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Measuring the privacy of user profiles in personalized information systems
Personalized information systems are information-filtering systems that endeavor to tailor
information-exchange functionality to the specific interests of their users. The ability of these …
information-exchange functionality to the specific interests of their users. The ability of these …
Comparing recommender systems using synthetic data
In this work, we propose SynRec, a data protection framework that uses data synthesis. The
goal is to protect sensitive information in the user-item matrix by replacing the original values …
goal is to protect sensitive information in the user-item matrix by replacing the original values …
A survey of privacy-preserving collaborative filtering schemes
With increasing need for preserving confidential data while providing recommendations,
privacy-preserving collaborative filtering has been receiving increasing attention. To make …
privacy-preserving collaborative filtering has been receiving increasing attention. To make …
Privacy-preserving enhanced collaborative tagging
Collaborative tagging is one of the most popular services available online, and it allows end
user to loosely classify either online or offline resources based on their feedback, expressed …
user to loosely classify either online or offline resources based on their feedback, expressed …
[HTML][HTML] Privacy protection against user profiling through optimal data generalization
Personalized information systems are information-filtering systems that endeavor to tailor
information-exchange functionality to the specific interests of their users. The ability of these …
information-exchange functionality to the specific interests of their users. The ability of these …
[HTML][HTML] Optimal forgery and suppression of ratings for privacy enhancement in recommendation systems
Recommendation systems are information-filtering systems that tailor information to users on
the basis of knowledge about their preferences. The ability of these systems to profile users …
the basis of knowledge about their preferences. The ability of these systems to profile users …
A practical system for privacy-preserving collaborative filtering
Collaborative filtering is a widely-used technique in online services to enhance the accuracy
of a recommender system. This technique, however, comes at the cost of users having to …
of a recommender system. This technique, however, comes at the cost of users having to …
Protecting private attributes in app based mobile user profiling
The Analytics companies enable successful targeted advertising via user profiles, derived
from the mobile apps installed by specific users, and hence have become an integral part of …
from the mobile apps installed by specific users, and hence have become an integral part of …
Differential data analysis for recommender systems
We present techniques to characterize which data contributes most to the accuracy of a
recommendation algorithm. Our main technique is called differential data analysis. The …
recommendation algorithm. Our main technique is called differential data analysis. The …
Privacy preserving collaborative filtering from asymmetric randomized encoding
Collaborative filtering is a famous technique in recommendation systems. Yet, it requires the
users to reveal their preferences, which has undesirable privacy implications. Over the …
users to reveal their preferences, which has undesirable privacy implications. Over the …