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» Relevance Ranking Using Kernels
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SIGIR
2012
ACM
13 years 5 months ago
Learning to suggest: a machine learning framework for ranking query suggestions
We consider the task of suggesting related queries to users after they issue their initial query to a web search engine. We propose a machine learning approach to learn the probab...
Umut Ozertem, Olivier Chapelle, Pinar Donmez, Emre...
85
Voted
VLDB
2007
ACM
102views Database» more  VLDB 2007»
15 years 8 months ago
Depth Estimation for Ranking Query Optimization
A relational ranking query uses a scoring function to limit the results of a conventional query to a small number of the most relevant answers. The increasing popularity of this q...
Karl Schnaitter, Joshua Spiegel, Neoklis Polyzotis
CIKM
2008
Springer
15 years 4 months ago
Are click-through data adequate for learning web search rankings?
Learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. A traditional way of generating training examp...
Zhicheng Dou, Ruihua Song, Xiaojie Yuan, Ji-Rong W...
146
Voted
WWW
2011
ACM
14 years 9 months ago
Learning to rank with multiple objective functions
We investigate the problem of learning to rank for document retrieval from the perspective of learning with multiple objective functions. We present solutions to two open problems...
Krysta Marie Svore, Maksims Volkovs, Christopher J...
135
Voted
SIGIR
2009
ACM
15 years 9 months ago
Combining LVCSR and vocabulary-independent ranked utterance retrieval for robust speech search
Well tuned Large-Vocabulary Continuous Speech Recognition (LVCSR) has been shown to generally be more effective than vocabulary-independent techniques for ranked retrieval of spo...
J. Scott Olsson, Douglas W. Oard