Session Context

Session context in recommender systems focuses on understanding and leveraging the implicit or explicit information within a user's interaction sequence (a "session") to improve prediction accuracy of their next action, such as purchasing an item or clicking a link. Current research emphasizes incorporating diverse contextual information, including item attributes, session attributes, and relationships between items within and across sessions, often using graph neural networks or other advanced embedding techniques to model these complex relationships. This research is significant because accurately capturing session context leads to more personalized and effective recommendations, improving user experience and the performance of online platforms.