Global and Local Tensor Factorization for Multi-criteria Recommender System

Global and Local Tensor Factorization for Multi-criteria Recommender System

Summary: 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...

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Bibliographic Details
Main Authors:	Shuliang Wang, Jingting Yang, Zhengyu Chen, Hanning Yuan, Jing Geng, Zhen Hai
Format:	Article
Language:	English
Published:	Elsevier 2020-05-01
Series:	Patterns
Subjects:	recommender systems multi-criteria recommender systems matrix factorization tensor factorization global and local tensor factorization (GLTF) big data
Online Access:	http://www.sciencedirect.com/science/article/pii/S2666389920300234

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