Top-N recommendations from expressive recommender systems

Understand

Normalized nonnegative models assign probability distributions to users and random variables to items; see [Stark, 2015].

• Rating an item is regarded as sampling the random variable assigned to the item with respect to the distribution assigned to the user who rates the item.
• Models of that kind are highly expressive.
• For instance, using normalized nonnegative models we can understand users' preferences as mixtures of interpretable user stereotypes, and we can arrange properties of users and items in a hierarchical manner.