Recommender Systems: Frontiers and Practices | Agenda Bookshop Skip to content
Online orders placed from 19/12 onward will not arrive in time for Christmas.
Online orders placed from 19/12 onward will not arrive in time for Christmas.
A01=Dongsheng Li
A01=Jianxun Lian
A01=Kan Ren
A01=Le Zhang
A01=Tao Wu
A01=Tun Lu
A01=Xing Xie
Age Group_Uncategorized
Age Group_Uncategorized
Author_Dongsheng Li
Author_Jianxun Lian
Author_Kan Ren
Author_Le Zhang
Author_Tao Wu
Author_Tun Lu
Author_Xing Xie
automatic-update
Category1=Non-Fiction
Category=UMB
Category=UYQE
Category=UYQM
COP=Singapore
Delivery_Pre-order
Language_English
PA=Not yet available
Price_€50 to €100
PS=Active
softlaunch

Recommender Systems: Frontiers and Practices

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.

 

See more
Current price €59.84
Original price €62.99
Save 5%
A01=Dongsheng LiA01=Jianxun LianA01=Kan RenA01=Le ZhangA01=Tao WuA01=Tun LuA01=Xing XieAge Group_UncategorizedAuthor_Dongsheng LiAuthor_Jianxun LianAuthor_Kan RenAuthor_Le ZhangAuthor_Tao WuAuthor_Tun LuAuthor_Xing Xieautomatic-updateCategory1=Non-FictionCategory=UMBCategory=UYQECategory=UYQMCOP=SingaporeDelivery_Pre-orderLanguage_EnglishPA=Not yet availablePrice_€50 to €100PS=Activesoftlaunch

Will deliver when available. Publication date 16 Apr 2024

Product Details
  • Dimensions: 155 x 235mm
  • Publication Date: 26 Mar 2024
  • Publisher: Springer Verlag Singapore
  • Publication City/Country: Singapore
  • Language: English
  • ISBN13: 9789819989638

About Dongsheng LiJianxun LianKan RenLe ZhangTao WuTun LuXing Xie

Dongsheng Li has been a principal research manager with Microsoft Research Asia (MSRA) since February 2020. His research interests include recommender systems and general machine learning applications. He has published over 100 papers in top-tier conferences and journals and has served as a program committee member for leading conferences.Dr. Jianxun Lian graduated from the University of Science and Technology of China and is currently a senior researcher with Microsoft Research Asia. His research interests mainly include recommendation systems user modeling and deep-learning-related technologies.Le Zhang is a machine learning architect with Standard Chartered Bank. He has extensive experience in applying cutting-edge machine learning and artificial intelligence technology to accelerate digital transformation for enterprises and start-ups.Kan Ren is a senior researcher with Microsoft Research. His main research interests include spatiotemporal data mining reasoning and decision optimization with applications in healthcare recommender systems and finance. Kan has published many papers in top-tier conferences on machine learning and data mining.Tun LU is currently a full professor with the School of Computer Science Fudan University China. His research interests include computer-supported cooperative work (CSCW) social computing recommender systems and humancomputer interaction (HCI). He has published more than 80 peer-reviewed publications in prestigious conferences and journals. Tao Wu is a Principal Applied Science Manager at Microsoft's Business Applications and Platform Group and leading product development efforts utilizing large language models and generative AI. He spearheaded the creation of the Microsoft Recommenders project (recently donated to the Linux Foundation) which has become one of the most popular open source projects on recommender systems.  Prior to Microsoft Tao held various research engineering and leadership positions at Nokia Research Center and MIT CSAIL. Dr. Xing Xie is currently a senior principal research manager with Microsoft Research Asia. In the past several years he has published over 300 papers won the 2022 ACM SIGKDD 2022 Test-of-Time Award and 2021 ACM SIGKDD China Test-of-Time Award received the 10-Year Impact Award (honorable mention) at ACM SIGSPATIAL 2020 and won the 10-Year Impact Award at ACM SIGSPATIAL 2019. He currently serves on the editorial boards of ACM Transactions on Recommender Systems (ToRS) ACM Transactions on Social Computing (TSC) and ACM Transactions on Intelligent Systems and Technology (TIST).

Customer Reviews

Be the first to write a review
0%
(0)
0%
(0)
0%
(0)
0%
(0)
0%
(0)
We use cookies to ensure that we give you the best experience on our website. If you continue we'll assume that you are understand this. Learn more
Accept