  Attribute-aware CF models aims at rating prediction given not only the
historical rating from users to items, but also the information associated with
users (e.g. age), items (e.g. price), or even ratings (e.g. rating time). This
paper surveys works in the past decade developing attribute-aware CF systems,
and discovered that mathematically they can be classified into four different
categories. We provide the readers not only the high level mathematical
interpretation of the existing works in this area but also the mathematical
insight for each category of models. Finally we provide in-depth experiment
results comparing the effectiveness of the major works in each category.
