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Privacy-Preserving Collaborative Filtering on Vertically Partitioned Databy: Huseyin Polat, Wenliang Du
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AbstractCollaborative filtering (CF) systems are widely used by E-commerce sites to provide predictions using existing databases comprised of ratings recorded from groups of people evaluating various items, sometimes, however, such systems’ ratings are split among different parties. To provide better filtering services, such parties may wish to share their data. However, due to privacy concerns, data owners do not want to disclose data. This paper presents a privacy-preserving protocol for CF grounded on vertically partitioned data. We conducted various experiments to evaluate the overall performance of our scheme.
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