TFROM: A Two-sided Fairness-Aware Recommendation Model for Both Customers and Providers.
Yao Wu|Jian Cao|Guandong Xu|Yudong Tan
| Anthology ID: | DBLP:conf/sigir/Wu0XT21 |
|---|---|
| Volume: | SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, Canada, July 11-15, 2021 |
| Year: | 2021 |
| Venue: | Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) |
| Publisher: | ACM |
| Pages: | 1013-1022 |
| URL: | https://doi.org/10.1145/3404835.3462882 |
| DOI: | https://doi.org/10.1145/3404835.3462882 |
| DBLP: | conf/sigir/Wu0XT21 |
| BibTeX: |
@inproceedings{wu-2021-tfrom,
author = {Yao Wu and
Jian Cao and
Guandong Xu and
Yudong Tan},
editor = {Fernando Diaz and
Chirag Shah and
Torsten Suel and
Pablo Castells and
Rosie Jones and
Tetsuya Sakai},
title = {{TFROM: A Two-sided Fairness-Aware Recommendation Model for Both Customers and Providers}},
booktitle = {{SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, Canada, July 11-15, 2021}},
pages = {1013--1022},
publisher = {ACM},
year = {2021},
url = {https://doi.org/10.1145/3404835.3462882},
doi = {https://doi.org/10.1145/3404835.3462882}
}