Recommender Systems

Recommender Systems

  • Dongsheng Li
  • Jianxun Lian
  • Le Zhang
  • Kan Ren
  • Tun Lu
  • Tao Wu
  • Xing Xie
Publisher:Springer NatureISBN 13: 9789819989645ISBN 10: 9819989647

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Know about the book -

Recommender Systems is written by Dongsheng Li and published by Springer Nature. It's available with International Standard Book Number or ISBN identification 9819989647 (ISBN 10) and 9789819989645 (ISBN 13).

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 used, and analyzes problems arising in the theory and practice of recommender systems, helping readers gain a deeper understanding of the cutting-edge technology used in these systems. Lastly, it shares practical experience with Microsoft 's open source project Microsoft Recommenders. Readers can learn the design principles of recommendation algorithms using the source code provided in this book, allowing them to quickly build accurate and efficient recommender systems from scratch.