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» Learning to rank for information retrieval
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SIGIR
2009
ACM
14 years 2 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
WSDM
2010
ACM
245views Data Mining» more  WSDM 2010»
14 years 5 months ago
Improving Quality of Training Data for Learning to Rank Using Click-Through Data
In information retrieval, relevance of documents with respect to queries is usually judged by humans, and used in evaluation and/or learning of ranking functions. Previous work ha...
Jingfang Xu, Chuanliang Chen, Gu Xu, Hang Li, Elbi...
ERCIMDL
2009
Springer
117views Education» more  ERCIMDL 2009»
14 years 2 months ago
A Visualization Tool of Probabilistic Models for Information Access Components
An effective graphic interface is a key tool to improve the fruition of the results retrieved by an Information Retrieval (IR) system. In this work, we describe a two-dimensional...
Lorenzo De Stefani, Giorgio Maria Di Nunzio, Giorg...
KDD
2007
ACM
192views Data Mining» more  KDD 2007»
14 years 8 months ago
Active exploration for learning rankings from clickthrough data
We address the task of learning rankings of documents from search engine logs of user behavior. Previous work on this problem has relied on passively collected clickthrough data. ...
Filip Radlinski, Thorsten Joachims
WWW
2007
ACM
14 years 8 months ago
Supervised rank aggregation
This paper is concerned with rank aggregation, the task of combining the ranking results of individual rankers at meta-search. Previously, rank aggregation was performed mainly by...
Yu-Ting Liu, Tie-Yan Liu, Tao Qin, Zhiming Ma, Han...