PLMTrajRec: A Scalable and Generalizable Trajectory Recovery Method with Pre-trained Language Models

Understand

Spatiotemporal trajectory data is crucial for various applications.

• However, issues such as device malfunctions and network instability often cause sparse trajectories, leading to lost detailed movement information.
• Recovering the missing points in sparse trajectories to restore the detailed information is thus essential.
• Despite recent progress, several challenges remain.