Can One Embedding Fit All? A Multi-Interest Learning Paradigm Towards Improving User Interest Diversity Fairness
Author:
Affiliation:
1. Vanderbilt University, Nashville, TN, USA
2. Visa Research, Foster City, CA, USA
Funder
NSF (National Science Foundation)
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3589334.3645662
Reference44 articles.
1. Controllable Multi-Interest Framework for Recommendation
2. Structured Graph Convolutional Networks with Stochastic Masks for Recommender Systems
3. Graph Neural Transport Networks with Non-local Attentions for Recommender Systems
4. Gautam Choudhary, Iftikhar Ahamath Burhanuddin, Eunyee Koh, Fan Du, and Ryan A Rossi. 2022. PersonaSAGE: A Multi-Persona Graph Neural Network. arXiv preprint arXiv:2212.13709 (2022).
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