Privacy risks in recommender systems

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Privacy Risks in Recommender Systems

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...

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Privacy risks in recommender systems - Internet Computing, IEEE

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...

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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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ژورنال

عنوان ژورنال: IEEE Internet Computing

سال: 2001

ISSN: 1089-7801

DOI: 10.1109/4236.968832