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SDM
2012
SIAM
281views Data Mining» more  SDM 2012»
11 years 6 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
JMLR
2010
173views more  JMLR 2010»
12 years 11 months ago
Collaborative Filtering via Rating Concentration
While most popular collaborative filtering methods use low-rank matrix factorization and parametric density assumptions, this article proposes an approach based on distribution-fr...
Bert Huang, Tony Jebara
RECSYS
2010
ACM
13 years 4 months ago
Multiverse recommendation: n-dimensional tensor factorization for context-aware collaborative filtering
Context has been recognized as an important factor to consider in personalized Recommender Systems. However, most model-based Collaborative Filtering approaches such as Matrix Fac...
Alexandros Karatzoglou, Xavier Amatriain, Linas Ba...
RECSYS
2010
ACM
13 years 4 months ago
Collaborative filtering via euclidean embedding
Recommendation systems suggest items based on user preferences. Collaborative filtering is a popular approach in which recommending is based on the rating history of the system. O...
Mohammad Khoshneshin, W. Nick Street
CORR
2010
Springer
175views Education» more  CORR 2010»
13 years 4 months ago
Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes
Probabilistic matrix factorization (PMF) is a powerful method for modeling data associated with pairwise relationships, finding use in collaborative filtering, computational biolo...
Ryan Prescott Adams, George E. Dahl, Iain Murray