A Privacy-Preserving Multi-Task Framework for Knowledge Graph Enhanced Recommendation

A Privacy-Preserving Multi-Task Framework for Knowledge Graph Enhanced Recommendation

Multi-task learning (MTL) is a learning paradigm which can improve generalization performance by transferring knowledge among multiple tasks. Traditional collaborative filtering recommendation methods suffer from cold start, sparsity and scalability problems. The latest research has shown that apply...

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Bibliographic Details
Main Authors: Bin Yu, Chenyu Zhou, Chen Zhang, Guodong Wang, Yiming Fan
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Recommendation system
differential privacy
multi-task learning
Online Access:https://ieeexplore.ieee.org/document/9122494/

Internet

https://ieeexplore.ieee.org/document/9122494/

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