Recommendation Model Based on Probabilistic Matrix Factorization, Integrating User Trust Relationship, Interest Mining, and Item Correlation

Recommendation Model Based on Probabilistic Matrix Factorization, Integrating User Trust Relationship, Interest Mining, and Item Correlation

Personalized recommendation has gained widespread attention in the academic and industrial fields to minimize information overload and has produced good benefits. Current research shows that social recommendations that effectively utilize user trust relationships can solve data sparsity and cold sta...

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Bibliographic Details
Main Authors: Lifeng Han, Li Chen, Xiaolong Shi
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Correlation relationship
direct trust
indirect trust
heterogeneous network
probability matrix factorization
user interest
Online Access:https://ieeexplore.ieee.org/document/9992003/

Internet

https://ieeexplore.ieee.org/document/9992003/

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