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} }