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SIGIR
2002
ACM
13 years 4 months ago
Collaborative filtering with privacy via factor analysis
Collaborative filtering (CF) is valuable in e-commerce, and for direct recommendations for music, movies, news etc. But today's systems have several disadvantages, including ...
John F. Canny
ATAL
2007
Springer
13 years 11 months ago
An agent-based approach for privacy-preserving recommender systems
Recommender Systems are used in various domains to generate personalized information based on personal user data. The ability to preserve the privacy of all participants is an ess...
Richard Cissée, Sahin Albayrak
MMM
2009
Springer
169views Multimedia» more  MMM 2009»
14 years 2 months ago
Personalized Image Recommendation
—In this paper, we have developed a novel framework called JustClick to enable personalized image recommendation via exploratory search from large-scale collections of manuallyan...
Yuli Gao, Hangzai Luo, Jianping Fan
TKDD
2010
121views more  TKDD 2010»
13 years 3 months ago
Factor in the neighbors: Scalable and accurate collaborative filtering
Recommender systems provide users with personalized suggestions for products or services. These systems often rely on Collaborating Filtering (CF), where past transactions are ana...
Yehuda Koren
SDM
2012
SIAM
281views Data Mining» more  SDM 2012»
11 years 7 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