Which technique is suitable for providing recommendations in the absence of user-item interaction data?Review LaterCollaborative FilteringContent-Based FilteringMatrix FactorizationHybrid Filtering

Which technique aims to fill in missing entries in a user-item interaction matrix to generate personalized recommendations?Review LaterHybrid FilteringMatrix FactorizationCollaborative FilteringNone of the above

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 is more effective in handling the "cold start" problem in Recommendation Systems?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