Pre-training Graph Transformer with Multimodal Side Information for Recommendation

Understand

Side information of items, e.g., images and text description, has shown to be effective in contributing to accurate recommendations.

• Inspired by the recent success of pre-training models on natural language and images, we propose a pre-training strategy to learn item representations by considering both item side information and their relationships.
• We relate items by common user activities, e.g., co-purchase, and construct a homogeneous item graph.
• This graph provides a unified view of item relations and their associated side information in multimodality.