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Recommender Systems: An Introduction [Hardcover]

Dietmar Jannach , Markus Zanker , Alexander Felfernig , Gerhard Friedrich

Price: 45.00 & FREE Delivery in the UK. Details
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Book Description

30 Sep 2010 0521493366 978-0521493369
In this age of information overload, people use a variety of strategies to make choices about what to buy, how to spend their leisure time, and even whom to date. Recommender systems automate some of these strategies with the goal of providing affordable, personal, and high-quality recommendations. This book offers an overview of approaches to developing state-of-the-art recommender systems. The authors present current algorithmic approaches for generating personalized buying proposals, such as collaborative and content-based filtering, as well as more interactive and knowledge-based approaches. They also discuss how to measure the effectiveness of recommender systems and illustrate the methods with practical case studies. The final chapters cover emerging topics such as recommender systems in the social web and consumer buying behavior theory. Suitable for computer science researchers and students interested in getting an overview of the field, this book will also be useful for professionals looking for the right technology to build real-world recommender systems.

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'Behind the modest title of 'An Introduction' lies the type of work the field needs to consolidate its learning and move forward to address new challenges. Across the chapters that follow lie both a tour of what the field knows well - a diverse collection of algorithms and approaches to recommendation - and a snapshot of where the field is today as new approaches derived from social computing and the semantic web find their place in the recommender systems toolbox. Let's all hope this worthy effort spurs yet more creativity and innovation to help recommender systems move forward to new heights.' Joseph A. Konstan, from the Foreword

Book Description

This book offers an overview of approaches to developing state-of-the-art recommender systems that automate a variety of choice-making strategies with the goal of providing affordable, personal, and high-quality recommendations. The authors present algorithmic approaches for generating personalized buying proposals, as well as more interactive and knowledge-based approaches. They discuss how to measure the effectiveness of recommender systems and illustrate the methods with practical case studies.

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Front Cover | Copyright | Table of Contents | Excerpt | Index
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Customer Reviews

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Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com: 4.7 out of 5 stars  7 reviews
9 of 10 people found the following review helpful
5.0 out of 5 stars The Best Introductory Book about Recommendations 14 Mar 2011
By H. Lee - Published on Amazon.com
Format:Hardcover|Verified Purchase
I am referring to this book for my lectures and this book is fascinating.
First of all, this book is really well-written. The authors explained recommendation technology concepts in an easy-to-follow way. At the same time, they didn't miss the most up-to-date research topics.

Second, all the writers are world's leading researchers of recommendations.
Therefore, they are good to lead readers to more focal points. I like the bibliographic notes at the end of each chapter.

Lastly, by introducing toy examples in every chapter, readers are able to easily comprehend each technology. Actually, this part is my favorite. I think this book is between a reference book of recommendation-related rationales and practical programming books like Manning series or O'Reilly's.

I already made my mind to choose this book as a textbook of my course in the next semester.
3 of 3 people found the following review helpful
4.0 out of 5 stars Too much e-commerce 23 Nov 2012
By Sonne Im Herz - Published on Amazon.com
Format:Hardcover
Well, I am new to the field of recommender system,
so I bought this book as the golden standard.

It is well written and quite interesting,
but for my taste it is too
theoretical and with too much focus
on e-commerce-recommenders and even customer-decision-making.

The book could have more information for that price.
2 of 2 people found the following review helpful
5.0 out of 5 stars Best introduction 5 Sep 2012
By Luiz - Published on Amazon.com
Format:Hardcover|Verified Purchase
I've been studying recomender systems for my Bsc degree in the last two years and I've spent lots of money reading many other books. This book is the cheaper one on my library and I'm so pleased about the content and the way the authors explain things. I know most people doesn't like math and I believe you shouldn't read about this subject but, even if you math weaker, you can have this book.

I'm saying that because I had other books, for example:
http://www.amazon.com/gp/product/3540720782/ref=oh_details_o00_s00_i01
http://www.amazon.com/gp/product/3790821330/ref=oh_details_o01_s00_i02
http://www.amazon.com/gp/product/1933988665/ref=oh_details_o03_s00_i03
Those ones are good but didn't fulfill my desires.

Besides, it is easy to read and understand the concepts, I felt it gave me a good understand of the recomender system universe. I agree that this is the first step. But this first step is so dense that the second step seems so far away.
1 of 1 people found the following review helpful
4.0 out of 5 stars Good book 23 Sep 2013
By Nivio Ziviani - Published on Amazon.com
Format:Hardcover|Verified Purchase
The book is a good introduction to the main topics related to recommender systems. It covers the main problems and issues related to recommendation.
5.0 out of 5 stars Great for academic reading 3 July 2014
By mypapit (m.hafiz) - Published on Amazon.com
Format:Hardcover|Verified Purchase
Great for academic reading, contains literature review on building Recommender System. I myself is looking into building an online recommender system
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