To solve the information explosion problem and enhance user experience in various online
applications, recommender systems have been developed to model users' preferences …

Recommender systems have emerged as indispensable tools for information filtering, and
the integration of knowledge graphs for auxiliary information is becoming an increasingly …

Recently, much attention has been paid to the usage of knowledge graph within the context
of recommender systems to alleviate the data sparsity and cold-start problems. However …

In recent years, the use of recommender systems has become popular on the web. To
improve recommendation performance, usage, and scalability, the research has evolved by …

Incorporating knowledge graph (KG) into recommender system is promising in improving the
recommendation accuracy and explainability. However, existing methods largely assume …

Incorporating knowledge graph into recommender systems has attracted increasing
attention in recent years. By exploring the interlinks within a knowledge graph, the …

Recent advances in research have demonstrated the effectiveness of knowledge graphs
(KG) in providing valuable external knowledge to improve recommendation systems (RS). A …

Abstract Knowledge graphs have shown to be highly beneficial to recommender systems,
providing an ideal data structure to generate hybrid recommendations using both content …

To address the sparsity and cold start problem of collaborative filtering, researchers usually
make use of side information, such as social networks or item attributes, to improve …

Abstract Knowledge graphs (KGs) have proven to be effective for high-quality
recommendation, where the connectivities between users and items provide rich and …