Robust Cost-Sensitive Learning for Recommendation with Implicit Feedback

  title={Robust Cost-Sensitive Learning for Recommendation with Implicit Feedback},
  author={Peng Yang and Peilin Zhao and Xin Gao and Yong Liu},
Recommendation is the task of improving customer experience through personalized recommendation based on users' past feedback. In this paper, we investigate the most common scenario: the user-item (U-I) matrix of implicit feedback. Even though many recommendation approaches are designed based on implicit feedback, they attempt to project the U-I matrix into a low-rank latent space, which is a strict restriction that rarely holds in practice. In addition, although misclassification costs from… 

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