Interesting concept, guessing it's based on the same sort of user data as Amazon "users who liked X, also liked Y" system. Often thought that this would be a good fit for restaurants. i.e. I like Metallica, I'm 32, I like spicy food. Will I like this Korean restaurant?
Hi jamesfx4, I've got the answer you're looking for. The technology powering our recommendations does not use a collaborative filtering approach, such as Amazon's "users who liked X, also liked Y" solution. The recommendations are backed by artificial neural networks which have been tweaked to provide the best results at a personal level.
Added about two dozen ratings, checked my favorite IPA's and my least favorite ones. It nailed them with scores. Definitely using this over the weekend.
