A Review of Research on the Application of Knowledge Graphs in Recommender Systems

This paper reviews the application of knowledge graphs in recommender systems, focusing on the advantages, common types, key technologies, and application cases of knowledge graph-based recommender systems. First, the definition, characteristics, and construction method of knowledge graphs are introduced. Then, the current research status of knowledge graph-based recommender system is elaborated in detail, including its advantages, common types, and application cases. Then, the key technologies of the knowledge graph-based recommender systems are discussed in depth, such asrepresentation learning of knowledge graphs, representation learning of users and items, recommendation algorithms based on graph neural networks, and model evaluation. Finally, challenges and future trends in the field are discussed. The aim of this paper is to provide a more comprehensive overview of the research on the application of knowledge graphs in recommender systems in order to promote the further development of the field.