Leveraging ChatGPT to Empower Training-free Dataset Condensation for Content-based Recommendation.
Jiahao Wu|Qijiong Liu|Hengchang Hu|Wenqi Fan|Shengcai Liu|Qing Li|Xiao-Ming Wu|Ke Tang
| Anthology ID: | DBLP:conf/www/WuLHFLLW025 |
|---|---|
| Volume: | Companion Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025 - 2 May 2025 |
| Year: | 2025 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM |
| Pages: | 1402-1406 |
| URL: | https://doi.org/10.1145/3701716.3715555 |
| DOI: | https://doi.org/10.1145/3701716.3715555 |
| DBLP: | conf/www/WuLHFLLW025 |
| BibTeX: |
@inproceedings{wu-2025-leveraging,
author = {Jiahao Wu and
Qijiong Liu and
Hengchang Hu and
Wenqi Fan and
Shengcai Liu and
Qing Li and
Xiao-Ming Wu and
Ke Tang},
editor = {Guodong Long and
Michale Blumestein and
Yi Chang and
Liane Lewin-Eytan and
Zi Huang and
Elad Yom-Tov},
title = {{Leveraging ChatGPT to Empower Training-free Dataset Condensation for Content-based Recommendation}},
booktitle = {{Companion Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025 - 2 May 2025}},
pages = {1402--1406},
publisher = {ACM},
year = {2025},
url = {https://doi.org/10.1145/3701716.3715555},
doi = {https://doi.org/10.1145/3701716.3715555}
}