A Novel Learning Model Based on Trust Diffusion and Global Item for Recommender Systems

A Novel Learning Model Based on Trust Diffusion and Global Item for Recommender Systems

Recommender systems can provide users with an ordered list of various items, which greatly assists users to purchase products that they are satisfied with. However, item recommendation has been confronted with some inherent problems, such as sparse ratings and long-tail distribution, resulting in lo...

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Bibliographic Details
Main Authors: Yakun Li, Jiaomin Liu, Jiadong Ren
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Recommender system
sparse data
trust diffusion
global item
item rating prediction
Online Access:https://ieeexplore.ieee.org/document/8911514/

Internet

https://ieeexplore.ieee.org/document/8911514/

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