A Unified Search and Recommendation Framework Based on Multi-Scenario Learning for Ranking in E-commerce.
Jinhan Liu|Qiyu Chen|Junjie Xu|Junjie Li|Baoli Li|Sulong Xu
| Anthology ID: | DBLP:conf/sigir/LiuCXL0X24 |
|---|---|
| Volume: | Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024, Washington DC, USA, July 14-18, 2024 |
| Year: | 2024 |
| Venue: | Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) |
| Publisher: | ACM |
| Pages: | 2890-2894 |
| URL: | https://doi.org/10.1145/3626772.3661356 |
| DOI: | https://doi.org/10.1145/3626772.3661356 |
| DBLP: | conf/sigir/LiuCXL0X24 |
| BibTeX: |
@inproceedings{liu-2024-unified,
author = {Jinhan Liu and
Qiyu Chen and
Junjie Xu and
Junjie Li and
Baoli Li and
Sulong Xu},
editor = {Grace Hui Yang and
Hongning Wang and
Sam Han and
Claudia Hauff and
Guido Zuccon and
Yi Zhang},
title = {{A Unified Search and Recommendation Framework Based on Multi-Scenario Learning for Ranking in E-commerce}},
booktitle = {{Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024, Washington DC, USA, July 14-18, 2024}},
pages = {2890--2894},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3626772.3661356},
doi = {https://doi.org/10.1145/3626772.3661356}
}