Author
Naren Ramakrishnan, Benjamin J. Keller, Batul J. Mirza, Ananth Y. Grama, George Karypis
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 graphÂtheoretic model for studying the benefit for and risk to straddlers.
