ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models.
Qijiong Liu|Nuo Chen|Tetsuya Sakai|Xiao-Ming Wu
| Anthology ID: | DBLP:conf/wsdm/LiuCS024 |
|---|---|
| Volume: | Proceedings of the 17th ACM International Conference on Web Search and Data Mining, WSDM 2024, Merida, Mexico, March 4-8, 2024 |
| Year: | 2024 |
| Venue: | Web Search and Data Mining (WSDM) |
| Publisher: | ACM |
| Pages: | 452-461 |
| URL: | https://doi.org/10.1145/3616855.3635845 |
| DOI: | https://doi.org/10.1145/3616855.3635845 |
| DBLP: | conf/wsdm/LiuCS024 |
| BibTeX: |
@inproceedings{liu-2024-boosting,
author = {Qijiong Liu and
Nuo Chen and
Tetsuya Sakai and
Xiao-Ming Wu},
editor = {Luz Angelica Caudillo-Mata and
Silvio Lattanzi and
Andr\'{e}s Mu\~{n}oz Medina and
Leman Akoglu and
Aristides Gionis and
Sergei Vassilvitskii},
title = {{ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models}},
booktitle = {{Proceedings of the 17th ACM International Conference on Web Search and Data Mining, WSDM 2024, Merida, Mexico, March 4-8, 2024}},
pages = {452--461},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3616855.3635845},
doi = {https://doi.org/10.1145/3616855.3635845}
}