Urban region representation learning with human trajectories: a multi-view approach incorporating transition, spatial, and temporal perspectives

• المؤلفون الرئيسيون: Zhang, Yu, Huang, Weiming, Yao, Yao, Gao, Song, Cui, Lizhen, Yan, Zhongmin
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2024
• الموضوعات: Computer and Information Science; Urban region embedding; Human trajectories
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/181780

Mining latent information from human trajectories for understanding our cities has been persistent endeavors in urban studies and spatial information science. Many previous studies relied on manually crafted features and followed a supervised learning pipeline for a particular task, e.g. land use cl...