Recommender Systems Handbook

Editors: Ricci, Francesco, Rokach, Lior, Shapira, Bracha (Eds.)

  • Includes major updates as well as 20 new chapters
  • Presents detailed case studies
  • Shares tips and insights from renowned experts in the field
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Buy this book

eBook $189.00
price for USA (gross)
  • ISBN 978-1-4899-7637-6
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $249.00
price for USA
  • ISBN 978-1-4899-7636-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $249.00
price for USA
  • ISBN 978-1-4899-7780-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, and challenges. A variety of real-world applications and detailed case studies are included. In addition to wholesale revision of the existing chapters, this edition includes new topics including: decision making and recommender systems, reciprocal recommender systems, recommender systems in social networks, mobile recommender systems, explanations for recommender systems, music recommender systems, cross-domain recommendations, privacy in recommender systems, and semantic-based recommender systems. This multi-disciplinary handbook involves world-wide experts from diverse fields such as artificial intelligence, human-computer interaction, information retrieval, data mining, mathematics, statistics, adaptive user interfaces, decision support systems, psychology, marketing, and consumer behavior. Theoreticians and practitioners from these fields will find this reference to be an invaluable source of ideas, methods and techniques for developing more efficient, cost-effective and accurate recommender systems.

About the authors

Francesco Ricci is a professor of computer science at the Free University of Bozen-Bolzano, Italy. His current research interests include recommender systems, intelligent interfaces, mobile systems, machine learning, case-based reasoning, and the applications of ICT to health and tourism. He has published more than one hundred thirty of academic papers on these topics. He is the editor in chief of the Journal of Information Technology & Tourism and on the editorial board of User Modeling and User Adapted Interaction. Lior Rokach is a data scientist and an associate professor of information systems and software engineering at Ben-Gurion University of the Negev (BGU). Rokach established the machine learning laboratory in BGU which promotes innovative adaptations of machine learning and data mining methods to create the next generation of intelligent systems. Rokach is known for his contributions to the advancement of machine learning, recommender systems and cyber security. Bracha Shapira is an associate professor and the head of the information systems and engineering Department at Ben-Gurion University of the Negev (BGU). She leads large scale research projects at the Telekom Innovation Laboratories at BGU in the area of data analytics, recommender systems and personalization that delivers innovative technologies to address challenges in these fields. Shapira is known for her contribution in integrating social network, context awareness and privacy consideration to recommender systems.

Reviews

“If you have time for just one book to get yourself up to speed with the latest and best in recommender systems, this is the book you want. … this is an excellent educational resource on the main techniques employed for making recommendations … . is definitely a book to read to get updated on the state of the art of recommender systems, and also to get a feel of the breadth of the research areas available in this area.” (Jun-Ping Ng, Computing Reviews, April, 2016)


Table of contents (28 chapters)

  • Recommender Systems: Introduction and Challenges

    Ricci, Francesco (et al.)

    Pages 1-34

  • A Comprehensive Survey of Neighborhood-Based Recommendation Methods

    Ning, Xia (et al.)

    Pages 37-76

  • Advances in Collaborative Filtering

    Koren, Yehuda (et al.)

    Pages 77-118

  • Semantics-Aware Content-Based Recommender Systems

    Gemmis, Marco (et al.)

    Pages 119-159

  • Constraint-Based Recommender Systems

    Felfernig, Alexander (et al.)

    Pages 161-190

Buy this book

eBook $189.00
price for USA (gross)
  • ISBN 978-1-4899-7637-6
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $249.00
price for USA
  • ISBN 978-1-4899-7636-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $249.00
price for USA
  • ISBN 978-1-4899-7780-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Recommender Systems Handbook
Editors
  • Francesco Ricci
  • Lior Rokach
  • Bracha Shapira
Copyright
2015
Publisher
Springer US
Copyright Holder
Springer Science+Business Media New York
eBook ISBN
978-1-4899-7637-6
DOI
10.1007/978-1-4899-7637-6
Hardcover ISBN
978-1-4899-7636-9
Softcover ISBN
978-1-4899-7780-9
Edition Number
2
Number of Pages
XVII, 1003
Topics