Privacy Risks in Recommender Systems

  • Authors:
  • Naren Ramakrishnan;Benjamin J. Keller;Batul J. Mirza;Ananth Y. Grama;George Karypis

  • Affiliations:
  • -;-;-;-;-

  • Venue:
  • IEEE Internet Computing
  • Year:
  • 2001

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Abstract

The authors explore the conflict between personalization and privacy that arises from the existence of straddlers - users with eclectic tastes who rates products across several different types or domains -- in recommender systems. While straddlers enable serendipitous recommendations, information about their existence could be used in conjunction with other data sources to uncover identities and reveal personal details. This article discusses a graph theoretic model for studying the benefit for and risk to straddlers.