  In this paper, we present a novel structure, Semi-AutoEncoder, based on
AutoEncoder. We generalize it into a hybrid collaborative filtering model for
rating prediction as well as personalized top-n recommendations. Experimental
results on two real-world datasets demonstrate its state-of-the-art
performances.
