1.5k citations · 6.3k across the 35 of their papers we have counts for
5 papers · 1 filter
Multi-Stage Network Embedding for Exploring Heterogeneous Edges
Hong Huang, Yu Song, Fanghua Ye +3
The relationships between objects in a network are typically diverse and complex, leading to the heterogeneous edges with different semantic information. In this paper, we focus on…
HieRec: Hierarchical User Interest Modeling for Personalized News Recommendation
Tao Qi, Fangzhao Wu, Chuhan Wu +4
User interest modeling is critical for personalized news recommendation. Existing news recommendation methods usually learn a single user embedding for each user from their previou…
DebiasedRec: Bias-aware User Modeling and Click Prediction for Personalized News Recommendation
Jingwei Yi, Fangzhao Wu, Chuhan Wu +3
News recommendation is critical for personalized news access. Existing news recommendation methods usually infer users' personal interest based on their historical clicked news, an…
FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation
Chuhan Wu, Fangzhao Wu, Yang Cao +2
Graph neural network (GNN) is widely used for recommendation to model high-order interactions between users and items. Existing GNN-based recommendation methods rely on centralized…
Neural News Recommendation with Negative Feedback
Chuhan Wu, Fangzhao Wu, Yongfeng Huang +1
News recommendation is important for online news services. Precise user interest modeling is critical for personalized news recommendation. Existing news recommendation methods usu…