Privacy Auctions for Recommender Systems
نویسندگان
چکیده
منابع مشابه
Privacy 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...
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Privacy issues are an undying obstacle to the adoption of recommender systems, because recommender systems critically rely on their users to disclose information about themselves. While there exist several technical solutions to reduce the exposure of such personal information (e.g. client-side personalization, homomorphic encryption, k-anonymity), the concept of privacy is an inherently human ...
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Recommender systems involve an inherent trade-off between accuracy of recommendations and the extent to which users are willing to release information about their preferences. In this paper, we explore a two-tiered notion of privacy where there is a small set of “public” users who are willing to share their preferences openly, and a large set of “private” users who require privacy guarantees. W...
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R ecommender systems have become important tools in ecommerce. They combine one user’s ratings of products or services with ratings from other users to answer queries such as “Would I like X?” with predictions and suggestions. Users thus receive anonymous recommendations from people with similar tastes. While this process seems innocuous, it aggregates user preferences in ways analogous to stat...
متن کاملPrivacy Aspects of Recommender Systems
The popularity of online recommender systems has soared; they are deployed in numerous websites and gather tremendous amounts of user data that are necessary for the recommendation purposes. This data, however, may pose a severe threat to user privacy, if accessed by untrusted parties or used inappropriately. Hence, it is of paramount importance for recommender system designers and service prov...
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ژورنال
عنوان ژورنال: ACM Transactions on Economics and Computation
سال: 2014
ISSN: 2167-8375,2167-8383
DOI: 10.1145/2629665