Recommender Systems: Frontiers and Practices

by Dongsheng Li, Jianxun Lian, Le Zhang, Kan Ren, Tun Lu, Tao Wu, and Xing Xie

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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.

 

  • ISBN13 9789819989638
  • Publish Date 26 March 2024
  • Publish Status Active
  • Publish Country SG
  • Imprint Springer Verlag, Singapore
  • Edition 1st ed. 2024
  • Format Hardcover
  • Pages 280
  • Language English