31 citations · 33 across the 4 of their papers we have counts for
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cs.IR2022★ 2 cited
Multi-Sparse-Domain Collaborative Recommendation via Enhanced Comprehensive Aspect Preference Learning
Xiaoyun Zhao, Ning Yang, Philip S. Yu
Cross-domain recommendation (CDR) has been attracting increasing attention of researchers for its ability to alleviate the data sparsity problem in recommender systems. However, th…
cs.IR2022
Learning from Atypical Behavior: Temporary Interest Aware Recommendation Based on Reinforcement Learning
Ziwen Du, Ning Yang, Zhonghua Yu +1
Traditional robust recommendation methods view atypical user-item interactions as noise and aim to reduce their impact with some kind of noise filtering technique, which often suff…
cs.IR2021
Dual Adversarial Variational Embedding for Robust Recommendation
Qiaomin Yi, Ning Yang, Philip S. Yu
Robust recommendation aims at capturing true preference of users from noisy data, for which there are two lines of methods have been proposed. One is based on noise injection, and…