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133
Voted
KDD
2010
ACM
265views Data Mining» more  KDD 2010»
15 years 8 months ago
Combining predictions for accurate recommender systems
We analyze the application of ensemble learning to recommender systems on the Netflix Prize dataset. For our analysis we use a set of diverse state-of-the-art collaborative filt...
Michael Jahrer, Andreas Töscher, Robert Legen...
159
Voted
KDD
2010
ACM
257views Data Mining» more  KDD 2010»
15 years 8 months ago
Multi-task learning for boosting with application to web search ranking
In this paper we propose a novel algorithm for multi-task learning with boosted decision trees. We learn several different learning tasks with a joint model, explicitly addressing...
Olivier Chapelle, Pannagadatta K. Shivaswamy, Srin...
KDD
2010
ACM
207views Data Mining» more  KDD 2010»
15 years 8 months ago
Evaluating online ad campaigns in a pipeline: causal models at scale
David Chan, Rong Ge, Ori Gershony, Tim Hesterberg,...
182
Voted
KDD
2010
ACM
259views Data Mining» more  KDD 2010»
15 years 8 months ago
A probabilistic model for personalized tag prediction
Social tagging systems have become increasingly popular for sharing and organizing web resources. Tag recommendation is a common feature of social tagging systems. Social tagging ...
Dawei Yin, Zhenzhen Xue, Liangjie Hong, Brian D. D...
KDD
2010
ACM
235views Data Mining» more  KDD 2010»
15 years 8 months ago
Direct mining of discriminative patterns for classifying uncertain data
Classification is one of the most essential tasks in data mining. Unlike other methods, associative classification tries to find all the frequent patterns existing in the input...
Chuancong Gao, Jianyong Wang