Collaborative filtering (user-based)

User-based collaborative filtering is a method used by recommendation systems to suggest items by finding users with similar preferences. It works by analyzing a user's past choices and comparing them to other users' preferences. If many users with similar tastes liked a particular movie, product, or song, the system recommends that item to the user. Essentially, it leverages the collective behavior and opinions of like-minded individuals to make personalized suggestions, assuming people with similar interests will enjoy similar things.