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Utility-theoretic ranking for semi-automated text classification

Academic Article
Publication Date:
2013
abstract:
Researchers from ISTI-CNR, Pisa, have addressed the problem of optimizing the work of human editors who proofcheck the results of an automatic text classifier with the goal of improving the accuracy of the automatically classified document set.
Iris type:
01.01 Articolo in rivista
Keywords:
Utility theory; Semi-automated text classification; I.2.6 Learning
List of contributors:
Esuli, Andrea; Sebastiani, Fabrizio
Authors of the University:
ESULI ANDREA
SEBASTIANI FABRIZIO
Handle:
https://iris.cnr.it/handle/20.500.14243/255109
Published in:
ERCIM NEWS
Journal
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URL

http://ercim-news.ercim.eu/images/stories/EN92/EN92-web.pdf
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