Recommender Systems: An Introduction by Dietmar Jannach (English) Hardcover Book

Description: Recommender Systems by Dietmar Jannach, Markus Zanker, Alexander Felfernig, Gerhard Friedrich This book introduces different approaches to developing recommender systems that automate choice-making strategies to provide affordable, personal, and high-quality recommendations. FORMAT Hardcover LANGUAGE English CONDITION Brand New Publisher Description 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. Author Biography Dietmar Jannach is a chaired Professor of Computer Science at TU Dortmund, Germany. The author of more than 100 scientific papers, he is a member of the editorial board of the Applied Intelligence journal and the review board of the International Journal of Electronic Commerce. Markus Zanker is an associate professor at the Alpen-Adria University, Klagenfurt, Austria. He directs the research group on recommender systems and is the director of the study programme in information management. In 2010 he was the program co-chair of the 4th International ACM Conference on Recommender Systems. He has published numerous papers in the area of artificial intelligence focusing on recommender systems, consumer buying behavior and human factors. He is also an associate editor of the International Journal of Human-Computer Studies. Alexander Felfernig is Professor of Applied Software Engineering at the Graz University of Technology (TU Graz). In his research he focuses on intelligent methods and algorithms supporting the development and maintenance of complex knowledge bases. Furthermore, Alexander is interested in the application of AI techniques in the software engineering context, for example, the application of decision and recommendation technologies to make software requirements engineering processes more effective. For his research he received the Heinz–Zemanek Award from the Austrian Computer Society in 2009. Gerhard Friedrich is a chaired Professor at the Alpen-Adria Universität Klagenfurt, Austria, where he is head of the Institute of Applied Informatics and directs the Intelligent Systems and Business Informatics research group. He is an editor of AI Communications and an associate editor of the International Journal of Mass Customisation. Table of Contents 1. Introduction; Part I. Introduction into Basic Concepts: 2. Collaborative recommendation; 3. Content-based recommendation; 4. Knowledge-based recommendation; 5. Hybrid recommendation approaches; 6. Explanations in recommender systems; 7. Evaluating recommender systems; 8. Case study - personalized game recommendations on the mobile Internet; Part II. Recent Developments: 9. Attacks on collaborative recommender systems; 10. Online consumer decision making; 11. Recommender systems and the next-generation Web; 12. Recommendations in ubiquitous environments; 13. Summary and outlook. Review 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. Lets 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 Promotional This book introduces different approaches to developing recommender systems that automate choice-making strategies to provide affordable, personal, and high-quality recommendations. Review Quote 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. Lets 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 Promotional "Headline" This book introduces different approaches to developing recommender systems that automate choice-making strategies to provide affordable, personal, and high-quality recommendations. Description for Bookstore 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. Description for Library 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. Details ISBN0521493366 Author Gerhard Friedrich Year 2010 ISBN-10 0521493366 ISBN-13 9780521493369 Format Hardcover Media Book Imprint Cambridge University Press Subtitle An Introduction Place of Publication Cambridge Country of Publication United Kingdom Publisher Cambridge University Press DEWEY 381.142 Short Title RECOMMENDER SYSTEMS Language English Pages 352 Birth 1973 Publication Date 2010-09-30 UK Release Date 2010-09-30 AU Release Date 2010-09-30 NZ Release Date 2010-09-30 Illustrations 29 Tables, unspecified; 8 Halftones, unspecified; 64 Line drawings, unspecified Alternative 9780511763113 Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! 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