Divide and Conquer: Towards Better Embedding-based Retrieval for Recommender Systems from a Multi-task Perspective.
Yuan Zhang|Xue Dong|Weijie Ding|Biao Li|Peng Jiang|Kun Gai
| Anthology ID: | DBLP:conf/www/ZhangDDLJG23 |
|---|---|
| Volume: | Companion Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023 |
| Year: | 2023 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM |
| Pages: | 366-370 |
| URL: | https://doi.org/10.1145/3543873.3584629 |
| DOI: | https://doi.org/10.1145/3543873.3584629 |
| DBLP: | conf/www/ZhangDDLJG23 |
| BibTeX: |
@inproceedings{zhang-2023-divide,
author = {Yuan Zhang and
Xue Dong and
Weijie Ding and
Biao Li and
Peng Jiang and
Kun Gai},
editor = {Ying Ding and
Jie Tang and
Juan F. Sequeda and
Lora Aroyo and
Carlos Castillo and
Geert-Jan Houben},
title = {{Divide and Conquer: Towards Better Embedding-based Retrieval for Recommender Systems from a Multi-task Perspective}},
booktitle = {{Companion Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023}},
pages = {366--370},
publisher = {ACM},
year = {2023},
url = {https://doi.org/10.1145/3543873.3584629},
doi = {https://doi.org/10.1145/3543873.3584629}
}