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RECSYS
2009
ACM
14 years 2 months ago
Ordering innovators and laggards for product categorization and recommendation
Different buyers exhibit different purchasing behaviors. Some rush to purchase new products while others tend to be more cautious, waiting for reviews from people they trust. In...
Sarah K. Tyler, Shenghuo Zhu, Yun Chi, Yi Zhang
ML
2008
ACM
146views Machine Learning» more  ML 2008»
13 years 7 months ago
Improving maximum margin matrix factorization
Abstract. Collaborative filtering is a popular method for personalizing product recommendations. Maximum Margin Matrix Factorization (MMMF) has been proposed as one successful lear...
Markus Weimer, Alexandros Karatzoglou, Alex J. Smo...
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
RECSYS
2010
ACM
13 years 7 months ago
Global budgets for local recommendations
We present the design, implementation and evaluation of a new geotagging service, Gloe, that makes it easy to find, rate and recommend arbitrary on-line content in a mobile settin...
Thomas Sandholm, Hang Ung, Christina Aperjis, Bern...
SIGIR
2006
ACM
14 years 1 months ago
Personalized recommendation driven by information flow
We propose that the information access behavior of a group of people can be modeled as an information flow issue, in which people intentionally or unintentionally influence and in...
Xiaodan Song, Belle L. Tseng, Ching-Yung Lin, Ming...