NPA applies CNN-based news encoding and personalized attention (word- and news-level) driven by user ID embeddings to improve click prediction on an MSN news dataset.
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2 Pith papers cite this work. Polarity classification is still indexing.
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cs.IR 2years
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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NPA: Neural News Recommendation with Personalized Attention
NPA applies CNN-based news encoding and personalized attention (word- and news-level) driven by user ID embeddings to improve click prediction on an MSN news dataset.
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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.