Global and Local Tensor Factorization for Multi-criteria Recommender System

In multi-criteria recommender systems, matrix factorization characterizes users and items via latent factor vectors inferred from user-item rating patterns. However, two-dimensional matrix factorization models may not be able to cope with the recommendation problem that involves additional criterion...

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Detalles Bibliográficos
Autores principales: Wang, Shuliang, Yang, Jingting, Chen, Zhengyu, Yuan, Hanning, Geng, Jing, Hai, Zhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660452/
https://www.ncbi.nlm.nih.gov/pubmed/33205096
http://dx.doi.org/10.1016/j.patter.2020.100023

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660452/
https://www.ncbi.nlm.nih.gov/pubmed/33205096
http://dx.doi.org/10.1016/j.patter.2020.100023

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