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CIKM
2001
Springer
13 years 10 months ago
Selecting Relevant Instances for Efficient and Accurate Collaborative Filtering
Collaborative filtering uses a database about consumers’ preferences to make personal product recommendations and is achieving widespread success in both E-Commerce and Informat...
Kai Yu, Xiaowei Xu, Martin Ester, Hans-Peter Krieg...
IPAS
2008
13 years 8 months ago
Image restoration by sparse 3D transform-domain collaborative filtering
We propose an image restoration technique exploiting regularized inversion and the recent block-matching and 3D filtering (BM3D) denoising filter. The BM3D employs a non-local mod...
Kostadin Dabov, Alessandro Foi, Vladimir Katkovnik...
IPAS
2008
13 years 8 months ago
Image restoration by sparse 3D transform-domain collaborative filtering
We propose an image restoration technique exploiting regularized inversion and the recent block-matching and 3D filtering (BM3D) denoising filter. The BM3D employs a non-local mod...
Kostadin Dabov, Alessandro Foi, Vladimir Katkovnik...
RECSYS
2010
ACM
13 years 6 months ago
Nantonac collaborative filtering: a model-based approach
A recommender system has to collect users' preference data. To collect such data, rating or scoring methods that use rating scales, such as good-fair-poor or a five-point-sca...
Toshihiro Kamishima, Shotaro Akaho
CIKM
2005
Springer
13 years 11 months ago
Person resolution in person search results: WebHawk
Finding information about people on the Web using a search engine is difficult because there is a many-to-many mapping between person names and specific persons (i.e. referents). ...
Xiaojun Wan, Jianfeng Gao, Mu Li, Binggong Ding