Dimension Reduction for Object Ranking
Inhaltsverzeichnis
Reference
Toshihiro Kamishima, Shotaro Akaho: Dimension Reduction for Object Ranking. In: Fürnkranz, J. and Hüllermeier, E.: Preference Learning, 2011, 203-215.
DOI
http://dx.doi.org/10.1007/978-3-642-14125-6_10
Abstract
Ordered lists of objects are widely used as representational forms. Such ordered objects include Web search results and bestseller lists. Techniques for processing such ordinal data are being developed, particularly methods for an object ranking task: i.e., learning functions used to sort objects from sample orders. In this article, we propose two dimension reduction methods specifically designed to improve prediction performance in an object ranking task.
Extended Abstract
Bibtex
@incollection{
year={2011},
isbn={978-3-642-14124-9},
booktitle={Preference Learning},
editor={Fürnkranz, Johannes and Hüllermeier, Eyke},
doi={10.1007/978-3-642-14125-6_10},
title={Dimension Reduction for Object Ranking},
url={http://dx.doi.org/10.1007/978-3-642-14125-6_10, http://de.evo-art.org/index.php?title=Dimension_Reduction_for_Object_Ranking },
publisher={Springer Berlin Heidelberg},
author={Kamishima, Toshihiro and Akaho, Shotaro},
pages={203-215},
language={English}
}
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Links
Full Text
http://www.kamishima.net/archive/2009-b-pl1.pdf
