GNN-based Recommendation System
Published:
An advanced recommendation system that leverages Graph Neural Networks to tackle the cold-start problem. This project enhances traditional collaborative filtering methods with graph-based learning to improve recommendations for new users and items.
Key Features
- Dynamic graph layers for user-item interactions
- 20-D user/item embeddings for efficient representation
- 4.21% improvement in recommendation accuracy
- Recall@10 improved by 5.38% for sparse user histories
Technologies
- PyTorch Geometric
- Graph Neural Networks
- Collaborative filtering algorithms
- Python and deep learning frameworks