Recommendation Scenario

Recommendation systems aim to predict user preferences and provide personalized suggestions, focusing on accurately modeling user behavior and context to improve the relevance and effectiveness of recommendations. Current research emphasizes incorporating advanced techniques like large language models (LLMs) and graph neural networks (GNNs) to better understand user interests from diverse data sources (e.g., text, interactions, temporal patterns), as well as addressing challenges like cold-start problems and mitigating biases. These advancements are crucial for enhancing user experience across various applications, from e-commerce and streaming services to online-to-offline platforms, and are driving improvements in recommendation accuracy and efficiency.