Can One Embedding Fit All? A Multi-Interest Learning Paradigm Towards Improving User Interest Diversity Fairness.

Yuying Zhao|Minghua Xu|Huiyuan Chen|Yuzhong Chen|Yiwei Cai|Rashidul Islam|Yu Wang|Tyler Derr


Anthology ID:DBLP:conf/www/Zhao0CCCI0D24
Volume:Proceedings of the ACM on Web Conference 2024, WWW 2024, Singapore, May 13-17, 2024
Year:2024
Venue:The Web Conference (WWW)
Publisher:ACM
Pages:1237-1248
URL:https://doi.org/10.1145/3589334.3645662
DOI:https://doi.org/10.1145/3589334.3645662
DBLP:conf/www/Zhao0CCCI0D24
BibTeX:
@inproceedings{zhao-2024-one, author = {Yuying Zhao and Minghua Xu and Huiyuan Chen and Yuzhong Chen and Yiwei Cai and Rashidul Islam and Yu Wang and Tyler Derr}, editor = {Tat-Seng Chua and Chong-Wah Ngo and Ravi Kumar and Hady Wirawan Lauw and Roy Ka-Wei Lee}, title = {{Can One Embedding Fit All? A Multi-Interest Learning Paradigm Towards Improving User Interest Diversity Fairness}}, booktitle = {{Proceedings of the ACM on Web Conference 2024, WWW 2024, Singapore, May 13-17, 2024}}, pages = {1237--1248}, publisher = {ACM}, year = {2024}, url = {https://doi.org/10.1145/3589334.3645662}, doi = {https://doi.org/10.1145/3589334.3645662} }