What should the Specialist do to meet this objective?
Build a content-based filtering recommendation engine with Apache Spark ML on Amazon EMR
Build a collaborative filtering recommendation engine with Apache Spark ML on Amazon EMR.
Build a model-based filtering recommendation engine with Apache Spark ML on Amazon EMR
Build a combinative filtering recommendation engine with Apache Spark ML on Amazon EMR
Explanations:
Content-based filtering recommends products based on individual users’ preferences and behaviors rather than user similarity. It doesn’t rely on user interactions with other users.
Collaborative filtering uses the similarity between users (or items) to make recommendations. This approach fits the objective of predicting products based on user similarity.
Model-based filtering is a broader category that involves building predictive models (e.g., matrix factorization), but it isn’t specific to user similarity as collaborative filtering is.
Combinative filtering is not a standard term in recommendation systems and is not an established method for making predictions based on user similarity.