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Recommender Systems Frontiers and Practices /

This book starts from the classic recommendation algorithms, introduces readers to the basic principles and main concepts of the traditional algorithms, and analyzes their advantages and limitations. Then, it addresses the fundamentals of deep learning, focusing on the deep-learning-based technology...

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Hlavní autoři: Li, Dongsheng (Autor), Lian, Jianxun (Autor), Zhang, Le (Autor), Ren, Kan (Autor), Lu, Tun (Autor), Wu, Tao (Autor), Xie, Xing (Autor)
Korporativní autor: SpringerLink (Online service)
Médium: Elektronický zdroj E-kniha
Jazyk:angličtina
Vydáno: Singapore : Springer Nature Singapore : Imprint: Springer, 2024.
Vydání:1st ed. 2024.
Témata:
Information storage and retrieval systems.
Data mining.
Artificial intelligence.
Information Storage and Retrieval.
Data Mining and Knowledge Discovery.
Artificial Intelligence.
On-line přístup:https://doi.org/10.1007/978-981-99-8964-5
Tagy: Přidat tag
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Obsah:
  • Chapter 1. Overview of Recommender Systems
  • Chapter 2. Classic Recommendation Algorithms
  • Chapter 3. Foundations of Deep Learning
  • Chapter 4. Deep Learning-based Recommendation Algorithms
  • Chapter 5. Recommender System Frontier Topics. Chapter 6. Practical Recommender System
  • Chapter 7. Summary and Outlook.

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