RMPD: Method for Enhancing the Robustness of Recommendations With Attack Environments

RMPD: Method for Enhancing the Robustness of Recommendations With Attack Environments

Personalized item recommendation has become a hot topic research among academic and industry community. But lots of purposeful fraudsters maybe perform different attacks on the recommender system to insert fake ratings, which could reduce the authenticity and reliability of recommendations. For a re...

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Bibliographic Details
Main Authors: Qi Ding, Peiyu Liu, Zhenfang Zhu, Huajuan Duan, Fuyong Xu
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Deep neural networks
matrix decomposition
recommender system
robustness
Online Access:https://ieeexplore.ieee.org/document/9334992/

Internet

https://ieeexplore.ieee.org/document/9334992/

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