03617nam a22006135i 4500 978-981-99-8964-5 DE-He213 20251030111746.0 cr nn 008mamaa 240325s2024 si | s |||| 0|eng d 9789819989645 978-981-99-8964-5 10.1007/978-981-99-8964-5 doi QA75.5-76.95 UNH bicssc UND bicssc COM030000 bisacsh UNH thema UND thema Li, Dongsheng. author. aut http://id.loc.gov/vocabulary/relators/aut 74015 Recommender Systems [electronic resource] : Frontiers and Practices / by Dongsheng Li, Jianxun Lian, Le Zhang, Kan Ren, Tun Lu, Tao Wu, Xing Xie. 1st ed. 2024. Singapore : Springer Nature Singapore : Imprint: Springer, 2024. XVI, 280 p. 92 illus., 75 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda 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. 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. Information storage and retrieval systems. 65568 Data mining. 6941 Artificial intelligence. 58441 Information Storage and Retrieval. 65570 Data Mining and Knowledge Discovery. Artificial Intelligence. 58441 Lian, Jianxun. author. aut http://id.loc.gov/vocabulary/relators/aut 74016 Zhang, Le. author. aut http://id.loc.gov/vocabulary/relators/aut 74017 Ren, Kan. author. aut http://id.loc.gov/vocabulary/relators/aut 74018 Lu, Tun. author. aut http://id.loc.gov/vocabulary/relators/aut Wu, Tao. author. aut http://id.loc.gov/vocabulary/relators/aut 74019 Xie, Xing. author. aut http://id.loc.gov/vocabulary/relators/aut 74020 SpringerLink (Online service) Springer Nature eBook Printed edition: 9789819989638 Printed edition: 9789819989652 Printed edition: 9789819989669 https://doi.org/10.1007/978-981-99-8964-5 ZDB-2-SCS ZDB-2-SXCS 58666 58666