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WWW
2008
ACM
16 years 7 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...
WWW
2010
ACM
16 years 1 months ago
New-web search with microblog annotations
Web search engines discover indexable documents by recursively ‘crawling’ from a seed URL. Their rankings take into account link popularity. While this works well, it introduc...
Tom Rowlands, David Hawking, Ramesh Sankaranarayan...
STOC
2009
ACM
172views Algorithms» more  STOC 2009»
16 years 7 months ago
Linear time approximation schemes for the Gale-Berlekamp game and related minimization problems
We design a linear time approximation scheme for the GaleBerlekamp Switching Game and generalize it to a wider class of dense fragile minimization problems including the Nearest C...
Marek Karpinski, Warren Schudy
ADC
2006
Springer
120views Database» more  ADC 2006»
16 years 16 days ago
Approximate data mining in very large relational data
In this paper we discuss eNERF, an extended version of non-Euclidean relational fuzzy c-means (NERFCM) for approximate clustering in very large (unloadable) relational data. The e...
James C. Bezdek, Richard J. Hathaway, Christopher ...
GECCO
2005
Springer
156views Optimization» more  GECCO 2005»
16 years 2 days ago
Extraction of informative genes from microarray data
Identification of those genes that might anticipate the clinical behavior of different types of cancers is challenging due to availability of a smaller number of patient samples...
Topon Kumar Paul, Hitoshi Iba