Machine Learning and Deep Learning Techniques for Recommendation Systems: A Comprehensive Review

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Mamta Kalra, Suman Sangwan

Abstract

In the current era, our digital lives are driven by data. Recommendation engines have become part and parcel of our digital lives and help us to make decisions about products, content, and services to buy. The evolving landscape of deep learning-based recommendation systems has been extensively discussed in this paper. The main focus is on key advancements in recommendation system evaluation, personalized recommendation techniques, and the integration of various data sources. Furthermore, it discusses the ethical and privacy concerns associated with recommendation systems. A critical analysis of the current state of recommendation systems has been presented to give valuable insights for future advancements in this area.

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