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• W2893085659 abstract "We describe a novel, multi-task recommendation model, which jointly learns to perform rating prediction and recommendation explanation by combining matrix factorization, for rating prediction, and adversarial sequence to sequence learning for explanation generation. The result is evaluated using real-world datasets to demonstrate improved rating prediction performance, compared to state-of-the-art alternatives, while producing effective, personalized explanations." @default.
• W2893085659 created "2018-10-05" @default.
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• W2893085659 date "2018-09-27" @default.
• W2893085659 modified "2023-10-17" @default.
• W2893085659 title "Why I like it" @default.
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• W2893085659 doi "https://doi.org/10.1145/3240323.3240365" @default.
• W2893085659 hasPublicationYear "2018" @default.
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