Attack-Resistant Recommender Systems

  • Charu C. Aggarwal


The input to recommender systems is typically provided through open platforms. Almost anyone can register and submit a review at sites such as and Like any other data-mining system, the effectiveness of a recommender system depends almost exclusively on the quality of the data available to it. Unfortunately, there are significant motivations for participants to submit incorrect feedback about items for personal gain or for malicious reasons:

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Charu C. Aggarwal
    • 1
  1. 1.IBM T.J. Watson Research CenterYorktown HeightsUSA

Personalised recommendations