Fighting Mainstream Bias in Recommender Systems via Local Fine Tuning.

Ziwei Zhu|James Caverlee


Anthology ID:DBLP:conf/wsdm/ZhuC22
Volume:WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21 - 25, 2022
Year:2022
Venue:Web Search and Data Mining (WSDM)
Publisher:ACM
Pages:1497-1506
URL:https://doi.org/10.1145/3488560.3498427
DOI:https://doi.org/10.1145/3488560.3498427
DBLP:conf/wsdm/ZhuC22
BibTeX:
@inproceedings{zhu-2022-fighting, author = {Ziwei Zhu and James Caverlee}, editor = {K. Sel\c{c}uk Candan and Huan Liu and Leman Akoglu and Xin Dong and Jiliang Tang}, title = {{Fighting Mainstream Bias in Recommender Systems via Local Fine Tuning}}, booktitle = {{WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21 - 25, 2022}}, pages = {1497--1506}, publisher = {ACM}, year = {2022}, url = {https://doi.org/10.1145/3488560.3498427}, doi = {https://doi.org/10.1145/3488560.3498427} }