Sciweavers

16 search results - page 1 / 4
» Pseudo test collections for learning web search ranking func...
Sort
View
SIGIR
2011
ACM
12 years 7 months ago
Pseudo test collections for learning web search ranking functions
Test collections are the primary drivers of progress in information retrieval. They provide a yardstick for assessing the effectiveness of ranking functions in an automatic, rapi...
Nima Asadi, Donald Metzler, Tamer Elsayed, Jimmy L...
WWW
2008
ACM
14 years 5 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...
SIGIR
2004
ACM
13 years 10 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
CIKM
2008
Springer
13 years 7 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...
KDD
2005
ACM
177views Data Mining» more  KDD 2005»
14 years 5 months ago
Query chains: learning to rank from implicit feedback
This paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. We observe that users searching the web often perform ...
Filip Radlinski, Thorsten Joachims