Recommender Systems: An Introduction

by Dietmar Jannach, Markus Zanker, Alexander Felfernig

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.

Genres: Programming, Artificial Intelligence, Nonfiction

352 pages, Hardcover

First published September 30, 2010

Reviews

[Christopher · Rating 4 out of 5]

Great book about recommender systems. It has helped me out a lot during my master thesis in laying out a clear and understandable overview of the field. My only regret is not reading this earlier!

[Kasra · Rating 4 out of 5]

It is very good and useful book for the beginner to know about recommender system, however, the topics are quite diverse and some formula didn't explained very well.

[Mateo Zapata López · Rating 5 out of 5]

Muy bien libro, da las bases sobre los sistemas de recomendación y los diferentes tipos que hay. Es clave para continuar el camino de un científico de datos y una persona en aplicar modelos de machine learning.

[Mmmmm · Rating 5 out of 5]

I really understood what recommender systems are.
Before reading it, I had read many papers on Rec. sys.
I don't know, maybe I hadn't focused on them exactly.
However, this book is a good one and up on me is better than a handbook on Rec. sys.
Despite of not having "Handbook" OR "Survey" in its title, I believe that it contains many reviews of good papers on Rec. sys.

[Yahia El gamal · Rating 4 out of 5]

Very good breadth and depth. It will trigger many things for you to read. And at the same time you will feel that the concepts and techniques are concrete enough that you can just go and implement them (giving a bit of extra research). I don't recommend for a total beginner, but for someone who is serious about the field.

[Arif Rohmadi · Rating 3 out of 5]

Bukunya bagus, menjelaskan tentang metode-metode sistem rekomendasi secara lengkap mulai dari berbasis content based, collaborative based, dan knowledge based..

[Yoly · Rating 5 out of 5]

Very good book. The content is great and references tons of papers to read.