Learning urban region representations with POIs and hierarchical graph infomax

We present the hierarchical graph infomax (HGI) approach for learning urban region representations (vector embeddings) with points-of-interest (POIs) in a fully unsupervised manner, which can be used in various downstream tasks. Specifically, HGI comprises several key steps: (1) training category em...

全面介紹

Saved in:
書目詳細資料
Main Authors: Huang, Weiming, Zhang, Daokun, Mai, Gengchen, Guo, Xu, Cui, Lizhen
其他作者: School of Computer Science and Engineering
格式: Article
語言:English
出版: 2023
主題:
在線閱讀:https://hdl.handle.net/10356/169131
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!