All, seeking some advice on collaborative filtering problem! I’m trying to build a recommender for users with around 1,500 features they may or may not have, and so are boolean rather than numerical.
Eg, a user may select feature 1, 2 and 3, and I’d like to recommend that other users who have those also have 5,6 and 7.
My question is how I prepare the data…the tutorial based on netflix movies obviously has each movie as either watched with a rating, or absent. In my data however, I’m treated each user as having or not having each and every skill. Eg, if in my training set a user has feature 2,3 and 4, I assume they do not have every other feature (rather than them being absent).
Does that make sense? Is there a better way to approach collaborative filtering with a large number of boolean features?