Improving Item-side Fairness of Multimodal Recommendation via Modality Debiasing-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Improving Item-side Fairness of Multimodal Recommendation via Modality Debiasing

Published:2024-05-13 Issue: Volume:33 Page:4697-4705
ISSN:
Container-title:Proceedings of the ACM Web Conference 2024
language:
Short-container-title:

Author:

Shang Yu¹^ORCID,Gao Chen²^ORCID,Chen Jiansheng³^ORCID,Jin Depeng¹^ORCID,Li Yong¹^ORCID

Affiliation:

1. Department of Electronic Engineering, Tsinghua University & BNRist, Tsinghua University, Beijing, China

2. BNRist, Tsinghua University, Beijing, China

3. School of Computer & Communication Engineering, University of Science and Technology Beijing, Beijing, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Guoqiang Institute, Tsinghua University

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3589334.3648156

Reference43 articles.

1. Controlling Popularity Bias in Learning-to-Rank Recommendation

2. Breaking Isolation

3. Simplify and robustify negative sampling for implicit collaborative filtering;Ding Jingtao;Advances in Neural Information Processing Systems,2020

4. Michael D Ekstrand, Mucun Tian, Ion Madrazo Azpiazu, Jennifer D Ekstrand, Oghenemaro Anuyah, David McNeill, and Maria Soledad Pera. 2018. All the cool kids, how do they fit in?: Popularity and demographic biases in recommender evaluation and effectiveness. In Conference on fairness, accountability and transparency. PMLR, 172--186.

5. A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP