Privacy-Preserving Friendship-Based Recommender Systems
نویسندگان
چکیده
منابع مشابه
Privacy-preserving Friendship-based Recommender Systems
Today, recommender systems are playing an indispensable role in our daily life. However, nothing is for free – such systems have also upset the society with severe privacy concerns. In this paper, we first revisit the concept of computing recommendations based on inputs from both a user’s friends and a set of randomly chosen strangers. We propose two security models to formalize information lea...
متن کاملPreserving Privacy in Web Recommender Systems
The rapid growth of the Web has led to the development of new solutions in the Web recommender or personalization domain, aimed to assist users in satisfying their information needs. The main goal of this chapter is to survey some of the recommender system proposals appeared in the literature, and to evaluate these proposals from the point of view of privacy preservation. Then, as an example of...
متن کاملPrivacy-Preserving Context-Aware Recommender Systems: Analysis and New Solutions
Nowadays, recommender systems have become an indispensable part of our daily life and provide personalized services for almost everything. However, nothing is for free – such systems have also upset the society with severe privacy concerns because they accumulate a lot of personal information in order to provide recommendations. In this work, we construct privacy-preserving recommendation proto...
متن کاملOn Privacy-preserving Context-aware Recommender System
Privacy is an important issue in Context-aware recommender systems (CARSs). In this paper, we propose a privacy-preserving CARS in which a user can limit the contextual information submitted to the server without sacrificing a significant recommendation accuracy. Specifically, for users, we introduce a client-side algorithm that the user can employ to generalize its context to some extent, in o...
متن کاملPrivacy in Recommender Systems
In many online applications, the range of content that is offered to users is so wide that a need for automated recommender systems arises. Such systems can provide a personalized selection of relevant items to users. In practice, this can help people find entertaining movies, boost sales through targeted advertisements, or help social network users meet new friends. To generate accurate person...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Dependable and Secure Computing
سال: 2018
ISSN: 1545-5971,1941-0018,2160-9209
DOI: 10.1109/tdsc.2016.2631533