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

Contributo in Atti di convegno
Data di Pubblicazione:
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.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
Textual Genre Classification; Feature Selection; Syntactic Features
Elenco autori:
Venturi, Giulia; Cimino, Andrea; Montemagni, Simonetta; Dell'Orletta, Felice
Autori di Ateneo:
DELL'ORLETTA FELICE
MONTEMAGNI SIMONETTA
VENTURI GIULIA
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/342154
Pubblicato 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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