6 citations · 6 across the 4 of their papers we have counts for
4 papers
Graph Neural Networks Intersect Probabilistic Graphical Models: A Survey
Chenqing Hua, Sitao Luan, Qian Zhang +1
Graphs are a powerful data structure to represent relational data and are widely used to describe complex real-world data structures. Probabilistic Graphical Models (PGMs) have bee…
Modeling Complex Dependencies for Session-based Recommendations via Graph Neural Networks
Qian Zhang, Wenpeng Lu
Session-based recommendations (SBRs) capture items' dependencies from the sessions to recommend the next item. In recent years, Graph neural networks (GNN) based SBRs have become t…
Aspect-driven User Preference and News Representation Learning for News Recommendation
Rongyao Wang, Wenpeng Lu, Shoujin Wang +3
News recommender systems are essential for helping users to efficiently and effectively find out those interesting news from a large amount of news. Most of existing news recommend…
Causality-Aware Neighborhood Methods for Recommender Systems
Masahiro Sato, Sho Takemori, Janmajay Singh +1
The business objectives of recommenders, such as increasing sales, are aligned with the causal effect of recommendations. Previous recommenders targeting for the causal effect empl…