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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...
CIKM
2005
Springer
14 years 1 months ago
Maximal termsets as a query structuring mechanism
Search engines process queries conjunctively to restrict the size of the answer set. Further, it is not rare to observe a mismatch between the vocabulary used in the text of Web p...
Bruno Pôssas, Nivio Ziviani, Berthier A. Rib...
CIKM
2008
Springer
13 years 9 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...
SIGIR
1999
ACM
14 years 18 hour ago
Deriving Concept Hierarchies from Text
This paper presents a means of automatically deriving a hierarchical organization of concepts from a set of documents without use of training data or standard clustering technique...
Mark Sanderson, W. Bruce Croft
WWW
2009
ACM
14 years 8 months ago
User-centric content freshness metrics for search engines
In order to return relevant search results, a search engine must keep its local repository synchronized to the Web, but it is usually impossible to attain perfect freshness. Hence...
Ali Dasdan, Xinh Huynh