Chen, Yu Zheng, Jiangtao Gong

cs.LG updates on arXiv.org arxiv.org

arXiv:2402.16915v1 Announce Type: new
Abstract: Trajectory representation learning plays a pivotal role in supporting various downstream tasks. Traditional methods in order to filter the noise in GPS trajectories tend to focus on routing-based methods used to simplify the trajectories. However, this approach ignores the motion details contained in the GPS data, limiting the representation capability of trajectory representation learning. To fill this gap, we propose a novel representation learning framework that Joint GPS and Route Modelling based on self-supervised technology, …

abstract arxiv cs.ai cs.lg filter focus gps modeling noise pivotal refine representation representation learning role route routing tasks trajectory type

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