User performance versus precision measures for simple search tasks
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Privacy-enhancing personalized web search
Proceedings of the 16th international conference on World Wide Web
On anonymizing query logs via token-based hashing
Proceedings of the 16th international conference on World Wide Web
Vanity fair: privacy in querylog bundles
Proceedings of the 17th ACM conference on Information and knowledge management
Releasing search queries and clicks privately
Proceedings of the 18th international conference on World wide web
Privacy-preserving data publishing: A survey of recent developments
ACM Computing Surveys (CSUR)
UPS: efficient privacy protection in personalized web search
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Understanding the privacy-personalization dilemma for web search: a user perspective
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Know your personalization: learning topic level personalization in online services
Proceedings of the 22nd international conference on World Wide Web
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We study the problem of anonymizing user profiles so that user privacy is sufficiently protected while the anonymized profiles are still effective in enabling personalized web search. We propose a Bayes-optimal privacy notion to bound the prior and posterior probability of associating a user with an individual term in the anonymized user profile set. We also propose a novel bundling technique that clusters user profiles into groups by taking into account the semantic relationships between the terms while satisfying the privacy constraint. We evaluate our approach through a set of preliminary experiments using real data demonstrating its feasibility and effectiveness.