Research on Deep Learning-Based Personalized Recommendation Systems

Traditional methods have struggled to meet the increasingly diverse needs of users and industry development, particularly on short video platforms. This paper investigates the application of deep learning-based recommendation systems in the domain of video recommendations and their impact on user experience. It explores how different deep learning algorithms can be utilized to understand user preferences, analyze video content, and subsequently provide personalized recommendations. The study evaluates the accuracy and efficiency of these systems and investigates potential optimization strategies. The aim of this research is to provide a comprehensive perspective on how deep learning-based recommendation systems function in the short video environment and to discuss their future development directions.