Recommender Systems: A Review

Patrick M. LeBlanc, David Banks, Linhui Fu, Mingyan Li, Zhengyu Tang, Qiuyi Wu
January, 2023
PDF Cite Code DOI
Image credit: online source

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.

Type
Journal article
Publication
Journal of the American Statistical Association
Collaborative filtering Content-based filtering Conversational recommender systems MovieLens data Probabilistic matrix factorization
Qiuyi Wu
Qiuyi Wu
Postdoc Research Fellow

My research interests include functional data analysis, image processing and high dimensional data anlaysis.