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Collaborative filtering

Known as: Cf, Collaborative Filter, Shilling attacks 
Collaborative filtering (CF) is a technique used by recommender systems. Collaborative filtering has two senses, a narrow one and a more general one… 
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Papers overview

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Highly Cited
2017
Highly Cited
2017
In recent years, deep neural networks have yielded immense success on speech recognition, computer vision and natural language… 
Review
2009
Review
2009
As one of the most successful approaches to building recommender systems, collaborative filtering (CF) uses the known preferences… 
Highly Cited
2008
Highly Cited
2008
A common task of recommender systems is to improve customer experience through personalized recommendations based on prior… 
Highly Cited
2007
Highly Cited
2007
Most of the existing approaches to collaborative filtering cannot handle very large data sets. In this paper we show how a class… 
Review
2004
Review
2004
Recommender systems have been evaluated in many, often incomparable, ways. In this article, we review the key decisions in… 
Highly Cited
2003
Highly Cited
2003
Recommendation algorithms are best known for their use on e-commerce Web sites, where they use input about a customer's interests… 
Highly Cited
2001
Highly Cited
2001
Recommender systems apply knowledge discovery techniques to the problem of making personalized recommendations for information… 
Highly Cited
2000
Highly Cited
2000
Automated collaborative filtering (ACF) systems predict a person's affinity for items or information by connecting that person's… 
Highly Cited
1997
Highly Cited
1997
newsgroups carry a wide enough spread of messages to make most individuals consider Usenet news to be a high noise information… 
Highly Cited
1994
Highly Cited
1994
Collaborative filters help people make choices based on the opinions of other people. GroupLens is a system for collaborative…