Quantifying Aspect Bias in Ordinal Ratings using a Bayesian Approach

15 May 2017 Lahari Poddar Wynne Hsu Mong Li Lee

User opinions expressed in the form of ratings can influence an individual's view of an item. However, the true quality of an item is often obfuscated by user biases, and it is not obvious from the observed ratings the importance different users place on different aspects of an item... (read more)

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