A novel framework jointly captures flat and hierarchical side information in recommender systems and shows significant performance gains over state-of-the-art methods on real-world datasets.
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Recommender Systems with Heterogeneous Side Information
A novel framework jointly captures flat and hierarchical side information in recommender systems and shows significant performance gains over state-of-the-art methods on real-world datasets.