Intelligent Recommendation
We leverage advanced Graph Neural Networks (GNN) technology to
explore the relationships between user preferences and behaviors.
Simultaneously, we employ Graph Convolutional Networks (GCN) to
capture user-item interactions, thereby enhancing recommendation
accuracy. With a Transformer-based attention mechanism, we focus
on key information, understand complex user preferences, and
deliver personalised recommendations. Through Reinforcement
Learning (RL), the recommendation system learns through user
interaction, dynamically adjusts strategies, and optimizes
long-term recommendation effectiveness.