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WWW
2008
ACM
14 years 5 months ago
Ranking refinement and its application to information retrieval
We consider the problem of ranking refinement, i.e., to improve the accuracy of an existing ranking function with a small set of labeled instances. We are, particularly, intereste...
Rong Jin, Hamed Valizadegan, Hang Li
MIR
2005
ACM
140views Multimedia» more  MIR 2005»
13 years 10 months ago
Multiple random walk and its application in content-based image retrieval
In this paper, we propose a transductive learning method for content-based image retrieval: Multiple Random Walk (MRW). Its basic idea is to construct two generative models by mea...
Jingrui He, Hanghang Tong, Mingjing Li, Wei-Ying M...
WWW
2008
ACM
14 years 5 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
2011
ACM
12 years 10 months ago
Identifying primary content from web pages and its application to web search ranking
Web pages are usually highly structured documents. In some documents, content with different functionality is laid out in blocks, some merely supporting the main discourse. In ot...
Srinivas Vadrevu, Emre Velipasaoglu
CIVR
2006
Springer
201views Image Analysis» more  CIVR 2006»
13 years 8 months ago
Efficient Margin-Based Rank Learning Algorithms for Information Retrieval
Learning a good ranking function plays a key role for many applications including the task of (multimedia) information retrieval. While there are a few rank learning methods availa...
Rong Yan, Alexander G. Hauptmann