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» Collaborative filtering with privacy via factor analysis
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CIKM
2009
Springer
13 years 11 months ago
Semi-nonnegative matrix factorization with global statistical consistency for collaborative filtering
Collaborative Filtering, considered by many researchers as the most important technique for information filtering, has been extensively studied by both academic and industrial co...
Hao Ma, Haixuan Yang, Irwin King, Michael R. Lyu
SIGIR
2009
ACM
13 years 11 months ago
Fast nonparametric matrix factorization for large-scale collaborative filtering
With the sheer growth of online user data, it becomes challenging to develop preference learning algorithms that are sufficiently flexible in modeling but also affordable in com...
Kai Yu, Shenghuo Zhu, John D. Lafferty, Yihong Gon...
IIR
2010
13 years 6 months ago
An Empirical Comparison of Collaborative Filtering Approaches on Netflix Data
Recommender systems are widely used in E-Commerce for making automatic suggestions of new items that could meet the interest of a given user. Collaborative Filtering approaches co...
Nicola Barbieri, Massimo Guarascio, Ettore Ritacco
JMLR
2010
173views more  JMLR 2010»
12 years 11 months ago
Collaborative Filtering via Rating Concentration
While most popular collaborative filtering methods use low-rank matrix factorization and parametric density assumptions, this article proposes an approach based on distribution-fr...
Bert Huang, Tony Jebara
KDD
2004
ACM
173views Data Mining» more  KDD 2004»
13 years 10 months ago
Collaborative Quality Filtering: Establishing Consensus or Recovering Ground Truth?
We present a algorithm based on factor analysis for performing collaborative quality filtering (CQF). Unlike previous approaches to CQF, which estimate the consensus opinion of a...
Jonathan Traupman, Robert Wilensky