A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions

Recommender system is one of the most important information services on today’s Internet. Recently, graph neural networks have become the new state-of-the-art approach to recommender systems. In this survey, we conduct a comprehensive review of the literature on graph neural network-based recommender systems. We first introduce the background and the history of the development of both recommender systems and graph neural networks. For recommender systems, in general, there are four aspects for categorizing existing works: stage, scenario, objective, and application. For graph neural networks, the existing methods consist of two categories: spectral models and spatial ones. We then discuss the motivation of…

• NN
  National Natural Science Foundation of China

  Award: U19A2079
• CP
  China Postdoctoral Science Foundation

  Award: 2021TQ0027 and 2022M710006
• NK
  National Key Research and Development Program of China

  Award: 2020AAA0106000