Entity-driven recommendations use a knowledge graph to model users, content items, and their interrelationships as distinct entities. This creates a rich, semantic understanding of affinity, moving past simple co-viewership to model why a user prefers certain content—based on shared topics, authors, or underlying concepts. The core components are a user-entity affinity model, which profiles interests based on past interactions, and a content entity graph, which structures articles, products, or media by their core attributes and relationships.
