A deep learning content-collaborative model for size and fit prediction that outperforms state-of-the-art on two public and two proprietary datasets.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2019 2verdicts
UNVERDICTED 2representative citing papers
NeuCDCF is a wide-and-deep neural architecture for cross-domain collaborative filtering that jointly learns matrix factorization and deep representations, reporting better performance than prior CDCF models on four real-world datasets.
citing papers explorer
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A Deep Learning System for Predicting Size and Fit in Fashion E-Commerce
A deep learning content-collaborative model for size and fit prediction that outperforms state-of-the-art on two public and two proprietary datasets.
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Neural Cross-Domain Collaborative Filtering with Shared Entities
NeuCDCF is a wide-and-deep neural architecture for cross-domain collaborative filtering that jointly learns matrix factorization and deep representations, reporting better performance than prior CDCF models on four real-world datasets.