Back to Search Start Over

Recommender Systems: A Review.

Authors :
LeBlanc, Patrick M.
Banks, David
Fu, Linhui
Li, Mingyan
Tang, Zhengyu
Wu, Qiuyi
Source :
Journal of the American Statistical Association. Mar2024, Vol. 119 Issue 545, p773-785. 13p.
Publication Year :
2024

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01621459
Volume :
119
Issue :
545
Database :
Academic Search Index
Journal :
Journal of the American Statistical Association
Publication Type :
Academic Journal
Accession number :
175846074
Full Text :
https://doi.org/10.1080/01621459.2023.2279695