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Identifying predictive features for textual genre classification: The key role of syntax

Conference Paper
Publication Date:
2017
abstract:
The paper investigates impact and role of different feature types for the specific task of Automatic Genre Classification with the final aim of identifying the most predictive ones. The goal was pursued by carrying out incremental feature selection through Grafting using different sets of linguistic features. Achieved results for discriminating among four traditional textual genres show the key role played by syntactic features, whose impact turned out to vary across genres.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
Textual Genre Classification; Feature Selection; Syntactic Features
List of contributors:
Venturi, Giulia; Cimino, Andrea; Montemagni, Simonetta; Dell'Orletta, Felice
Authors of the University:
DELL'ORLETTA FELICE
MONTEMAGNI SIMONETTA
VENTURI GIULIA
Handle:
https://iris.cnr.it/handle/20.500.14243/342154
Published in:
CEUR WORKSHOP PROCEEDINGS
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http://www.scopus.com/record/display.url?eid=2-s2.0-85037370866&origin=inward
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