36 citations · 57 across the 9 of their papers we have counts for
4 papers · 1 filter
Dual Contrastive Transformer for Hierarchical Preference Modeling in Sequential Recommendation
Chengkai Huang, Shoujin Wang, Xianzhi Wang +1
Sequential recommender systems (SRSs) aim to predict the subsequent items which may interest users via comprehensively modeling users' complex preference embedded in the sequence o…
Modeling Temporal Positive and Negative Excitation for Sequential Recommendation
Chengkai Huang, Shoujin Wang, Xianzhi Wang +1
Sequential recommendation aims to predict the next item which interests users via modeling their interest in items over time. Most of the existing works on sequential recommendatio…
Locality-Sensitive Experience Replay for Online Recommendation
Xiaocong Chen, Lina Yao, Xianzhi Wang +1
Online recommendation requires handling rapidly changing user preferences. Deep reinforcement learning (DRL) is gaining interest as an effective means of capturing users' dynamic i…
A Survey of Deep Reinforcement Learning in Recommender Systems: A Systematic Review and Future Directions
Xiaocong Chen, Lina Yao, Julian McAuley +2
In light of the emergence of deep reinforcement learning (DRL) in recommender systems research and several fruitful results in recent years, this survey aims to provide a timely an…