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148
Voted
KDD
2008
ACM
147views Data Mining» more  KDD 2008»
16 years 3 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...
146
Voted
KDD
2007
ACM
191views Data Mining» more  KDD 2007»
16 years 3 months ago
Cost-effective outbreak detection in networks
Given a water distribution network, where should we place sensors to quickly detect contaminants? Or, which blogs should we read to avoid missing important stories? These seemingl...
Andreas Krause, Carlos Guestrin, Christos Faloutso...
138
Voted
WSDM
2010
ACM
188views Data Mining» more  WSDM 2010»
16 years 25 days ago
Anatomy of the Long Tail: Ordinary People with Extraordinary Tastes
The success of "infinite-inventory" retailers such as Amazon.com and Netflix has been ascribed to a "long tail" phenomenon. To wit, while the majority of their...
Andrei Z. Broder, Bo Pang, Evgeniy Gabrilovich, Sh...
145
Voted
KDD
2010
ACM
247views Data Mining» more  KDD 2010»
15 years 5 months ago
Active learning for biomedical citation screening
Active learning (AL) is an increasingly popular strategy for mitigating the amount of labeled data required to train classifiers, thereby reducing annotator effort. We describe ...
Byron C. Wallace, Kevin Small, Carla E. Brodley, T...
159
Voted
WSDM
2012
ACM
283views Data Mining» more  WSDM 2012»
13 years 11 months ago
The life and death of online groups: predicting group growth and longevity
We pose a fundamental question in understanding how to identify and design successful communities: What factors predict whether a community will grow and survive in the long term?...
Sanjay Ram Kairam, Dan J. Wang, Jure Leskovec