Question - Explain collaborative filtering in recommender systems.
Answer -
Collaborative filtering is a technique used to build recommender systems. In this technique, to generate recommendations, we make use of data about the likes and dislikes of users similar to other users. This similarity is estimated based on several varying factors, such as age, gender, locality, etc.
If User A, similar to User B, watched and liked a movie, then that movie will be recommended to User B, and similarly, if User B watched and liked a movie, then that would be recommended to User A.
In other words, the content of the movie does not matter much. When recommending it to a user what matters is if other users similar to that particular user liked the content of the movie or not.