Performance metric in recommender systems with implicit feedback
I think your post is missing a clear question. 

I'll answer your concerns anyway:


For a implicit feedback problem like the one described RMSE, indeed, doesn't make much sense. First of all it is not clear what the difference between the real value (number of interactions, e.g. watched movie 4 times) and the estimation would mean. Second, in recommender systems you usuallly want to give the user 10-20 relevant recommendations and you don't care for the rest. Hence, it makes sense to optimize your algorithm to get these top recommendations right while disregarding your performance further down in the ranking. 
See my first answer. Also, the authors of your cited paper argue for a rank-based metric.