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Privacy Risks in Recommender Systems
November/December 2001 (vol. 5 no. 6)
pp. 54-62

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.

Citation:
Naren Ramakrishnan, Benjamin J. Keller, Batul J. Mirza, Ananth Y. Grama, George Karypis, "Privacy Risks in Recommender Systems," IEEE Internet Computing, vol. 5, no. 6, pp. 54-62, Nov.-Dec. 2001, doi:10.1109/4236.968832
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