Graph Neural Networks based Recommendation Methods in Different Scenarios: A Survey

Abstract

Recommendation system is one of the most important service applications in the world, and graph neural network is currently the most popular research direction in the field of recommendation system. In this survey, we conduct a literature survey on graph neural network-based recommender systems. Firstly, we introduce the classification for graph neural networks. Secondly, different recommendation scenarios in the recommendation system are introduced, and the challenges faced by graph neural networks in different recommendation scenarios are analyzed. Finally, the solutions to these challenges are summarized.