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Privacy Risks to Straddlers in Recommender Systems (2001)
BibTeX
@MISC{Ramakrishnan01privacyrisks,
author = {Naren Ramakrishnan and Benjamin J. Keller and Batul J. Mirza and Ananth Y. Grama and George Karypis},
title = {Privacy Risks to Straddlers in Recommender Systems},
year = {2001}
}
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Abstract
We explore the conflict between personalization and privacy that arises from the existence of straddlers in a recommender system. A straddler is a person with eclectic tastes who rates products across several different types or domains. While straddlers enable serendipitous recommendations, information about their existence could be used in conjunction with other sources of data to uncover identities and reveal personal details. In this article, we use a graph-theoretic model to study the benefit from and risk to straddlers.
