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.
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