30 citations · 51 across the 7 of their papers we have counts for
4 papers · 1 filter
Modeling Multi-interest News Sequence for News Recommendation
Rongyao Wang, Wenpeng Lu
A session-based news recommender system recommends the next news to a user by modeling the potential interests embedded in a sequence of news read/clicked by her/him in a session.…
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…
Jointly Modeling Intra- and Inter-transaction Dependencies with Hierarchical Attentive Transaction Embeddings for Next-item Recommendation
Shoujin Wang, Longbing Cao, Liang Hu +4
A transaction-based recommender system (TBRS) aims to predict the next item by modeling dependencies in transactional data. Generally, two kinds of dependencies considered are intr…