Comprehensive Evaluation of Matrix Factorization Models for Collaborative Filtering Recommender Systems.

Matrix factorization models are the core of current commercial collaborative filtering Recommender Systems. This paper tested six representative matrix factorization models, using four collaborative filtering datasets. Experiments have tested a variety of accuracy and beyond accuracy quality measur...

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Bibliographic Details

Main Authors:	Jesús Bobadilla, Jorge Dueñas Lerín, Fernando Ortega, Abraham Gutierrez
Format:	Artigo
Language:	Inglês
Published:	Universidad Internacional de La Rioja (UNIR) 2024-06-01
Series:	International Journal of Interactive Multimedia and Artificial Intelligence
Subjects:	Collaborative Filtering Matrix Factorization Recommendation Systems
Online Access:	https://www.ijimai.org/index.php/ijimai/article/view/301
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