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WWW
2009
ACM
16 years 2 months ago
Matchbox: large scale online bayesian recommendations
We present a probabilistic model for generating personalised recommendations of items to users of a web service. The Matchbox system makes use of content information in the form o...
David H. Stern, Ralf Herbrich, Thore Graepel
CHI
2009
ACM
16 years 2 months ago
Making sense of strangers' expertise from signals in digital artifacts
Contemporary work increasingly involves interacting with strangers in technology-mediated environments. In this context, we come to rely on digital artifacts to infer characterist...
N. Sadat Shami, Kate Ehrlich, Geri Gay, Jeffrey T....
KDD
2009
ACM
219views Data Mining» more  KDD 2009»
16 years 2 months ago
Structured correspondence topic models for mining captioned figures in biological literature
A major source of information (often the most crucial and informative part) in scholarly articles from scientific journals, proceedings and books are the figures that directly pro...
Amr Ahmed, Eric P. Xing, William W. Cohen, Robert ...
KDD
2009
ACM
305views Data Mining» more  KDD 2009»
16 years 2 months ago
Grocery shopping recommendations based on basket-sensitive random walk
We describe a recommender system in the domain of grocery shopping. While recommender systems have been widely studied, this is mostly in relation to leisure products (e.g. movies...
Ming Li, M. Benjamin Dias, Ian H. Jarman, Wael El-...
KDD
2008
ACM
147views Data Mining» more  KDD 2008»
16 years 2 months ago
Structured learning for non-smooth ranking losses
Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major te...
Soumen Chakrabarti, Rajiv Khanna, Uma Sawant, Chir...