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» Regression-based latent factor models
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RECSYS
2010
ACM
14 years 9 months ago
Collaborative filtering via euclidean embedding
Recommendation systems suggest items based on user preferences. Collaborative filtering is a popular approach in which recommending is based on the rating history of the system. O...
Mohammad Khoshneshin, W. Nick Street
CSDA
2010
165views more  CSDA 2010»
14 years 9 months ago
A two-component Weibull mixture to model early and late mortality in a Bayesian framework
A two component parametric mixture is proposed to model survival after an invasive treatment, when patients may experience different hazards regimes: a risk of early mortality dir...
Alessio Farcomeni, Alessandra Nardi
KDD
2004
ACM
173views Data Mining» more  KDD 2004»
15 years 3 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
ICDM
2010
IEEE
172views Data Mining» more  ICDM 2010»
14 years 7 months ago
Learning Attribute-to-Feature Mappings for Cold-Start Recommendations
Cold-start scenarios in recommender systems are situations in which no prior events, like ratings or clicks, are known for certain users or items. To compute predictions in such ca...
Zeno Gantner, Lucas Drumond, Christoph Freudenthal...
NIPS
2003
14 years 11 months ago
Hierarchical Topic Models and the Nested Chinese Restaurant Process
We address the problem of learning topic hierarchies from data. The model selection problem in this domain is daunting—which of the large collection of possible trees to use? We...
David M. Blei, Thomas L. Griffiths, Michael I. Jor...