Collaborative filtering is a branch of recommendation that takes account of the information about different users. The word "collaborative" refers to the fact that users collaborate with each other to recommend items. In fact, the algorithms take account of user purchases and preferences. The starting point is a rating matrix in which rows correspond to users and columns correspond to items.
This section will show you an example of item-based collaborative filtering. Given a new user, the algorithm considers the user's purchases and recommends similar items. The core algorithm is based on these steps: