Enhancing Session-Based Recommendation with Lossless Gated Graph Neural Networks

The last decade has witnessed the emergence of Session-Based Recommendation (SBR) as a novel type of recommendation system (RS) that captures dynamic and shortterm user preferences within a session, aiming to offer more relevant and precise next-item recommendations. Recently, there has been a growing emphasis on utilising graph neural networks (GNN) to enhance SBR development. However, most GNN-b...