Collaborative Filtering

Collaborative filtering is a technique used in Recommender Systems to make automatic predictions about the interests of a user by collecting preferences from many users. It is based on the idea that users who have agreed in the past tend to agree again in the future.


  • Collaborative filtering can be categorized into two types:
    • user-based: User-based collaborative filtering recommends items to a user that similar users have liked.
    • item-based: Item-based collaborative filtering recommends items similar to those that a user has liked.
  • Collaborative filtering is widely used in e-commerce, social media, and content streaming platforms to provide personalized recommendations to users based on their preferences and behavior.