Recommender Systems (Record no. 87749)
[ view plain ]
| 000 -LEADER | |
|---|---|
| fixed length control field | 03606nam a22006135i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-981-99-8964-5 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240730171705.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 240325s2024 si | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9789819989645 |
| -- | 978-981-99-8964-5 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 025.04 |
| 100 1# - AUTHOR NAME | |
| Author | Li, Dongsheng. |
| 245 10 - TITLE STATEMENT | |
| Title | Recommender Systems |
| Sub Title | Frontiers and Practices / |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2024. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XVI, 280 p. 92 illus., 75 illus. in color. |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | 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. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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. . |
| 700 1# - AUTHOR 2 | |
| Author 2 | Lian, Jianxun. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Zhang, Le. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Ren, Kan. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Lu, Tun. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Wu, Tao. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Xie, Xing. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1007/978-981-99-8964-5 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Singapore : |
| -- | Springer Nature Singapore : |
| -- | Imprint: Springer, |
| -- | 2024. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Information storage and retrieval systems. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial intelligence. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Information Storage and Retrieval. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data Mining and Knowledge Discovery. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial Intelligence. |
| 912 ## - | |
| -- | ZDB-2-SCS |
| 912 ## - | |
| -- | ZDB-2-SXCS |
No items available.