Quantifying and Mitigating Popularity Bias in Conversational Recommender Systems.
Allen Lin|Jianling Wang|Ziwei Zhu|James Caverlee
| Anthology ID: | DBLP:conf/cikm/LinW0C22 |
|---|---|
| Volume: | Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, USA, October 17-21, 2022 |
| Year: | 2022 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 1238-1247 |
| URL: | https://doi.org/10.1145/3511808.3557423 |
| DOI: | https://doi.org/10.1145/3511808.3557423 |
| DBLP: | conf/cikm/LinW0C22 |
| BibTeX: |
@inproceedings{lin-2022-quantifying,
author = {Allen Lin and
Jianling Wang and
Ziwei Zhu and
James Caverlee},
editor = {Mohammad Al Hasan and
Li Xiong},
title = {{Quantifying and Mitigating Popularity Bias in Conversational Recommender Systems}},
booktitle = {{Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, USA, October 17-21, 2022}},
pages = {1238--1247},
publisher = {ACM},
year = {2022},
url = {https://doi.org/10.1145/3511808.3557423},
doi = {https://doi.org/10.1145/3511808.3557423}
}