Recommending with an Agenda: Active Learning of Private Attributes using Matrix Factorization

26 Nov 2013Smriti BhagatUdi WeinsbergStratis IoannidisNina Taft

Recommender systems leverage user demographic information, such as age, gender, etc., to personalize recommendations and better place their targeted ads. Oftentimes, users do not volunteer this information due to privacy concerns, or due to a lack of initiative in filling out their online profiles... (read more)

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