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» Adapting ranking SVM to document retrieval
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CIKM
2009
Springer
13 years 11 months ago
Learning to rank from Bayesian decision inference
Ranking is a key problem in many information retrieval (IR) applications, such as document retrieval and collaborative filtering. In this paper, we address the issue of learning ...
Jen-Wei Kuo, Pu-Jen Cheng, Hsin-Min Wang
KDD
2002
ACM
169views Data Mining» more  KDD 2002»
14 years 5 months ago
Optimizing search engines using clickthrough data
This paper presents an approach to automatically optimizing the retrieval quality of search engines using clickthrough data. Intuitively, a good information retrieval system shoul...
Thorsten Joachims
GECCO
2009
Springer
151views Optimization» more  GECCO 2009»
13 years 11 months ago
Swarming to rank for information retrieval
This paper presents an approach to automatically optimize the retrieval quality of ranking functions. Taking a Swarm Intelligence perspective, we present a novel method, SwarmRank...
Ernesto Diaz-Aviles, Wolfgang Nejdl, Lars Schmidt-...
SIGIR
2006
ACM
13 years 10 months ago
Learning a ranking from pairwise preferences
We introduce a novel approach to combining rankings from multiple retrieval systems. We use a logistic regression model or an SVM to learn a ranking from pairwise document prefere...
Ben Carterette, Desislava Petkova
AAAI
2008
13 years 7 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