Université de Fribourg

Privacy-preserving social media data publishing for personalized ranking-based recommendation

Yang, Dingqi ; Qu, Bingqing ; Cudré-Mauroux, Philippe

In: IEEE Transactions on Knowledge and Data Engineering, 2019, vol. 31, no. 3, p. 507–520

Personalized recommendation is crucial to help users find pertinent information. It often relies on a large collection of user data, in particular users' online activity (e.g., tagging/rating/checking-in) on social media, to mine user preference. However, releasing such user activity data makes users vulnerable to inference attacks, as private data (e.g., gender) can often be inferred from...