I am using spark MlLib ALS CF algorithm to build a recommender system for an e-commerce website.
I am required by the owner of the website, to sort for each individual user, all 4000 items in the catalog according to that user`s likelihood to buy them.
Spark`s CF algorithm allows me to do that, however, I suspect that after a few recommended items (say 30 for example), the order by which the algorithms sorts the items becomes pretty meaningless, and post that "magical" point, I am better off sorting the items by their general global popularity.
My question: How can I find that "magical point"? Should it be different for each user?
I know this question might be a bit theoretical, but I would appreciate any thought on this matter.
