The neighborhood concept can be implemented in two ways: user neighbors or movie neighbors. User neighborhoods are based on a very simple concept: to know how a user will rate a movie, find the users most similar to them, and look at their ratings. We will only consider user neighbors for the moment. At the end of this section, we will discuss how the code can be adapted to compute movie neighbors.
One of the interesting techniques that we will now explore is to just see which movies each user has rated, even without taking a look at what rating was given. Even with a binary matrix where we have an entry equal to one when a user rates a movie, and zero when they do not, we can make useful predictions. In hindsight, this makes perfect sense—we do not completely randomly choose movies to watch, but instead pick those where we already...
