Enhancing Disentanglement of Popularity Bias for Recommendation With Triplet Contrastive Learning
Author:
Affiliation:
1. School of Big Data and Software Engineering, Chongqing University, Chongqing, China
2. School of Civil Engineering, University of Sydney, Camperdown, NSW, Australia
Funder
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
Chongqing University
Australian Research Council
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/4629386/10554674/10479167.pdf?arnumber=10479167
Reference36 articles.
1. SocialLGN: Light graph convolution network for social recommendation;Liao,2022
2. Modeling Dynamic Missingness of Implicit Feedback for Sequential Recommendation
3. Modeling Product’s Visual and Functional Characteristics for Recommender Systems
4. A Granular SVM-Based Method for Top-N Web Services Recommendation
5. Privacy Preserving Location-Aware Personalized Web Service Recommendations
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