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WWW
2008
ACM
14 years 10 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...
ECIR
2007
Springer
13 years 11 months ago
Enhancing Expert Search Through Query Modeling
An expert finding is a very common task among enterprise search activities, while its usual retrieval performance is far from the quality of the Web search. Query modeling helps t...
Pavel Serdyukov, Sergey Chernov, Wolfgang Nejdl
CIKM
2009
Springer
14 years 4 months ago
Post-rank reordering: resolving preference misalignments between search engines and end users
No search engine is perfect. A typical type of imperfection is the preference misalignment between search engines and end users, e.g., from time to time, web users skip higherrank...
Chao Liu, Mei Li, Yi-Min Wang
CIKM
2010
Springer
13 years 8 months ago
Exploiting site-level information to improve web search
Ranking Web search results has long evolved beyond simple bag-of-words retrieval models. Modern search engines routinely employ machine learning ranking that relies on exogenous r...
Andrei Z. Broder, Evgeniy Gabrilovich, Vanja Josif...
RSFDGRC
2007
Springer
124views Data Mining» more  RSFDGRC 2007»
14 years 3 months ago
Supporting Literature Exploration with Granular Knowledge Structures
Reading and literature exploration are important tasks of scientific research. However, conventional retrieval systems provide limited support for these tasks by concentrating on ...
Yiyu Yao, Yi Zeng, Ning Zhong