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SIGIR
2006
ACM
13 years 10 months ago
Learning a ranking from pairwise preferences
We introduce a novel approach to combining rankings from multiple retrieval systems. We use a logistic regression model or an SVM to learn a ranking from pairwise document prefere...
Ben Carterette, Desislava Petkova
AI
2008
Springer
13 years 4 months ago
Label ranking by learning pairwise preferences
Preference learning is a challenging problem that involves the prediction of complex structures, such as weak or partial order relations, rather than single values. In the recent ...
Eyke Hüllermeier, Johannes Fürnkranz, We...
ECML
2003
Springer
13 years 9 months ago
Pairwise Preference Learning and Ranking
We consider supervised learning of a ranking function, which is a mapping from instances to total orders over a set of labels (options). The training information consists of exampl...
Johannes Fürnkranz, Eyke Hüllermeier
IDA
2005
Springer
13 years 10 months ago
Learning Label Preferences: Ranking Error Versus Position Error
We consider the problem of learning a ranking function, that is a mapping from instances to rankings over a finite number of labels. Our learning method, referred to as ranking by...
Eyke Hüllermeier, Johannes Fürnkranz
COLING
2010
12 years 11 months ago
Cross-Market Model Adaptation with Pairwise Preference Data for Web Search Ranking
Machine-learned ranking techniques automatically learn a complex document ranking function given training data. These techniques have demonstrated the effectiveness and flexibilit...
Jing Bai, Fernando Diaz, Yi Chang, Zhaohui Zheng, ...