Building a Recommender System Using LightGCN
Recommender systems have become an integral part of modern online platforms, with the goal of providing personalized recommendations to users based on their interests and past interactions. These systems can be found in a variety of applications, including suggesting products to purchase on e-commerce websites, recommending content to watch on streaming services, and suggesting connections to make on social media platforms.
Recommendation systems are one of the main applications of GNNs. Indeed, they can effectively incorporate the complex relationships between users, items, and their interactions into a unified model. In addition, the graph structure allows for the incorporation of side information, such as user and item metadata, into the recommendation process.
In this chapter, we will introduce a new GNN architecture called LightGCN, specifically designed for recommender systems. We will also introduce a new dataset, the Book-Crossing...
