239 citations · 890 across the 14 of their papers we have counts for
6 papers · 1 filter
SelfCF: A Simple Framework for Self-supervised Collaborative Filtering
Xin Zhou, Aixin Sun, Yong Liu +2
Collaborative filtering (CF) is widely used to learn informative latent representations of users and items from observed interactions. Existing CF-based methods commonly adopt nega…
A Critical Study on Data Leakage in Recommender System Offline Evaluation
Yitong Ji, Aixin Sun, Jie Zhang +1
Recommender models are hard to evaluate, particularly under offline setting. In this paper, we provide a comprehensive and critical analysis of the data leakage issue in recommende…
A Re-visit of the Popularity Baseline in Recommender Systems
Yitong Ji, Aixin Sun, Jie Zhang +1
Popularity is often included in experimental evaluation to provide a reference performance for a recommendation task. To understand how popularity baseline is defined and evaluated…
Hierarchical Attentive Knowledge Graph Embedding for Personalized Recommendation
Xiao Sha, Zhu Sun, Jie Zhang
Knowledge graphs (KGs) have proven to be effective for high-quality recommendation, where the connectivities between users and items provide rich and complementary information to u…
Research Commentary on Recommendations with Side Information: A Survey and Research Directions
Zhu Sun, Qing Guo, Jie Yang +4
Recommender systems have become an essential tool to help resolve the information overload problem in recent decades. Traditional recommender systems, however, suffer from data spa…
Interacting Attention-gated Recurrent Networks for Recommendation
Wenjie Pei, Jie Yang, Zhu Sun +3
Capturing the temporal dynamics of user preferences over items is important for recommendation. Existing methods mainly assume that all time steps in user-item interaction history…