69 citations · 75 across the 6 of their papers we have counts for
5 papers · 1 filter
PHKT:Personalized Dynamic Hypergraph-enhanced KAN-Transformer for Multi-behavior Sequential Recommendation
Ruijie Du, Hao Chen, Xin Zhang +5
In multi-behavior recommendation, auxiliary behaviors such as clicks, add-to-cart, and purchases can provide richer supervisory information for predicting target behaviors. Althoug…
Investigating Accuracy-Novelty Performance for Graph-based Collaborative Filtering
Minghao Zhao, Le Wu, Yile Liang +7
Recent years have witnessed the great accuracy performance of graph-based Collaborative Filtering (CF) models for recommender systems. By taking the user-item interaction behavior…
MLP4Rec: A Pure MLP Architecture for Sequential Recommendations
Muyang Li, Xiangyu Zhao, Chuan Lyu +3
Self-attention models have achieved state-of-the-art performance in sequential recommender systems by capturing the sequential dependencies among user-item interactions. However, t…
Personalized Bundle Recommendation in Online Games
Qilin Deng, Kai Wang, Minghao Zhao +5
In business domains, \textit{bundling} is one of the most important marketing strategies to conduct product promotions, which is commonly used in online e-commerce and offline reta…
Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendation
Kai Wang, Zhene Zou, Qilin Deng +5
In recent years, there are great interests as well as challenges in applying reinforcement learning (RL) to recommendation systems (RS). In this paper, we summarize three key pract…