HierST: A Unified Hierarchical Spatial-temporal Framework for COVID-19 Trend Forecasting.
Shun Zheng|Zhifeng Gao|Wei Cao|Jiang Bian|Tie-Yan Liu
| Anthology ID: | DBLP:conf/cikm/ZhengGC0L21 |
|---|---|
| Volume: | CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1 - 5, 2021 |
| Year: | 2021 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 4383-4392 |
| URL: | https://doi.org/10.1145/3459637.3481927 |
| DOI: | https://doi.org/10.1145/3459637.3481927 |
| DBLP: | conf/cikm/ZhengGC0L21 |
| BibTeX: |
@inproceedings{zheng-2021-hierst,
author = {Shun Zheng and
Zhifeng Gao and
Wei Cao and
Jiang Bian and
Tie-Yan Liu},
editor = {Gianluca Demartini and
Guido Zuccon and
J. Shane Culpepper and
Zi Huang and
Hanghang Tong},
title = {{HierST: A Unified Hierarchical Spatial-temporal Framework for COVID-19 Trend Forecasting}},
booktitle = {{CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1 - 5, 2021}},
pages = {4383--4392},
publisher = {ACM},
year = {2021},
url = {https://doi.org/10.1145/3459637.3481927},
doi = {https://doi.org/10.1145/3459637.3481927}
}