Comment by mhb
2 days ago
Ah. My fault. I put the whole URL in the User ID box instead of just the User ID.
Do you know how your model compares to Cinematch's SVD? Does your model use only books rated highly or also include low rated ones?
2 days ago
Ah. My fault. I put the whole URL in the User ID box instead of just the User ID.
Do you know how your model compares to Cinematch's SVD? Does your model use only books rated highly or also include low rated ones?
I am not familiar with Cinematch, is there a writeup about it? When training I used every input book and did not include ratings as a feature. In the future I want to experiment with treating 1 or 2 star ratings as negative feedback.
You can start reading here: https://en.wikipedia.org/wiki/Netflix_Prize
Netflix used to have a great recommendation engine based on what you liked/disliked. It included all of their members ratings. They had a contest in which they offered $1M to anyone who could improve their algorithm by 10%. The winning team used some kind of customized version of Singular Value Decomposition. The algorithm is public.
I think it is essential to use the negative ratings.