Advertisement

© 2011

Recommender Systems Handbook

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

Benefits

  • First comprehensive handbook which is dedicated entirely to the field of recommender systems

  • IT professionals that provides services and products to the end-customers via the Internet or other communication means, will find this book very valuable,because it contains detailed algorithms and provides a Java source for all algorithms

  • Contributed by leading experts in the field

Book

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

About this book

Introduction

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.

Keywords

Collaborative filtering Content-based filtering Information access Personalization currentsmp

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

About the editors

Francesco Ricci is associate professor at the faculty of computer science, 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 Tourism. He is in the editorial board of Journal of Information Technology and Tourism and he is member of ACM and IEEE. F. Ricci is also member of the steering committee of the ACM Conference on Recommender Systems.

Lior Rokach is assistant professor at the Department of Information System Engineering at Ben-Gurion University. He is a recognized expert in intelligent information systems and has held several leading positions in this field. His main areas of interest are Data Mining, Pattern Recognition, and Recommender Systems. Dr. Rokach is the author of over 70 refereed papers in leading journals, conference proceedings and book chapters. In addition he has authored six books and edited three others books.

Bracha Shapira is assistant professor at the Department of Information Systems Engineering at Ben-Gurion University, Beer-Sheva, Israel. Her current research interests include recommender systems, information retrieval, personalization, user modelling, and social networks. She leads research projects at the Deutsche telekom Laboratories at Ben-Gurion University and is a member of ACM and IEEE.

Paul Kantor is Professor of Information Science in the School of Communication and Information at Rutgers University, with additional appointments in the Faculty of Computer Science and the RUTCOR Center for Operations Research. His interests are in collaborative information finding, text classification, and text or imaging indexing and retrieval. He is a Fellow of the American Association for the Advancement of Science, and a member of the ACM, IEEE and ASIST, and his research is supported by the US NSF and Department of Homeland Security, and other agencies.

Bibliographic information

Industry Sectors
Automotive
Chemical Manufacturing
Biotechnology
IT & Software
Telecommunications
Law
Consumer Packaged Goods
Pharma
Materials & Steel
Finance, Business & Banking
Electronics
Energy, Utilities & Environment
Aerospace
Oil, Gas & Geosciences
Engineering