Examining users' attitude towards privacy preserving collaborative filtering

Shlomo Berkovsky, Nikita Borisov, Yaniv Eytani, Tsvi Kuflik, Francesco Ricci

Research output: Contribution to conferencePaperpeer-review


Privacy hazard to Web-based information services represents an important obstacle to the growth and diffusion of the personalized services. Data obfuscation methods were proposed for enhancing the users’ privacy in recommender systems based on collaborative filtering. Data obfuscation can provide statistically measurable privacy gains. However, these are measured using metrics that may not be necessarily intuitively understandable by end user, such as conditional entropy. In fact, it could happen that the users are unaware, misunderstand how their privacy is being preserved or do not feel comfortable with such methods. Thus, these may not reflect in the users’ actual personal sense of privacy. In this work we provide an exploratory study to examine correlation between different data obfuscation methods and their effect on the subjective sense of privacy of users. We analyze users’ opinion about the impact of data obfuscation on different types of users’ rating values and generally on their sense of privacy.
Original languageEnglish
Number of pages7
StatePublished - 2007
EventWorkshop on Data Mining for User Modeling (K-DUUM), co-located with UM 2007 - Corfu, Greece
Duration: 25 Jun 2007 → …


ConferenceWorkshop on Data Mining for User Modeling (K-DUUM), co-located with UM 2007
Period25/06/07 → …


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