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135
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WWW
2008
ACM
16 years 4 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...
COLING
2010
14 years 10 months ago
Extracting and Ranking Product Features in Opinion Documents
An important task of opinion mining is to extract people's opinions on features of an entity. For example, the sentence, "I love the GPS function of Motorola Droid"...
Lei Zhang, Bing Liu, Suk Hwan Lim, Eamonn O'Brien-...
165
Voted
ICCV
2009
IEEE
15 years 1 months ago
Efficient multi-label ranking for multi-class learning: Application to object recognition
Multi-label learning is useful in visual object recognition when several objects are present in an image. Conventional approaches implement multi-label learning as a set of binary...
Serhat Selcuk Bucak, Pavan Kumar Mallapragada, Ron...
FOCS
2008
IEEE
15 years 3 months ago
Matrix Sparsification for Rank and Determinant Computations via Nested Dissection
The nested dissection method developed by Lipton, Rose, and Tarjan is a seminal method for quickly performing Gaussian elimination of symmetric real positive definite matrices who...
Raphael Yuster
CORR
2008
Springer
188views Education» more  CORR 2008»
15 years 1 months ago
Citation Counting, Citation Ranking, and h-Index of Human-Computer Interaction Researchers: A Comparison between Scopus and Web
: This study examines the differences between Scopus and Web of Science in the citation counting, citation ranking, and h-index of 22 top human-computer interaction (HCI) researche...
Lokman I. Meho, Yvonne Rogers