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» Relevance Ranking Metrics for Learning Objects
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152
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DICTA
2003
15 years 3 months ago
Learning Semantic Concepts from Visual Data Using Neural Networks
For content-based image retrieval techniques, query image is used to pick up and rank some relevant images from a database using some certain similarity metric. If semantic feature...
Xiaohang Ma, Dianhui Wang
ML
2010
ACM
185views Machine Learning» more  ML 2010»
14 years 8 months ago
Learning to rank on graphs
Graph representations of data are increasingly common. Such representations arise in a variety of applications, including computational biology, social network analysis, web applic...
Shivani Agarwal
MM
2004
ACM
152views Multimedia» more  MM 2004»
15 years 7 months ago
Manifold-ranking based image retrieval
In this paper, we propose a novel transductive learning framework named manifold-ranking based image retrieval (MRBIR). Given a query image, MRBIR first makes use of a manifold ra...
Jingrui He, Mingjing Li, HongJiang Zhang, Hanghang...
140
Voted
ICDM
2009
IEEE
154views Data Mining» more  ICDM 2009»
14 years 11 months ago
GSML: A Unified Framework for Sparse Metric Learning
There has been significant recent interest in sparse metric learning (SML) in which we simultaneously learn both a good distance metric and a low-dimensional representation. Unfor...
Kaizhu Huang, Yiming Ying, Colin Campbell
WSDM
2010
ACM
210views Data Mining» more  WSDM 2010»
15 years 11 months ago
Towards Recency Ranking in Web Search
In web search, recency ranking refers to ranking documents by relevance which takes freshness into account. In this paper, we propose a retrieval system which automatically detect...
Anlei Dong, Yi Chang, Zhaohui Zheng, Gilad Mishne,...