Recommender Systems Handbook

  • Francesco Ricci
  • Lior Rokach
  • Bracha Shapira
  • Paul B. Kantor

Table of contents

  1. Front Matter
    Pages i-xxix
  2. Francesco Ricci, Lior Rokach, Bracha Shapira
    Pages 1-35
  3. Basic Techniques

    1. Front Matter
      Pages 37-37
    2. Xavier Amatriain, Alejandro Jaimes*, Nuria Oliver, Josep M. Pujol
      Pages 39-71
    3. Pasquale Lops, Marco de Gemmis, Giovanni Semeraro
      Pages 73-105
    4. Christian Desrosiers, George Karypis
      Pages 107-144
    5. Yehuda Koren, Robert Bell
      Pages 145-186
    6. Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Zanker
      Pages 187-215
    7. Gediminas Adomavicius, Alexander Tuzhilin
      Pages 217-253
  4. Applications and Evaluation of RSs

    1. Front Matter
      Pages 255-255
    2. Guy Shani, Asela Gunawardana
      Pages 257-297
    3. Riccardo Bambini, Paolo Cremonesi, Roberto Turrin
      Pages 299-331
    4. Jérome Picault, Myriam Ribière, David Bonnefoy, Kevin Mercer
      Pages 333-365
    5. Robin Burke, Maryam Ramezani
      Pages 367-386
    6. Nikos Manouselis, Hendrik Drachsler, Riina Vuorikari, Hans Hummel, Rob Koper
      Pages 387-415
  5. Interacting with Recommender Systems

    1. Front Matter
      Pages 417-417
    2. Lorraine McGinty, James Reilly
      Pages 419-453
    3. Nava Tintarev, Judith Masthoff
      Pages 479-510
    4. Pearl Pu, Boi Faltings, Li Chen, Jiyong Zhang, Paolo Viappiani
      Pages 511-545
    5. Martijn Kagie, Michiel van Wezel, Patrick J.F. Groenen
      Pages 547-576
  6. Recommender Systems and Communities

    1. Front Matter
      Pages 577-577
    2. Barry Smyth, Maurice Coyle, Peter Briggs
      Pages 579-614
    3. Leandro Balby Marinho, Alexandros Nanopoulos, Lars Schmidt-Thieme, Robert Jäschke, Andreas Hotho, Gerd Stumme et al.
      Pages 615-644
    4. Patricia Victor, Martine De Cock, Chris Cornelis
      Pages 645-675
  7. Advanced Algorithms

    1. Front Matter
      Pages 703-703
    2. Gleb Beliakov, Tomasa Calvo, Simon James
      Pages 705-734
    3. Neil Rubens, Dain Kaplan, Masashi Sugiyama
      Pages 735-767
    4. Gediminas Adomavicius, Nikos Manouselis, YoungOk Kwon
      Pages 769-803
    5. Robin Burke, Michael P. O’Mahony, Neil J. Hurley
      Pages 805-835
  8. Back Matter
    Pages 837-842

About this book


The explosive growth of e-commerce and online environments has made the issue of information search and selection increasingly serious; users are overloaded by options to consider and they may not have the time or knowledge to personally evaluate these options. Recommender systems have proven to be a valuable way for online users to cope with the information overload and have become one of the most powerful and popular tools in electronic commerce. Correspondingly, various techniques for recommendation generation have been proposed. During the last decade, many of them have also been successfully deployed in commercial environments.

Recommender Systems Handbook, an edited volume, is a multi-disciplinary effort that involves world-wide experts from diverse fields, such as artificial intelligence, human computer interaction, information technology, data mining, statistics, adaptive user interfaces, decision support systems, marketing, and consumer behavior. Theoreticians and practitioners from these fields continually seek techniques for more efficient, cost-effective and accurate recommender systems. This handbook aims to impose a degree of order on this diversity, by presenting a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, challenges and applications. Extensive artificial applications, a variety of real-world applications, and detailed case studies are included.

Recommender Systems Handbook illustrates how this technology can support the user in decision-making, planning and purchasing processes. It works for well known corporations such as Amazon, Google, Microsoft and AT&T. This handbook is suitable for researchers and advanced-level students in computer science as a reference.


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Editors and affiliations

  • Francesco Ricci
    • 1
  • Lior Rokach
    • 2
  • Bracha Shapira
    • 3
  • Paul B. Kantor
    • 4
  1. 1., Faculty of Computer ScienceFree University of Bozen-BolzanoBolzanoItaly
  2. 2., Dept. Information Systems EngineeringBen-Gurion University of the NegevBeer-ShevaIsrael
  3. 3.Dept. Information Systems EngineeringBen-Gurion University of the NegevBeer-ShevaIsrael
  4. 4.School of Communication,, Information & Library StudiesRutgers UniversityNew BrunswickUSA

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