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from $108.67 1 Used from $126.89 5 New from $108.67. This book comprehensively covers the topic of recommender systems, which provide personalized recommendations of products or services to users based on their previous searches or purchases. Recommender system methods have been adapted to diverse applications including query log mining, social.


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Recommender Systems: The Textbook | Guide books | ACM Digital Library Browse Books Home Browse by Title Books Recommender Systems: The Textbook Recommender Systems: The TextbookApril 2016 Author: Charu C. Aggarwal Publisher: Springer Publishing Company, Incorporated ISBN: 978-3-319-29657-9 Published: 29 April 2016 Pages: 498 Available at Amazon


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Recommender Systems C. Aggarwal Published in Cambridge International Law… 29 March 2016 Computer Science This book comprehensively covers the topic of recommender systems, which provide personalized recommendations of products or services to users based on their previous searches or purchases.


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The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or


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Recommender system methods have been adapted to diverse applications including query log mining, social networking, news recommendations, and computational advertising. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The chapters of this book are organized into three categories:


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Recommender system methods have been adapted to diverse applications including query log mining, social networking, news recommendations, and computational advertising. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The chapters of this book are organized into three categories.


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"If you have time for just one book to get yourself up to speed with the latest and best in recommender systems, this is the book you want.. this is an excellent educational resource on the main techniques employed for making recommendations. . is definitely a book to read to get updated on the state of the art of recommender systems, and also to get a feel of the breadth of the.


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Recommender Systems Handbook Home Book Editors: Francesco Ricci, Lior Rokach, Bracha Shapira Includes eleven new chapters in this third edition handbook Introduces advanced topics such as Deep Neural Networks and RS, Natural Language Processing and RS and more Chapters are written by major renown experts in the field of Recommender Systems


[Download] Systems The Textbook

Recommender Systems: The Textbook Charu C. Aggarwal Springer, Mar 28, 2016 - Computers - 498 pages This book comprehensively covers the topic of recommender systems, which provide.


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The proposed Splitting and Replication mechanism is inspired by the successful shared-nothing architecture that underpins contemporary big data processing systems and has been applied to two well-known approaches for online recommender systems, namely, matrix factorization and item-based collaborative filtering.


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Recommender Systems Home Textbook Authors: Charu C. Aggarwal Includes exercises and assignments, with instructor access to a solutions manual Illustrations throughout aid in comprehension Provides many examples to simplify exposition and facilitate in learning Destined to be the standard textbook in a mature field — show all 1.76m Accesses


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Recommender Systems: The Textbook Charu C. Aggarwal 4.33 39 ratings4 reviews This book comprehensively covers the topic of recommender systems, which provide personalized recommendations of products or services to users based on their previous searches or purchases.


Systems cant be stopped part2(Machine Learning) by Monodeep Mukherjee Apr, 2023

Recommender-Systems Text Books If you are new to recommender systems, a text-book may be a good starting point. We would particularly recommend the following three textbooks. Book descriptions are from Amazon, sometimes extended by our own comments. Recommender Systems Handbook (2nd edt.; 2015)

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