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CVPR
2008
IEEE
13 years 9 months ago
Improving local learning for object categorization by exploring the effects of ranking
Local learning for classification is useful in dealing with various vision problems. One key factor for such approaches to be effective is to find good neighbors for the learning ...
Tien-Lung Chang, Tyng-Luh Liu, Jen-Hui Chuang
AIRS
2010
Springer
13 years 5 months ago
Relevance Ranking Using Kernels
This paper is concerned with relevance ranking in search, particularly that using term dependency information. It proposes a novel and unified approach to relevance ranking using ...
Jun Xu, Hang Li, Chaoliang Zhong
ECIR
2010
Springer
13 years 9 months ago
Learning to Select a Ranking Function
Abstract. Learning To Rank (LTR) techniques aim to learn an effective document ranking function by combining several document features. While the function learned may be uniformly ...
Jie Peng, Craig Macdonald, Iadh Ounis
WWW
2007
ACM
14 years 8 months ago
On ranking techniques for desktop search
This paper addresses the desktop search problem by considering various techniques for ranking results of a search query over the file system. First, basic ranking techniques, whic...
Sara Cohen, Carmel Domshlak, Naama Zwerdling
ICMCS
2008
IEEE
145views Multimedia» more  ICMCS 2008»
14 years 2 months ago
Video search reranking via online ordinal reranking
To exploit co-occurrence patterns among features and target semantics while keeping the simplicity of the keywordbased visual search, a novel reranking methods is proposed. The ap...
Yi-Hsuan Yang, Winston H. Hsu