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» Estimating Probabilities in Recommendation Systems
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CORR
2010
Springer
118views Education» more  CORR 2010»
13 years 1 months ago
Estimating Probabilities in Recommendation Systems
Modeling ranked data is an essential component in a number of important applications including recommendation systems and websearch. In many cases, judges omit preference among un...
Mingxuan Sun, Guy Lebanon, Paul Kidwell
RECSYS
2009
ACM
13 years 11 months ago
Collaborative prediction and ranking with non-random missing data
A fundamental aspect of rating-based recommender systems is the observation process, the process by which users choose the items they rate. Nearly all research on collaborative ï¬...
Benjamin M. Marlin, Richard S. Zemel
SDM
2003
SIAM
123views Data Mining» more  SDM 2003»
13 years 6 months ago
Fast Online SVD Revisions for Lightweight Recommender Systems
The singular value decomposition (SVD) is fundamental to many data modeling/mining algorithms, but SVD algorithms typically have quadratic complexity and require random access to ...
Matthew Brand
ICML
2001
IEEE
14 years 5 months ago
Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers
Accurate, well-calibrated estimates of class membership probabilities are needed in many supervised learning applications, in particular when a cost-sensitive decision must be mad...
Bianca Zadrozny, Charles Elkan
SIGIR
2006
ACM
13 years 10 months ago
Personalized recommendation driven by information flow
We propose that the information access behavior of a group of people can be modeled as an information flow issue, in which people intentionally or unintentionally influence and in...
Xiaodan Song, Belle L. Tseng, Ching-Yung Lin, Ming...