Graph Learning Approaches to Recommender Systems: A Review

Understand

Recent years have witnessed the fast development of the emerging topic of Graph Learning based Recommender Systems (GLRS).

• GLRS mainly employ the advanced graph learning approaches to model users' preferences and intentions as well as items' characteristics and popularity for Recommender Systems (RS).
• Differently from conventional RS, including content based filtering and collaborative filtering, GLRS are built on simple or complex graphs where various objects, e.g., users, items, and attributes, are explicitly or implicitly connected.
• With the rapid development of graph learning, exploring and exploiting homogeneous or heterogeneous relations in graphs is a promising direction for building advanced RS.