Abstract
Recommender systems (RSs) are powerful information filtering systems that rank items and recommend them to a user based on the preferences of the user and the features of the items. These recommendations can vary from which movies to watch to what products to purchase, from which songs to listen to which services to receive. The goal of recommender systems is to suggest the right items to the user to build a trust relationship to achieve long-term business objectives. Most of the large tech companies such as Amazon, Netflix, Spotify, YouTube, and Google benefit from recommender systems to a great extent.
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© 2021 Orhan Gazi Yalçın
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Yalçın, O.G. (2021). Recommender Systems. In: Applied Neural Networks with TensorFlow 2. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-6513-0_10
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DOI: https://doi.org/10.1007/978-1-4842-6513-0_10
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Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-6512-3
Online ISBN: 978-1-4842-6513-0
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