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Recommender Systems: The Textbook, by Charu C. Aggarwal
Fee Download Recommender Systems: The Textbook, by Charu C. Aggarwal
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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 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:
- Algorithms and evaluation: These chapters discuss the fundamental algorithms in recommender systems, including collaborative filtering methods, content-based methods, knowledge-based methods, ensemble-based methods, and evaluation.
- Recommendations in specific domains and contexts: the context of a recommendation can be viewed as important side information that affects the recommendation goals. Different types of context such as temporal data, spatial data, social data, tagging data, and trustworthiness are explored.
- Advanced topics and applications: Various robustness aspects of recommender systems, such as shilling systems, attack models, and their defenses are discussed.
In addition, recent topics, such as learning to rank, multi-armed bandits, group systems, multi-criteria systems, and active learning systems, are introduced together with applications.
Although this book primarily serves as a textbook, it will also appeal to industrial practitioners and researchers due to its focus on applications and references. Numerous examples and exercises have been provided, and a solution manual is available for instructors.- Sales Rank: #697982 in Books
- Published on: 2016-03-29
- Original language: English
- Number of items: 1
- Dimensions: 10.00" h x 1.13" w x 7.00" l, .0 pounds
- Binding: Hardcover
- 498 pages
Most helpful customer reviews
2 of 2 people found the following review helpful.
The Best Book on Recommender Systems
By Amazon Customer
For a technical book, the writing is surprisingly clear and the content is well-organized. This book has given me enough insight to build two sophisticated recommendation engines from scratch. I like that it does not get into specific languages and frameworks. It goes deep into the essential algorithms and mathematics that power recommendation engines and elucidates many concepts that are very hard to grasp by reading other sources. It gives you enough information to know what to look for when using a third party tool or framework. This is essential reading for anyone who wants to build a custom recommendation engine and actually understand how it works.
I highly recommend it :)
2 of 2 people found the following review helpful.
clear and complete book on recommender systems.
By mlgeek
very complete book on recommender systems in nearly 500 pages of lucid writing.
Almost every major topic is studied in detail. Matrix factorization material in the book
is lovely. The book can be helpful to both newcomers and advanced readers.
0 of 0 people found the following review helpful.
It's an excellent book which explains why of things
By SB
It's an excellent book which explains why of things. What could make it even better are some numerical examples and some sample R code. Also, Kindle version has TOC(table-of-contents) not hyperlinked makes it cumbersome to navigate. Regardless, it's both a solid text & reference
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