Privacy-Aware Personalization for Mobile Advertising

The authors address the problem of personalizing ad delivery to a smart phone, without violating user privacy. They propose a flexible framework where users can decide how much information about their private context they are willing to share with the ad server. Based on this limited information the server selects a set of ads and sends them to the client. The client then picks the most relevant one based on all its private contextual information. The optimization of selecting the most relevant ads to display is done jointly by the user and the server under two constraints on privacy, i.e., how much information is shared, and communication complexity, i.e. how many ads are sent to the client.

Provided by: Cornell University Topic: Mobility Date Added: Aug 2011 Format: PDF

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