Recommender Systems Clustering Using Bayesian Non Negative Matrix Factorization

Recommender Systems Clustering Using Bayesian Non Negative Matrix Factorization

Recommender Systems present a high-level of sparsity in their ratings matrices. The collaborative filtering sparse data makes it difficult to: 1) compare elements using memory-based solutions; 2) obtain precise models using model-based solutions; 3) get accurate predictions; and 4) properly cluster...

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Bibliographic Details
Main Authors: Jesus Bobadilla, Rodolfo Bojorque, Antonio Hernando Esteban, Remigio Hurtado
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Bayesian NMF
collaborative filtering
hard clustering
matrix factorization
pre-clustering
recommender systems
Online Access:https://ieeexplore.ieee.org/document/8241787/

Internet

https://ieeexplore.ieee.org/document/8241787/

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