Collaborative Filtering

Collaborative filtering is a technique used in recommendation systems to predict a user's interests by collecting preferences from many users. It operates on the principle that if two users have similar preferences in the past, they are likely to have similar preferences in the future. This method can be user-based, where recommendations are made based on similar users, or item-based, where recommendations are based on similar items. Common use cases include movie recommendations on streaming platforms, product recommendations in e-commerce, and content suggestions on social media. Collaborative filtering is essential for personalizing user experiences and enhancing engagement.