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NIPS
2008
13 years 10 months ago
Stochastic Relational Models for Large-scale Dyadic Data using MCMC
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
Shenghuo Zhu, Kai Yu, Yihong Gong
WWW
2011
ACM
13 years 4 months ago
Ranking in context-aware recommender systems
As context is acknowledged as an important factor that can affect users’ preferences, many researchers have worked on improving the quality of recommender systems by utilizing ...
Minsuk Kahng, Sangkeun Lee, Sang-goo Lee
WKDD
2010
CPS
204views Data Mining» more  WKDD 2010»
14 years 2 months ago
A Scalable, Accurate Hybrid Recommender System
—Recommender systems apply machine learning techniques for filtering unseen information and can predict whether a user would like a given resource. There are three main types of...
Mustansar Ali Ghazanfar, Adam Prügel-Bennett
ACMICEC
2007
ACM
117views ECommerce» more  ACMICEC 2007»
14 years 1 months ago
Selectively acquiring ratings for product recommendation
Accurate prediction of customer preferences on products is the key to any recommender systems to realize its promised strategic values such as improved customer satisfaction and t...
Zan Huang
ICDM
2009
IEEE
130views Data Mining» more  ICDM 2009»
14 years 3 months ago
Active Learning with Generalized Queries
—Active learning can actively select or construct examples to label to reduce the number of labeled examples needed for building accurate classifiers. However, previous works of...
Jun Du, Charles X. Ling