Recommender Systems

Shuai Zhang (), Aston Zhang () and Lina Yao ()
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Shuai Zhang: University of New South Wales
Aston Zhang: Amazon
Lina Yao: University of New South Wales

A chapter in Machine Learning for Data Science Handbook, 2023, pp 637-658 from Springer

Abstract: Abstract Recommender systems have achieved widespread success in real-life applications. Personalized recommendation can reduce customers’ effort in finding items they are interested in. It is also critical in some industries as it can increase customer stickiness and help industries to stand out from competitors. Recommender systems made a significant progress over the last decade, and the advancements are fruitful and inspiring. Given its importance, this chapter aims at introducing the fundamentals and advances of recommender systems. In specific, we will present readers with the widely used techniques, applications, and evaluation methods of recommender systems, in the hope that it could help them to get a thorough and clear understanding to this field.

Date: 2023
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DOI: 10.1007/978-3-031-24628-9_28

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