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» Preference-based learning to rank
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ECIR
2010
Springer
13 years 10 months ago
Learning to Select a Ranking Function
Abstract. Learning To Rank (LTR) techniques aim to learn an effective document ranking function by combining several document features. While the function learned may be uniformly ...
Jie Peng, Craig Macdonald, Iadh Ounis
ICML
2007
IEEE
14 years 9 months ago
Cluster analysis of heterogeneous rank data
Cluster analysis of ranking data, which occurs in consumer questionnaires, voting forms or other inquiries of preferences, attempts to identify typical groups of rank choices. Emp...
Ludwig M. Busse, Peter Orbanz, Joachim M. Buhmann
WWW
2008
ACM
14 years 9 months ago
Ranking refinement and its application to information retrieval
We consider the problem of ranking refinement, i.e., to improve the accuracy of an existing ranking function with a small set of labeled instances. We are, particularly, intereste...
Rong Jin, Hamed Valizadegan, Hang Li
AAAI
2008
13 years 10 months ago
Semi-Supervised Ensemble Ranking
Ranking plays a central role in many Web search and information retrieval applications. Ensemble ranking, sometimes called meta-search, aims to improve the retrieval performance b...
Steven C. H. Hoi, Rong Jin
IJCAI
2003
13 years 9 months ago
A Learning Algorithm for Web Page Scoring Systems
Hyperlink analysis is a successful approach to define algorithms which compute the relevance of a document on the basis of the citation graph. In this paper we propose a technique...
Michelangelo Diligenti, Marco Gori, Marco Maggini