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WSDM
2010
ACM
194views Data Mining» more  WSDM 2010»
14 years 5 months ago
Ranking with Query-Dependent Loss for Web Search
Queries describe the users' search intent and therefore they play an essential role in the context of ranking for information retrieval and Web search. However, most of exist...
Jiang Bian, Tie-Yan Liu, Tao Qin, Hongyuan Zha
IR
2010
13 years 6 months ago
Adapting boosting for information retrieval measures
Abstract We present a new ranking algorithm that combines the strengths of two previous methods: boosted tree classification, and LambdaRank, which has been shown to be empiricall...
Qiang Wu, Christopher J. C. Burges, Krysta Marie S...
KDD
2010
ACM
257views Data Mining» more  KDD 2010»
13 years 11 months ago
Multi-task learning for boosting with application to web search ranking
In this paper we propose a novel algorithm for multi-task learning with boosted decision trees. We learn several different learning tasks with a joint model, explicitly addressing...
Olivier Chapelle, Pannagadatta K. Shivaswamy, Srin...
SIGIR
2008
ACM
13 years 7 months ago
Learning to rank at query-time using association rules
Some applications have to present their results in the form of ranked lists. This is the case of many information retrieval applications, in which documents must be sorted accordi...
Adriano Veloso, Humberto Mossri de Almeida, Marcos...
ECML
2007
Springer
13 years 9 months ago
Sequence Labeling with Reinforcement Learning and Ranking Algorithms
Many problems in areas such as Natural Language Processing, Information Retrieval, or Bioinformatic involve the generic task of sequence labeling. In many cases, the aim is to assi...
Francis Maes, Ludovic Denoyer, Patrick Gallinari