Knowledge graphs (KGs) can help enhance recommendations, especially for the data-
sparsity scenarios with limited user-item interaction data. Due to the strong power of …

Knowledge Graphs (KGs) have emerged as invaluable resources for enriching
recommendation systems by providing a wealth of factual information and capturing …

Knowledge graph (KG) plays an increasingly important role in recommender systems.
Recently, graph neural networks (GNNs) based model has gradually become the theme of …

Recommender system (RS) devotes to predicting user preference to a given item and has
been widely deployed in most web-scale applications. Recently, knowledge graph (KG) …

Knowledge graph (KG) enhanced recommendation, which aims to solve the cold start and
explainability in recommender systems, has attracted considerable research interest …

Abstract Knowledge graph (KG)-based recommendation models generally explore auxiliary
information to alleviate the sparsity and cold-start problems in recommender systems …

Incorporating knowledge graph as side information has become a new trend in
recommendation systems. Recent studies regard items as entities of a knowledge graph and …

Abstract Knowledge graph-aware recommendation has become an important research topic
in recent years. The user preference representation, which preserves the user's taste …

To alleviate data sparsity and cold-start problems of traditional recommender systems (RSs),
incorporating knowledge graphs (KGs) to supplement auxiliary information has attracted …

Knowledge graphs (KGs) have been proven to be effective for improving the performance of
recommender systems. KGs can store rich side information and relieve the data sparsity …