Hi All, I’ve been working through this MOOC and I have a question about recommender systems. Almost all of the literature I have read on recommender systems is on generating recommendations when you already have a set of ratings. But what if you are just starting out and have NO ratings yet?
Specifically, the problem I am trying to find a solution for has a huge set of products – where we have images and text descriptions and a ontology for the products. In addition, we have a set of 5 multiple choice questions that we ask of the user about their “personality”. The goal is to match the set of products to these personality answers. Of course in the medium and long term I want to use the implicit feedback to recommend products. But starting out I don’t have that. How can I build a recommender system that matches the answers to these questions to the right set of products in a meaningful way? Seems like I have to hard code some rules?