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ISMIS
2005
Springer
13 years 11 months ago
Incremental Collaborative Filtering for Highly-Scalable Recommendation Algorithms
Most recommendation systems employ variations of Collaborative Filtering (CF) for formulating suggestions of items relevant to users’ interests. However, CF requires expensive co...
Manos Papagelis, Ioannis Rousidis, Dimitris Plexou...
ICPR
2008
IEEE
14 years 7 months ago
Efficient user preference predictions using collaborative filtering
Two major challenges in collaborative filtering are the efficiency of the algorithms and the quality of the recommendations. A variety of machine learning methods have been applie...
C. Lee Giles, Yang Song
AAIM
2008
Springer
208views Algorithms» more  AAIM 2008»
13 years 8 months ago
Large-Scale Parallel Collaborative Filtering for the Netflix Prize
Many recommendation systems suggest items to users by utilizing the techniques of collaborative filtering (CF) based on historical records of items that the users have viewed, purc...
Yunhong Zhou, Dennis M. Wilkinson, Robert Schreibe...
SIGIR
2008
ACM
13 years 6 months ago
Personalized active learning for collaborative filtering
Collaborative Filtering (CF) requires user-rated training examples for statistical inference about the preferences of new users. Active learning strategies identify the most infor...
Abhay Harpale, Yiming Yang
ITRUST
2005
Springer
13 years 11 months ago
Alleviating the Sparsity Problem of Collaborative Filtering Using Trust Inferences
Collaborative Filtering (CF), the prevalent recommendation approach, has been successfully used to identify users that can be characterized as “similar” according to their logg...
Manos Papagelis, Dimitris Plexousakis, Themistokli...