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AspeRa: Aspect-based Rating Prediction Model
[article]
2019
arXiv
pre-print
We propose a novel end-to-end Aspect-based Rating Prediction model (AspeRa) that estimates user rating based on review texts for the items and at the same time discovers coherent aspects of reviews that can be used to explain predictions or profile users. The AspeRa model uses max-margin losses for joint item and user embedding learning and a dual-headed architecture; it significantly outperforms recently proposed state-of-the-art models such as DeepCoNN, HFT, NARRE, and TransRev on two real
arXiv:1901.07829v1
fatcat:tjydwynebbbcxjkidogbmjpyqq