I have data on content-based recommendations of movies and their attributes.
Suppose a user likes x,y and z and also dislikes c and d movies. I want to predict movies that he will like based on his likes and dislikes.
It is actually quite easy to find similar items if the only interaction were a movie like, because I would then be looking at the closest items to x movie by calculating distances via attributes. But it is quite confusing when interactions are multiple and based on both likes and dislikes.
What is the right approach in that case ?