推荐系统的深度学习:文献综述和观点

B. Selma, Boustia Narhimene, Rezoug Nachida
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引用次数: 2

摘要

在过去的几年里,深度学习彻底改变了几个领域,包括:图像分析、语音识别和语言处理。深度学习在推荐系统和信息检索领域也变得普遍和有效。与传统的推荐系统不同,深度学习具有独特的能力,可以成功捕获用户和物品之间的非平凡和非线性交互,从而允许对更复杂的抽象进行编码。我们首先简要概述推荐系统和深度学习。其次,我们对基于深度学习的RS的现状进行了全面的概述,然后描述了该领域未来可能的研究方向。最后,我们对本文进行总结。
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Deep Learning for Recommender Systems: Literature Review and Perspectives
During the last few years, deep learning revolutionized several fields including: image analysis, speech recognition and language processing. Deep learning has also become pervasive and demonstrated effectiveness in the field of recommender systems and information retrieval. Unlike the conventional recommendation systems, deep learning have the unique ability to successfully capture non-trivial and non-linear interactions between user and item, allowing for the codification of more complicated abstractions. We begin by providing a brief overview of recommender systems and deep learning. Second, we present a complete overview of the current state of the art in deep learning-based RS. Then, we describe a possible future research direction of the field. Finally, we conclude the review.
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