WebXiang Wang (National University of Singapore) Title: Graph Neural Networks for Recommendation Abstract: Graph Neural Networks (GNNs) have achieved remarkable success in many domains and shown great potentials in personalized recommendation. In this talk, I will give a brief introduction on why GNNs are suitable for recommendation, … WebChuhan Wu, Fangzhao Wu, Tao Qi, and Yongfeng Huang: Two Birds with One Stone: Unified Model Learning for Both Recall and Ranking in News Recommendation. Findings of ACL 2024. Chuhan Wu, Fangzhao Wu, …

Graph Neural News Recommendation with User Existing and …

WebApr 14, 2024 · Convolutional Neural Networks (CNNs) have been recently introduced in the domain of session-based next item recommendation. An ordered collection of past items the user has interacted with in a ... WebJul 22, 2024 · Therefore, we propose an attention-based graph neural network news recommendation model. In our model, muti-channel convolutional neural network is used to generate news representations, and recurrent neural network is used to extract the news sequence information that users clicked on. simply be cocktail dresses

MVL: Multi-View Learning for News Recommendation

WebApr 14, 2024 · Convolutional Neural Networks (CNNs) have been recently introduced in the domain of session-based next item recommendation. An ordered collection of past … WebJan 4, 2024 · Graph Neural Networks (GNN) have shown remarkable performance in different tasks. However, there are a few studies about GNN on recommender systems. GCN as a type of GNNs can extract high-quality embeddings for different entities in a graph. WebOct 30, 2024 · Graph Neural News Recommendation with Long-term and Short-term Interest Modeling. With the information explosion of news articles, personalized news … simplybe.com payment