Nowadays, more and more news readers read news online where they have access to
millions of news articles from multiple sources. In order to help users find the right and …

This paper provides an extensive and thorough overview of the models and techniques
utilized in the first and second stages of the typical information retrieval processing chain …

Graph neural network (GNN) is widely used for recommendation to model high-order
interactions between users and items. Existing GNN-based recommendation methods rely …

News recommendation is an important technique for personalized news service. Compared
with product and movie recommendations which have been comprehensively studied, the …

Graph neural network (GNN) is effective in modeling high-order interactions and has been
widely used in various personalized applications such as recommendation. However …

Personalized news recommendation is an essential technique for online news services.
News articles usually contain rich textual content, and accurate news modeling is important …

Unsupervised graph representation learning (UGRL) has drawn increasing research
attention and achieved promising results in several graph analytic tasks. Relying on the …

Personalized news recommendation is important for users to find interesting news
information and alleviate information overload. Although it has been extensively studied …

The most important task in personalized news recommendation is accurate matching
between candidate news and user interest. Most of existing news recommendation methods …

User interest modeling is critical for personalized news recommendation. Existing news
recommendation methods usually learn a single user embedding for each user from their …