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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
AVI
2004
13 years 10 months ago
More than the sum of its members: challenges for group recommender systems
Systems that recommend items to a group of two or more users raise a number of challenging issues that are so far only partly understood. This paper identifies four of these issue...
Anthony Jameson
ESWA
2008
152views more  ESWA 2008»
13 years 8 months ago
Collaborative recommender systems: Combining effectiveness and efficiency
Recommender systems base their operation on past user ratings over a collection of items, for instance, books, CDs, etc. Collaborative filtering (CF) is a successful recommendatio...
Panagiotis Symeonidis, Alexandros Nanopoulos, Apos...
WWW
2009
ACM
14 years 9 months ago
Matchbox: large scale online bayesian recommendations
We present a probabilistic model for generating personalised recommendations of items to users of a web service. The Matchbox system makes use of content information in the form o...
David H. Stern, Ralf Herbrich, Thore Graepel
DL
2000
Springer
173views Digital Library» more  DL 2000»
14 years 27 days ago
Content-based book recommending using learning for text categorization
Recommender systems improve access to relevant products and information by making personalized suggestions based on previous examples of a user's likes and dislikes. Most exi...
Raymond J. Mooney, Loriene Roy