Recognize News Transition from Collective Behavior for News Recommendation.

The article focuses on enhancing news recommendation by addressing the issue of data sparsity in user behavior data. It discusses the integration of user-news relationships and user historical clicked news sequences to create a global heterogeneous transition graph and proposes the GAINRec model to improve news recommendations based on collective user behavior patterns, demonstrating its effectiveness in experiments.