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» Learning to rank for information retrieval
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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...
WWW
2008
ACM
14 years 8 months ago
Learning to rank relational objects and its application to web search
Learning to rank is a new statistical learning technology on creating a ranking model for sorting objects. The technology has been successfully applied to web search, and is becom...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
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
SIGIR
2004
ACM
14 years 1 months ago
Learning effective ranking functions for newsgroup search
Web communities are web virtual broadcasting spaces where people can freely discuss anything. While such communities function as discussion boards, they have even greater value as...
Wensi Xi, Jesper Lind, Eric Brill
ECIR
2009
Springer
14 years 4 months ago
Regression Rank: Learning to Meet the Opportunity of Descriptive Queries
Abstract. We present a new learning to rank framework for estimating context-sensitive term weights without use of feedback. Specifically, knowledge of effective term weights on ...
Matthew Lease, James Allan, W. Bruce Croft