Re4: Learning to Re-contrast, Re-attend, Re-construct for Multi-interest Recommendation.
Shengyu Zhang|Lingxiao Yang|Dong Yao|Yujie Lu|Fuli Feng|Zhou Zhao|Tat-Seng Chua|Fei Wu
| Anthology ID: | DBLP:conf/www/ZhangYYLFZC022 |
|---|---|
| Volume: | WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25 - 29, 2022 |
| Year: | 2022 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM |
| Pages: | 2216-2226 |
| URL: | https://doi.org/10.1145/3485447.3512094 |
| DOI: | https://doi.org/10.1145/3485447.3512094 |
| DBLP: | conf/www/ZhangYYLFZC022 |
| BibTeX: |
@inproceedings{zhang-2022-re4,
author = {Shengyu Zhang and
Lingxiao Yang and
Dong Yao and
Yujie Lu and
Fuli Feng and
Zhou Zhao and
Tat-Seng Chua and
Fei Wu},
editor = {Fr\'{e}d\'{e}rique Laforest and
Rapha\"{e}l Troncy and
Elena Simperl and
Deepak Agarwal and
Aristides Gionis and
Ivan Herman and
Lionel M\'{e}dini},
title = {{Re4: Learning to Re-contrast, Re-attend, Re-construct for Multi-interest Recommendation}},
booktitle = {{WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25 - 29, 2022}},
pages = {2216--2226},
publisher = {ACM},
year = {2022},
url = {https://doi.org/10.1145/3485447.3512094},
doi = {https://doi.org/10.1145/3485447.3512094}
}