Deep Heterogeneous Autoencoders for Collaborative Filtering

17 Dec 2018Tianyu LiYukun MaJiu XuBjorn StengerChen LiuYu Hirate

This paper leverages heterogeneous auxiliary information to address the data sparsity problem of recommender systems. We propose a model that learns a shared feature space from heterogeneous data, such as item descriptions, product tags and online purchase history, to obtain better predictions... (read more)

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