I have a solid user-item matrix, with which I have build a collaborative filtering recommender system. I also have for each item a number of high quality features.
If a new user comes to the website (online store), I quickly want to find out his taste. Currently I do this by asking 20 questions, in which I ask him to select his most preferred product out of 4 options.
How can you use the item features and the information in the user-item matrix (and it derivaties: product popularities and latent features) to set up an efficient questionnaire to get to know the user his taste?
For example, you want to find out if the user likes popular products. So in each question with 4 options, you want to make sure there is one popular product in it, and one non popular product. But there are many features, and I am looking for a method that makes sure there is as much variation as possible in all the questions, so you learn as fast as possible.
My question is inspired by the implementation of the game 20 questions, http://www.20q.com, where you also want to ask the question that eliminates to most of the potential concepts that the user can have in mind.
Can you guide me towards some concepts or solutions?