765 citations · 1.3k across the 29 of their papers we have counts for
4 papers · 1 filter
Alleviating the Long-Tail Problem in Conversational Recommender Systems
Zhipeng Zhao, Kun Zhou, Xiaolei Wang +4
Conversational recommender systems (CRS) aim to provide the recommendation service via natural language conversations. To develop an effective CRS, high-quality CRS datasets are ve…
Filter-enhanced MLP is All You Need for Sequential Recommendation
Kun Zhou, Hui Yu, Wayne Xin Zhao +1
Recently, deep neural networks such as RNN, CNN and Transformer have been applied in the task of sequential recommendation, which aims to capture the dynamic preference characteris…
Curriculum Pre-Training Heterogeneous Subgraph Transformer for Top- Recommendation
Hui Wang, Kun Zhou, Wayne Xin Zhao +2
Due to the flexibility in modelling data heterogeneity, heterogeneous information network (HIN) has been adopted to characterize complex and heterogeneous auxiliary data in top-…
S^3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization
Kun Zhou, Hui Wang, Wayne Xin Zhao +5
Recently, significant progress has been made in sequential recommendation with deep learning. Existing neural sequential recommendation models usually rely on the item prediction l…