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KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 8 months ago
Learning to rank networked entities
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal
MIR
2005
ACM
140views Multimedia» more  MIR 2005»
14 years 1 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 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...
JCDL
2011
ACM
272views Education» more  JCDL 2011»
12 years 10 months ago
CollabSeer: a search engine for collaboration discovery
Collaborative research has been increasingly popular and important in academic circles. However, there is no open platform available for scholars or scientists to effectively dis...
Hung-Hsuan Chen, Liang Gou, Xiaolong Zhang, Clyde ...
ICCV
2007
IEEE
14 years 9 months ago
Interactive Search for Image Categories by Mental Matching
Traditional image retrieval methods require a "query image" to initiate a search for members of an image category. However, when the image database is unstructured, and ...
Marin Ferecatu, Donald Geman