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» Using mixture models for collaborative filtering
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RECSYS
2010
ACM
13 years 8 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
DPHOTO
2010
360views Hardware» more  DPHOTO 2010»
13 years 10 months ago
Signal-dependent raw image denoising using sensor noise characterization via multiple acquisitions
Accurate noise level estimation is essential to assure good performance of noise reduction filters. Noise contaminating raw images is typically modeled as additive white and Gauss...
Angelo Bosco, Arcangelo Bruna, D. Giacalone, Sebas...
CIKM
2009
Springer
14 years 3 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
ICDM
2008
IEEE
183views Data Mining» more  ICDM 2008»
14 years 3 months ago
Collaborative Filtering for Implicit Feedback Datasets
A common task of recommender systems is to improve customer experience through personalized recommendations based on prior implicit feedback. These systems passively track differe...
Yifan Hu, Yehuda Koren, Chris Volinsky
WEBI
2007
Springer
14 years 2 months ago
An Augmented Tagging Scheme with Triple Tagging and Collective Filtering
Collaborative tagging is increasingly drawing attentions. However the keyword based tagging scheme has its limitations and it can be observed that tagging society are seeking and ...
Jie Yang, Yutaka Matsuo, Mitsuru Ishizuka