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WSDM
2010
ACM
245views Data Mining» more  WSDM 2010»
14 years 6 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...
WWW
2009
ACM
14 years 9 months ago
Learning consensus opinion: mining data from a labeling game
We consider the problem of identifying the consensus ranking for the results of a query, given preferences among those results from a set of individual users. Once consensus ranki...
Paul N. Bennett, David Maxwell Chickering, Anton M...
HICSS
2006
IEEE
163views Biometrics» more  HICSS 2006»
14 years 2 months ago
Learning Ranking vs. Modeling Relevance
The classical (ad hoc) document retrieval problem has been traditionally approached through ranking according to heuristically developed functions (such as tf.idf or bm25) or gene...
Dmitri Roussinov, Weiguo Fan
IPM
2006
108views more  IPM 2006»
13 years 8 months ago
Using searcher simulations to redesign a polyrepresentative implicit feedback interface
Information seeking is traditionally conducted in environments where search results are represented at the user interface by a minimal amount of meta-information such as titles an...
Ryen W. White
BMCBI
2008
105views more  BMCBI 2008»
13 years 8 months ago
Objective and automated protocols for the evaluation of biomedical search engines using No Title Evaluation protocols
Background: The evaluation of information retrieval techniques has traditionally relied on human judges to determine which documents are relevant to a query and which are not. Thi...
Fabien Campagne