Personalized communities in a distributed recommender system
ECIR'07 Proceedings of the 29th European conference on IR research
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Personalized online commerce systems, context-aware pervasive computing applications, and other personalized computing systems often sacrifice privacy for added convenience or improved service. Some systems provide users with substantial benefits from personalization; other systems profile users to the primary benefit of the service provider. In many cases users are not fully informed about how their profile information will be used and are not given adequate opportunities to control the use of their personal information. If developers of personalized systems do not consider privacy issues in the design of their systems they risk building systems that are unable to comply with legal requirements in some jurisdictions. In addition, concerns about privacy may slow adoption of some personalized systems or prevent them from ever gaining acceptance. In this talk I will discuss the privacy risks associated with personalization systems and discuss a number of approaches to reducing those risks, including approaches to minimizing the amount of profile information associated with identified individuals and approaches to better informing users and giving them meaningful opportunities to control the user of their personal information.