Matrix Factorization for Personalized Recommendation With Implicit Feedback and Temporal Information in Social Ecommerce Networks

Matrix Factorization for Personalized Recommendation With Implicit Feedback and Temporal Information in Social Ecommerce Networks

Collaborative filtering with implicit feedback is regarded as one of the most challenging issues in social ecommerce networks. However, the scarcity of negative feedback and the impact of time makes collaborative filtering difficult to use. Most models assign a uniform weight to missing data, but th...

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Bibliographic Details
Main Authors: Mingyang Li, Hongchen Wu, Huaxiang Zhang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Personalized recommendation in social computing
implicit feedback
collaborative filtering
temporal information
dynamic weight
matrix factorization
Online Access:https://ieeexplore.ieee.org/document/8850010/

Internet

https://ieeexplore.ieee.org/document/8850010/

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