Recommendation systems based on collaborative filtering can suffer from the "cold start" problem.Review LaterTrueFalse

Which technique is more effective in handling the "cold start" problem in Recommendation Systems?Review LaterCollaborative FilteringMatrix FactorizationContent-Based FilteringHybrid Filtering

The difficulty in recommendation when we have new user, and we cannot make a profile for him, or when we have a new item, which has not got any rating yet.This is the meaning of Cold-start problem.Review LaterTrueFalse

Which of the following techniques is commonly used in Recommendation Systems to suggest items based on user similarities?Review LaterCollaborative FilteringMatrix FactorizationContent-Based FilteringHybrid Filtering

Which technique considers the characteristics and features of items to make recommendations based on their similarity to previously liked items by the user?Review LaterCollaborative filteringContent-based filteringActive learningReinforcement learning

Which type of collaborative filtering algorithm utilizes item-item similarities to generate recommendations?Question 23Answera. Item-based collaborative filteringb.Matrix factorizationc.Content-based filteringd.User-based collaborative filtering