What is the standard way for evaluating and comparing different algorithms while developing recommendation system? Whether we need to have a predetermined annotated ranked dataset and then compare with precision/recall/F measure of  different algorithms ? Is this the best way for evaluation ? Or is there any other way to compare results of various recommendation algorithms ?
Evaluating Recommendation engines
machine learning;data mining;dataset;statistics;recommender system