Achieving Private Recommendations Using Randomized Response Techniques

  • Huseyin Polat
  • Wenliang Du
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3918)

Abstract

Collaborative filtering (CF) systems are receiving increasing attention. Data collected from users is needed for CF; however, many users do not feel comfortable to disclose data due to privacy risks. They sometimes refuse to provide information or might decide to give false data. By introducing privacy measures, it is more likely to increase users’ confidence to contribute their data and to provide more truthful data. In this paper, we investigate achieving referrals using item-based algorithms on binary ratings without greatly exposing users’ privacy. We propose to use randomized response techniques (RRT) to perturb users’ data. We conduct experiments to evaluate the accuracy of our scheme and to show how different parameters affect our results using real data sets.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Huseyin Polat
    • 1
  • Wenliang Du
    • 1
  1. 1.Department of Electrical Engineering and Computer ScienceSyracuse UniversitySyracuseUSA

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