Ranking Items by the Current-Preferences and Profits: A List-wise Learning-to-Rank Approach to Profit Maximization.
Hong-Kyun Bae|Hae-Ri Jang|Won-Yong Shin|Sang-Wook Kim
| Anthology ID: | DBLP:conf/www/BaeJSK25 |
|---|---|
| Volume: | 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: | 5010-5021 |
| URL: | https://doi.org/10.1145/3696410.3714731 |
| DOI: | https://doi.org/10.1145/3696410.3714731 |
| DBLP: | conf/www/BaeJSK25 |
| BibTeX: |
@inproceedings{bae-2025-ranking,
author = {Hong-Kyun Bae and
Hae-Ri Jang and
Won-Yong Shin and
Sang-Wook Kim},
editor = {Guodong Long and
Michale Blumestein and
Yi Chang and
Liane Lewin-Eytan and
Zi Huang and
Elad Yom-Tov},
title = {{Ranking Items by the Current-Preferences and Profits: A List-wise Learning-to-Rank Approach to Profit Maximization}},
booktitle = {{Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025- 2 May 2025}},
pages = {5010--5021},
publisher = {ACM},
year = {2025},
url = {https://doi.org/10.1145/3696410.3714731},
doi = {https://doi.org/10.1145/3696410.3714731}
}