I am creating a Recommender System and want to incorporate both the ratings of "similar" users and the features of the items. The output is a predicted rating [0-1].I am considering a Neural Network (to start with).
So, the inputs are a combination of the features of the items and the ratings of each user. For item A and user 1, the system could be trained on the combined data, A1. This would be one training example.
What if user 1 also rated movie B? Then would the data B1 also be a training example? Is there a problem with repeating the training with user 1's features in this way?
Do you have any suggestions about a better way to approach the problem?