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Robust Collaborative Recommendation

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Abstract

Collaborative recommender systems are vulnerable to malicious users who seek to bias their output, causing them to recommend (or not recommend) particular items. This problem has been an active research topic since 2002. Researchers have found that the most widely-studied memory-based algorithms have significant vulnerabilities to attacks that can be fairly easily mounted. This chapter discusses these findings and the responses that have been investigated, especially detection of attack profiles and the implementation of robust recommendation algorithms.

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Acknowledgements

Neil Hurley would like to acknowledge the support of Science Foundation Ireland, grant number 08/SRC/I1407: Clique: Graph and Network Analysis Cluster. Michael O’Mahony is supported by Science Foundation Ireland under grant 07/CE/I1147: CLARITY: Centre for Sensor Web Technologies.

Author information

Authors and Affiliations

  1. Center for Web Intelligence, School of Computer Science, Telecommunication and Information Systems, DePaul University, Chicago, Illinois, USA

    Robin Burke

  2. CLARITY: Centre for Sensor Web Technologies, School of Computer Science and Informatics, University College Dublin, Dublin, Ireland

    Michael P. O’Mahony

  3. School of Computer Science and Informatics, University College Dublin, Dublin, Ireland

    Neil J. Hurley

Authors
  1. Robin Burke
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  2. Michael P. O’Mahony
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  3. Neil J. Hurley
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Corresponding author

Correspondence to Robin Burke .

Editor information

Editors and Affiliations

  1. , Faculty of Computer Science, Free University of Bozen-Bolzano, Piazza Domenicani 3, Bolzano, 39100, Italy

    Francesco Ricci

  2. , Dept. Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel

    Lior Rokach

  3. Dept. Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel

    Bracha Shapira

  4. School of Communication,, Information & Library Studies, Rutgers University, Huntington Street 4, New Brunswick, 08901-1071, New Jersey, USA

    Paul B. Kantor

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Burke, R., O’Mahony, M.P., Hurley, N.J. (2011). Robust Collaborative Recommendation. In: Ricci, F., Rokach, L., Shapira, B., Kantor, P. (eds) Recommender Systems Handbook. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-85820-3_25

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  • DOI: https://doi.org/10.1007/978-0-387-85820-3_25

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  • Print ISBN: 978-0-387-85819-7

  • Online ISBN: 978-0-387-85820-3

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