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» Text classification improved through multigram models
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ICML
2005
IEEE
14 years 7 months ago
A model for handling approximate, noisy or incomplete labeling in text classification
We introduce a Bayesian model, BayesANIL, that is capable of estimating uncertainties associated with the labeling process. Given a labeled or partially labeled training corpus of...
Ganesh Ramakrishnan, Krishna Prasad Chitrapura, Ra...
JUCS
2007
86views more  JUCS 2007»
13 years 6 months ago
Improving LO Quality through Instructional Design Based on an Ontological Model and Metadata
: The activities developed in this paper were aimed at providing an awareness of the elements that should be considered in quality learning objects instructional design for elearni...
Erla Morales Morgado, Francisco José Garc&i...
CISSE
2008
Springer
13 years 9 months ago
Sentiment Mining Using Ensemble Classification Models
We live in the information age, where the amount of data readily available already overwhelms our capacity to analyze and absorb it without help from our machines. In particular, ...
Matthew Whitehead, Larry Yaeger
AIRS
2006
Springer
13 years 10 months ago
Learning to Separate Text Content and Style for Classification
Many text documents naturally have two kinds of labels. For example, we may label web pages from universities according to their categories, such as "student" or "fa...
Dell Zhang, Wee Sun Lee
TMI
2002
90views more  TMI 2002»
13 years 6 months ago
Edge Displacement Field-Based Classification for Improved Detection of Polyps in CT Colonography
Colorectal cancer can easily be prevented provided that the precursors to tumors, small colonic polyps, are detected and removed. Currently, the only definitive examination of the ...
Burak Acar, Christopher F. Beaulieu, Salih Burak G...