Magic barrier estimation models for recommended systems under normal distribution

Yan-Xue Wu
Yan-Xue Wu
Zhuo-Lin Fu
Zhuo-Lin Fu

Appl. Intell., Volume 48, Issue 12, 2018, Pages 4678-4693.

Cited by: 2|Bibtex|Views4|Links
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Keywords:
Magic barrierNormal distributionRecommender systemUser uncertainty

Abstract:

Real data are usually imperfect. The inherent nature of data determines the magical barrier of a machine learning task. In this paper, we propose three normal distribution models to estimate the magic barrier of recommender systems in terms of mean absolute error (MAE). The first model assumes that the users’ ratings are all subject to th...More

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