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» Learning with Annotation Noise
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CBMS
2006
IEEE
15 years 3 months ago
Class Noise and Supervised Learning in Medical Domains: The Effect of Feature Extraction
Inductive learning systems have been successfully applied in a number of medical domains. It is generally accepted that the highest accuracy results that an inductive learning sys...
Mykola Pechenizkiy, Alexey Tsymbal, Seppo Puuronen...
LREC
2008
89views Education» more  LREC 2008»
14 years 11 months ago
Ontology Learning and Semantic Annotation: a Necessary Symbiosis
Semantic annotation of text requires the dynamic merging of linguistically structured information and a "world model", usually represented as a domain-specific ontology....
Emiliano Giovannetti, Simone Marchi, Simonetta Mon...
ACL
2007
14 years 11 months ago
Annotating and Learning Compound Noun Semantics
There is little consensus on a standard experimental design for the compound interpretation task. This paper introduces wellmotivated general desiderata for semantic annotation sc...
Diarmuid Ó Séaghdha
NIPS
2004
14 years 11 months ago
Semi-supervised Learning via Gaussian Processes
We present a probabilistic approach to learning a Gaussian Process classifier in the presence of unlabeled data. Our approach involves a "null category noise model" (NCN...
Neil D. Lawrence, Michael I. Jordan
IJCAI
1997
14 years 11 months ago
Noise-Tolerant Windowing
Windowing has been proposed as a procedure for efficient memory use in the ID3 decision tree learning algorithm. However, it was shown that it may often lead to a decrease in perf...
Johannes Fürnkranz