title: Recommender system - mean average precision metric optimization
body: <p>I'm trying to build a recommender system that i must use off-line, on fixed training and test sets, and that i must evaluate with the precision metric. Each user gave some ratings (1-5 values), so I don't have null rows in the user ratings matrix. I must recommed items for the users in the test set, all of them are also present in the training set, and i must optimize the algorithm for the precision metric (in particular MAP@5, mean average precision). Someone, on the base of his experience, can give me an advice on the algorithm that I should use? And maybe also on how i should implement it, if I should use particular tools/libraries or a particular programming language.</p>