2021
DOI: 10.1145/3467023
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Collaborative Reflection-Augmented Autoencoder Network for Recommender Systems

Abstract: As the deep learning techniques have expanded to real-world recommendation tasks, many deep neural network based Collaborative Filtering (CF) models have been developed to project user-item interactions into latent feature space, based on various neural architectures, such as multi-layer perceptron, autoencoder, and graph neural networks. However, the majority of existing collaborative filtering systems are not well designed to handle missing data. Particularly, in order to inject the negative signals in the t… Show more

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Cited by 6 publications
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References 43 publications
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