Recommender systems: an introduction

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....

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Bibliographic Details
Main Author: Jannach, Dietmar 1973- (Author)
Format: Electronic eBook
Language:English
Published: Cambridge Cambridge University Press 2011
Subjects:
Online Access:BSB01
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Summary: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
Item Description:Title from publisher's bibliographic system (viewed on 05 Oct 2015)
Physical Description:1 online resource (335 pages)
ISBN:9780511763113
DOI:10.1017/CBO9780511763113