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» Explaining collaborative filtering recommendations
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WECWIS
2005
IEEE
137views ECommerce» more  WECWIS 2005»
14 years 1 months ago
Using Singular Value Decomposition Approximation for Collaborative Filtering
Singular Value Decomposition (SVD), together with the Expectation-Maximization (EM) procedure, can be used to find a low-dimension model that maximizes the loglikelihood of obser...
Sheng Zhang, Weihong Wang, James Ford, Fillia Make...
FLAIRS
2008
13 years 10 months ago
A Mixture Imputation-Boosted Collaborative Filter
Recommendation systems suggest products to users. Collaborative filtering (CF) systems, which base those recommendations on a database of previous ratings by various users and pro...
Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greine...
WEBI
2007
Springer
14 years 1 months ago
Hybrid Collaborative Filtering Algorithms Using a Mixture of Experts
Collaborative filtering (CF) is one of the most successful approaches for recommendation. In this paper, we propose two hybrid CF algorithms, sequential mixture CF and joint mixtu...
Xiaoyuan Su, Russell Greiner, Taghi M. Khoshgoftaa...
WEBI
2010
Springer
13 years 5 months ago
Reducing the Cold-Start Problem in Content Recommendation through Opinion Classification
Like search engines, recommender systems have become a tool that cannot be ignored by websites with a large selection of products, music, news or simply webpages links. The perform...
Damien Poirier, Françoise Fessant, Isabelle...
UAI
2003
13 years 9 months ago
Active Collaborative Filtering
Collaborative filtering (CF) allows the preferences of multiple users to be pooled to make recommendations regarding unseen products. We consider in this paper the problem of onl...
Craig Boutilier, Richard S. Zemel, Benjamin M. Mar...