Collaborative Filtering
Collaborative Filtering is a technique used in recommendation systems to predict a user's preferences based on the preferences of similar users. It is based on the assumption that people who have agreed in the past will agree in the future. Collaborative Filtering can be done in two ways: user-based and item-based. In user-based Collaborative Filtering, the system recommends items to a user based on the preferences of users who are similar to that user. In item-based Collaborative Filtering, the system recommends items to a user based on the preferences of that user for similar items. Collaborative Filtering is widely used in e-commerce, social media, and entertainment industries to provide personalized recommendations to users.
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