7 citations · 16 across the 8 of their papers we have counts for
4 papers · 1 filter
Time-aware Hyperbolic Graph Attention Network for Session-based Recommendation
Xiaohan Li, Yuqing Liu, Zheng Liu +1
Session-based Recommendation (SBR) is to predict users' next interested items based on their previous browsing sessions. Existing methods model sessions as graphs or sequences to e…
Mitigating Frequency Bias in Next-Basket Recommendation via Deconfounders
Xiaohan Li, Zheng Liu, Luyi Ma +4
Recent studies on Next-basket Recommendation (NBR) have achieved much progress by leveraging Personalized Item Frequency (PIF) as one of the main features, which measures the frequ…
Pre-training Recommender Systems via Reinforced Attentive Multi-relational Graph Neural Network
Xiaohan Li, Zhiwei Liu, Stephen Guo +4
Recently, Graph Neural Networks (GNNs) have proven their effectiveness for recommender systems. Existing studies have applied GNNs to capture collaborative relations in the data. H…
Dynamic Graph Collaborative Filtering
Xiaohan Li, Mengqi Zhang, Shu Wu +3
Dynamic recommendation is essential for modern recommender systems to provide real-time predictions based on sequential data. In real-world scenarios, the popularity of items and i…