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A Correlative Denoising Autoencoder to Model Social Influence for Top-N Recommender System
Towards this problem, we propose a novel Correlative Denoising Autoencoder (CoDAE) method by taking correlations between users with multiple roles into account to learn robust representations from sparse inputs of ratings and social networks for recommendation.
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