Analyzing and Mitigating Asymmetric Learning for Product Cold-Start in E-Commerce Purchase Prediction with Graph Neural Networks: Similarity-Driven History Augmentation
Graph Neural Networks (GNNs) have become a foundational tool for e-commerce recommendation systems, yet they consistently fail in zero-shot cold-start scenarios where new products enter the market without prior interactions. In this paper, we diagnose this failure as a structural vulnerability rather than a simple data...