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Probabilistic score normalization for rank aggregation

Fernandez, Miriam; Vallet, David and Castells, Pablo (2006). Probabilistic score normalization for rank aggregation. In: Advances in Information Retrieval, pp. 553–556.

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Rank aggregation is a pervading operation in IR technology. We hypothesize that the performance of score-based aggregation may be affected by artificial, usually meaningless deviations consistently occurring in the input score distributions, which distort the combined result when the individual biases differ from each other. We propose a score-based rank aggregation model where the source scores are normalized to a common distribution before being combined. Early experiments on available data from several TREC collections are shown to support our proposal.

Item Type: Conference Item
Copyright Holders: 2006 Springer-Verlag
ISSN: 0302-9743
Extra Information: Advances in Information Retrieval
28th European Conference on IR Research, ECIR 2006
London, UK, April 10-12, 2006
Mounia Lalmas, Andy MacFarlane, Stefan Rüger, Anastasios Tombros, Theodora Tsikrika, Alexei Yavlinsky (Eds.)
ISBN-13 978-3-540-33347-0
Academic Unit/Department: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Centre for Policing Research and Learning (CPRL)
Item ID: 28593
Depositing User: Kay Dave
Date Deposited: 10 May 2011 08:45
Last Modified: 05 Oct 2016 04:06
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