Efficient and Bias-aware Recommendation with Two-side Relevance for Implicit Feedback

Guanyu Lin, Lei Huang, Yuting Yin, Chengmin Zhang, Feng Zhu, Lingqi Kong, Zhiheng Li

2021 IEEE 2nd International Conference on Pattern Recognition and Machine Learning (PRML)（2021）

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摘要

Today’s wide-spread recommendation is usually constructed based on implicit data such as click for easy collection but whether the no clicked data is negative feedback or unobserved positive feedback confuses the model construction. As a response, Relevance Matrix Factorization (Rel-MF) is recently proposed to tackle this problem as well as the missing-not-at-random (MNAR) problem ignored by previ...

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关键词

Negative feedback,Conferences,Estimation,Machine learning,Data models,Pattern recognition

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