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» Abox Inference for Large Scale OWL-Lite Data
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SKG
2006
IEEE
14 years 4 months ago
Abox Inference for Large Scale OWL-Lite Data
Abox inference is an important part in OWL data management. When involving large scale of instance data, it can not be supported by existing inference engines. In this paper, we p...
Xiaofeng Wang, Jianbo Ou, Xiaofeng Meng, Yan Chen
ESWS
2007
Springer
14 years 5 months ago
Understanding Large Volumes of Interconnected Individuals by Visual Exploration
Abstract. Ontologies are now used within an increasing number of realworld applications. So far, significant effort has been spend in building tools to support users in creating,...
Olaf Noppens, Thorsten Liebig
ACL
2009
13 years 8 months ago
Efficient Inference of CRFs for Large-Scale Natural Language Data
This paper presents an efficient inference algorithm of conditional random fields (CRFs) for large-scale data. Our key idea is to decompose the output label state into an active s...
Minwoo Jeong, Chin-Yew Lin, Gary Geunbae Lee
CVPR
2012
IEEE
12 years 1 months ago
Large scale metric learning from equivalence constraints
In this paper, we raise important issues on scalability and the required degree of supervision of existing Mahalanobis metric learning methods. Often rather tedious optimization p...
Martin Köstinger, Martin Hirzer, Paul Wohlhar...
BMCBI
2007
114views more  BMCBI 2007»
13 years 11 months ago
Large scale statistical inference of signaling pathways from RNAi and microarray data
Background: The advent of RNA interference techniques enables the selective silencing of biologically interesting genes in an efficient way. In combination with DNA microarray tec...
Holger Fröhlich, Mark Fellmann, Holger Sü...