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» Explaining collaborative filtering recommendations
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SDM
2012
SIAM
281views Data Mining» more  SDM 2012»
11 years 10 months ago
Contextual Collaborative Filtering via Hierarchical Matrix Factorization
Matrix factorization (MF) has been demonstrated to be one of the most competitive techniques for collaborative filtering. However, state-of-the-art MFs do not consider contextual...
ErHeng Zhong, Wei Fan, Qiang Yang
WIRI
2005
IEEE
14 years 1 months ago
Collaborative Filtering by Mining Association Rules from User Access Sequences
Recent research in mining user access patterns for predicting Web page requests focuses only on consecutive sequential Web page accesses, i.e., pages which are accessed by followi...
Mei-Ling Shyu, Choochart Haruechaiyasak, Shu-Ching...
KDD
2007
ACM
191views Data Mining» more  KDD 2007»
14 years 8 months ago
Modeling relationships at multiple scales to improve accuracy of large recommender systems
The collaborative filtering approach to recommender systems predicts user preferences for products or services by learning past useritem relationships. In this work, we propose no...
Robert M. Bell, Yehuda Koren, Chris Volinsky
UIST
2009
ACM
14 years 2 months ago
CommunityCommands: command recommendations for software applications
We explore the use of modern recommender system technology to address the problem of learning software applications. Before describing our new command recommender system, we first...
Justin Matejka, Wei Li, Tovi Grossman, George W. F...
SAC
2008
ACM
13 years 7 months ago
Whom should I trust?: the impact of key figures on cold start recommendations
Generating adequate recommendations for newcomers is a hard problem for a recommender system (RS) due to lack of detailed user profiles and social preference data. Empirical evide...
Patricia Victor, Chris Cornelis, Ankur Teredesai, ...