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» Listwise approach to learning to rank: theory and algorithm
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WWW
2011
ACM
13 years 3 months ago
Learning to re-rank: query-dependent image re-ranking using click data
Our objective is to improve the performance of keyword based image search engines by re-ranking their baseline results. To this end, we address three limitations of existing searc...
Vidit Jain, Manik Varma
KDD
2005
ACM
177views Data Mining» more  KDD 2005»
14 years 9 months ago
Query chains: learning to rank from implicit feedback
This paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. We observe that users searching the web often perform ...
Filip Radlinski, Thorsten Joachims
CIKM
2008
Springer
13 years 11 months ago
Ranking information resources in peer-to-peer text retrieval: an experimental study
This paper experimentally studies approaches to the problem of ranking information resources w.r.t. user queries in peer-to-peer information retrieval. In distributed environments...
Hans F. Witschel
IJCNN
2006
IEEE
14 years 3 months ago
Learning to Rank by Maximizing AUC with Linear Programming
— Area Under the ROC Curve (AUC) is often used to evaluate ranking performance in binary classification problems. Several researchers have approached AUC optimization by approxi...
Kaan Ataman, W. Nick Street, Yi Zhang
ICML
2009
IEEE
14 years 9 months ago
Bayesian inference for Plackett-Luce ranking models
This paper gives an efficient Bayesian method for inferring the parameters of a PlackettLuce ranking model. Such models are parameterised distributions over rankings of a finite s...
John Guiver, Edward Snelson