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1 - Growth Engine of the Internet

Recommender Systems

Published online by Cambridge University Press:  08 May 2025

Zhe Wang ,
Chao Pu  and
Felice Wang
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Summary

Recommender systems have become deeply integrated into daily life, shaping decisions in online shopping, news consumption, learning, and entertainment. These systems offer personalized suggestions, enhancing user experiences in various scenarios. Behind this, machine learning engineers drive the constant evolution of recommendation technology. Described as the “growth engine” of the internet, recommender systems play a critical role in the digital ecosystem. This chapter explores the role of these systems, why they are essential, and how they are architected from a technical perspective.

Keywords

growth enginepersonalizationrecommender systems architecturesystems framework and overview
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Chapter
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Deep Learning Recommender Systems , pp. 1 - 11
Publisher: Cambridge University Press
Print publication year: 2025

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References

Covington, Paul, Adams, Jay, Sargin, Emre. Deep neural networks for YouTube recommendations. Proceedings of the 10th ACM Conference on Recommender Systems, September 7, 2016 (pp. 191–198).Google Scholar

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