When building a hybrid recommender for products, how do you ensure that the model doesn't just recommender the most popular products all the time? Would throwing out X% (where X is high) of transactions involving this popular product be a good idea? With a hybrid model, could this most popular product just be left out of the data entirely?
By hybrid recommender, I assume you mean a system that weights both a user's profile/behavior and item content. By its very nature, a hybrid recommender will use item content which is independent of popularity. Collaborative filtering recommends popular items among users with similar profile/behavior, which is not the same as overall popularity.