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Suppose that a Facebook user, whose age is hidden or missing, likes Britney Spears. Can one guess his/her age? Knowing that most Britney fans are teenagers, it is fairly easy for humans to answer this question. Interests (or "Likes") of users is one of the highly-available on-line information. In this paper, the authors show how these seemingly harmless interests (e.g., music interests) can leak privacy-sensitive information about users. In particular, they infer their undisclosed (private) attributes using the public attributes of other users sharing similar interests. In order to compare user-defined interest names, they extract their semantics using an ontologized version of Wikipedia and measure their similarity by applying a statistical learning method.
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