Privacy-Preserving Collaborative Filtering Using Randomized Perturbation Techniques

  • Authors:
  • Huseyin Polat;Wenliang Du

  • Affiliations:
  • -;-

  • Venue:
  • ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
  • Year:
  • 2003

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Abstract

Collaborative Filtering (CF) techniques are becomingincreasingly popular with the evolution of the Internet. Toconduct collaborative filtering, data from customers areneeded. However, collecting high quality data from customersis not an easy task because many customers areso concerned about their privacy that they might decide togive false information. We propose a randomized perturbation(RP) technique to protect users' privacy while stillproducing accurate recommendations.