The recommendation system has become a cornerstone of modern e-commerce platforms, helping users discover products tailored to their preferences. This project focuses on building a product recommendation system leveraging graph neural networks (GNNs), particularly LightGCN, to improve prediction accuracy and scalability.
The system is designed to recommend products to users based on timestamp, user ids, product ids and ratings, providing a personalized shopping experience.
| اسم المستقل | Farah M. |
| عدد الإعجابات | 0 |
| عدد المشاهدات | 10 |
| تاريخ الإضافة | |
| تاريخ الإنجاز |
