Recommender Systems: A Review

Abstract

Recommender systems are the engine of online advertising. Not only do they suggest movies, music, or romantic partners, but they also are used to select which advertisements to show to users. This paper reviews the basics of recommender system methodology and then looks at the emerging arena of active recommender systems.

Keywords:

• Collaborative filtering
• Content-based filtering
• Conversational recommender systems
• MovieLens data
• Probabilistic matrix factorization

Disclosure Statement

None of the authors received financial support from a grant for writing this article, and none of the authors have a conflict of interest.