Learning a ranking from pairwise preferences
Published 6 August 2006
Ben Carterette, Desislava Petkova
Citations38
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TL;DR
A novel approach to combining rankings from multiple retrieval systems using a logistic regression model or an SVM to learn a ranking from pairwise document preferences, which outperforms a popular voting algorithm.
Abstract
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 preferences. Our approach requires no training data or relevance scores, and outperforms a popular voting algorithm.
Keywords
Computer Science
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