M-scan: A Multi-Scenario Causal-driven Adaptive Network for Recommendation.
Jiachen Zhu|Yichao Wang|Jianghao Lin|Jiarui Qin|Ruiming Tang|Weinan Zhang|Yong Yu
| Anthology ID: | DBLP:conf/www/ZhuWLQTZY24 |
|---|---|
| Volume: | Proceedings of the ACM on Web Conference 2024, WWW 2024, Singapore, May 13-17, 2024 |
| Year: | 2024 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM |
| Pages: | 3844-3853 |
| URL: | https://doi.org/10.1145/3589334.3645635 |
| DOI: | https://doi.org/10.1145/3589334.3645635 |
| DBLP: | conf/www/ZhuWLQTZY24 |
| BibTeX: |
@inproceedings{zhu-2024-mscan,
author = {Jiachen Zhu and
Yichao Wang and
Jianghao Lin and
Jiarui Qin and
Ruiming Tang and
Weinan Zhang and
Yong Yu},
editor = {Tat-Seng Chua and
Chong-Wah Ngo and
Ravi Kumar and
Hady Wirawan Lauw and
Roy Ka-Wei Lee},
title = {{M-scan: A Multi-Scenario Causal-driven Adaptive Network for Recommendation}},
booktitle = {{Proceedings of the ACM on Web Conference 2024, WWW 2024, Singapore, May 13-17, 2024}},
pages = {3844--3853},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3589334.3645635},
doi = {https://doi.org/10.1145/3589334.3645635}
}