Recommender systems : frontiers and practices / Dongsheng Li, Jianxun Lian, Le Zhang, Kan Ren, Tun Lu, Tao Wu, Xing Xie.

Format:

Book

Author/Creator:

Li, Dongsheng, author.

Lian, Jianxun, author.

Zhang, Le, author.

Ren, Kan, author.

Lu, Tun, author.

Wu, Tao, author.

Xie, Xing, author.

Contributor:

Rosengarten Family Fund.

Language:

English

Subjects (All):

Recommender systems (Information filtering).

Physical Description:

xvi, 280 pages : color illustrations ; 25 cm

Place of Publication:

[S.l.] : SPRINGER, 2024.

Singapore : Springer Nature Singapore Pte Ltd., [2024]

Summary:

"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." -- Provided by publisher.

Notes:

Includes bibliographical references.

Local Notes:

Acquired for the Penn Libraries with assistance from the Rosengarten Family Fund.

ISBN:

9819989639

9789819989638

OCLC:

1409605492

Publisher Number:

99996433195