Multi Scenario Recommendation

Multi-scenario recommendation (MSR) aims to improve personalized recommendations by leveraging data across diverse contexts or "scenarios," such as different platforms, user interfaces, or product categories. Current research focuses on developing models that effectively integrate information from multiple scenarios, often employing techniques like graph neural networks, multi-task learning, and large language models to capture cross-scenario relationships and user preferences. These advancements address challenges like cold-start problems and data imbalance, leading to more accurate and robust recommendation systems with improved performance metrics in various applications, including e-commerce and online video platforms.