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» Estimating Probabilities in Recommendation Systems
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91
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CORR
2010
Springer
118views Education» more  CORR 2010»
14 years 9 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
15 years 6 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
116
Voted
SDM
2003
SIAM
123views Data Mining» more  SDM 2003»
15 years 1 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
16 years 1 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
104
Voted
SIGIR
2006
ACM
15 years 6 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...