Collaborative filtering (CF) is a popular recommendation algorithm
that bases its predictions and recommendations on the ratings or behavior
of other users in the system. The fundamental assumption behind
this method is that other users’ opinions can be selected and aggregated
in such a way as to provide a reasonable prediction of the active user’s
preference. Intuitively, they assume that, if users agree about the quality
or relevance of some items, then they will likely agree about other
items — if a group of users likes the same things as Mary, then Mary
is likely to like the things they like which she hasn’t yet seen.