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2010
ACM

Anonymizing user profiles for personalized web search

11 years 4 hour ago
Anonymizing user profiles for personalized web search
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. Categories and Subject Descriptors: H.2.7 [Database Administration]: Security, integrity, and protection; H.3.3. [Information Search and Retrieval] General Terms: Design, Experimentation, Security
Yun Zhu, Li Xiong, Christopher Verdery
Added 06 Dec 2010
Updated 06 Dec 2010
Type Conference
Year 2010
Where WWW
Authors Yun Zhu, Li Xiong, Christopher Verdery
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