19 citations · 39 across the 3 of their papers we have counts for
3 papers
Self-Supervised Reinforcement Learning for Recommender Systems
Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis +1
In session-based or sequential recommendation, it is important to consider a number of factors like long-term user engagement, multiple types of user-item interactions such as clic…
Graph Highway Networks
Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis +1
Graph Convolution Networks (GCN) are widely used in learning graph representations due to their effectiveness and efficiency. However, they suffer from the notorious over-smoothing…
Relational Collaborative Filtering:Modeling Multiple Item Relations for Recommendation
Xin Xin, Xiangnan He, Yongfeng Zhang +2
Existing item-based collaborative filtering (ICF) methods leverage only the relation of collaborative similarity. Nevertheless, there exist multiple relations between items in real…