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1 results

  • 3 - Top of the Tide

  • Zhe Wang, Chao Pu, Felice Wang
  • Book:
    Deep Learning Recommender Systems
    Published online:
    08 May 2025
    Print publication:
    22 May 2025, pp 48-116

  • Summary

    The introduction of advanced deep learning models such as Microsoft’s Deep Crossing, Google’s Wide&Deep, and others like FNN and PNN in 2016 marked a significant shift in the field of recommender systems and computational advertising, establishing deep learning as the dominant approach. This chapter discusses the evolution of traditional recommendation models and highlights two main advancements in deep learning models: enhanced expressivity for uncovering hidden data patterns and flexible model structures tailored to specific business use cases. Drawing on techniques from computer vision, speech, and natural language processing, deep learning recommendation models have rapidly evolved. The chapter summarizes several influential deep learning models and constructs an evolution map. These models are selected based on their industry impact and their role in advancing deep learning recommender systems. Additionally, the chapter will introduce applications of Large Language Models (LLMs) in recommender systems, exploring how these models further enhance recommendation technologies.