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CIKM
2008
Springer
13 years 8 months ago
SoRec: social recommendation using probabilistic matrix factorization
Data sparsity, scalability and prediction quality have been recognized as the three most crucial challenges that every collaborative filtering algorithm or recommender system conf...
Hao Ma, Haixuan Yang, Michael R. Lyu, Irwin King
STAIRS
2008
169views Education» more  STAIRS 2008»
13 years 7 months ago
Probabilistic Association Rules for Item-Based Recommender Systems
Since the beginning of the 1990's, the Internet has constantly grown, proposing more and more services and sources of information. The challenge is no longer to provide users ...
Sylvain Castagnos, Armelle Brun, Anne Boyer
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
ICDM
2008
IEEE
183views Data Mining» more  ICDM 2008»
14 years 22 days 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
KDD
2003
ACM
129views Data Mining» more  KDD 2003»
14 years 6 months ago
Nantonac collaborative filtering: recommendation based on order responses
A recommender system suggests the items expected to be preferred by the users. Recommender systems use collaborative filtering to recommend items by summarizing the preferences of...
Toshihiro Kamishima