Journal Article10.1016/J.INS.2021.01.083
Two-step hybrid collaborative filtering using deep variational Bayesian autoencoders
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TL;DR: A two-step hybrid variational Bayesian autoencoder is proposed to characterize the uncertainty of predicted ratings and stochastic variational inference is considered to approximate the posterior density of intractable user-item latent vectors.
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About: This article is published in Information Sciences. The article was published on 01 Jul 2021. The article focuses on the topics: Collaborative filtering & Autoencoder.
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Citations
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Evaluating collaborative filtering recommender systems
TL;DR: The key decisions in evaluating collaborative filtering recommender systems are reviewed: the user tasks being evaluated, the types of analysis and datasets being used, the ways in which prediction quality is measured, the evaluation of prediction attributes other than quality, and the user-based evaluation of the system as a whole.