Privacy-Preserving Collaborative Filtering Using Randomized Perturbation Techniques

Huseyin Polat; Wenliang Du

doi:10.1109/ICDM.2003.1250993

Third IEEE International Conference on Data Mining

Privacy-Preserving Collaborative Filtering Using Randomized Perturbation Techniques

Year: 2003, Pages: 625

DOI Bookmark: 10.1109/ICDM.2003.1250993

Authors

Huseyin Polat, Syracuse University, NY
Wenliang Du, Syracuse University, NY

Abstract

Collaborative Filtering (CF) techniques are becoming increasingly popular with the evolution of the Internet. To conduct collaborative filtering, data from customers are needed. However, collecting high quality data from customers is not an easy task because many customers are so concerned about their privacy that they might decide to give false information. We propose a randomized perturbation (RP) technique to protect users' privacy while still producing accurate recommendations.

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Privacy-Preserving Collaborative Filtering Using Randomized Perturbation Techniques

Authors

Abstract

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