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ECIR
2010
Springer
13 years 11 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
SDM
2009
SIAM
154views Data Mining» more  SDM 2009»
14 years 7 months ago
AMORI: A Metric-Based One Rule Inducer.
The requirements of real-world data mining problems vary extensively. It is plausible to assume that some of these requirements can be expressed as application-specific performan...
Niklas Lavesson, Paul Davidsson
ICML
2007
IEEE
14 years 10 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 10 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
INEX
2004
Springer
14 years 3 months ago
Reliability Tests for the XCG and inex-2002 Metrics
In this paper we compare the effectiveness scores and system rankings obtained with the inex-2002 metric, the official measure of INEX 2004, and the XCG metrics proposed in [4] an...
Gabriella Kazai, Mounia Lalmas, Arjen P. de Vries