83 citations · 200 across the 5 of their papers we have counts for
5 papers
Alleviating Video-Length Effect for Micro-video Recommendation
Yuhan Quan, Jingtao Ding, Chen Gao +4
Micro-videos platforms such as TikTok are extremely popular nowadays. One important feature is that users no longer select interested videos from a set, instead they either watch t…
Robust Preference-Guided Denoising for Graph based Social Recommendation
Yuhan Quan, Jingtao Ding, Chen Gao +3
Graph Neural Network(GNN) based social recommendation models improve the prediction accuracy of user preference by leveraging GNN in exploiting preference similarity contained in s…
A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions
Chen Gao, Yu Zheng, Nian Li +8
Recommender system is one of the most important information services on today's Internet. Recently, graph neural networks have become the new state-of-the-art approach to recommend…
TabGNN: Multiplex Graph Neural Network for Tabular Data Prediction
Xiawei Guo, Yuhan Quan, Huan Zhao +3
Tabular data prediction (TDP) is one of the most popular industrial applications, and various methods have been designed to improve the prediction performance. However, existing wo…
Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering
Jingtao Ding, Yuhan Quan, Quanming Yao +2
Negative sampling approaches are prevalent in implicit collaborative filtering for obtaining negative labels from massive unlabeled data. As two major concerns in negative sampling…