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Segmenting documents by stylistic character

Published online by Cambridge University Press:  10 November 2005

NEIL GRAHAM ,
GRAEME HIRST  and
BHASKARA MARTHI
NEIL GRAHAM
Affiliation:
Department of Computer Science, University of Toronto, Toronto, Ontario, Canada M5S 3G4 e-mail: gh@cs.toronto.edu Present address: IBM Canada Ltd.
GRAEME HIRST
Affiliation:
Department of Computer Science, University of Toronto, Toronto, Ontario, Canada M5S 3G4 e-mail: gh@cs.toronto.edu
BHASKARA MARTHI
Affiliation:
Department of Computer Science, University of Toronto, Toronto, Ontario, Canada M5S 3G4 e-mail: gh@cs.toronto.edu Present address: Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA, USA.
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Abstract

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As part of a larger project to develop an aid for writers that would help to eliminate stylistic inconsistencies within a document, we experimented with neural networks to find the points in a text at which its stylistic character changes. Our best results, well above baseline, were achieved with time-delay networks that used features related to the author's syntactic preferences, whereas low-level and vocabulary-based features were not found to be useful. An alternative approach with character bigrams was not successful.

Information

Type
Papers
Information
Natural Language Engineering , Volume 11 , Issue 4 , December 2005 , pp. 397 - 415
Copyright
2005 Cambridge University Press

Footnotes

An earlier version of parts of this paper was presented at the Workshop on Computational Approaches to Style Analysis and Synthesis, Acapulco, August 2003.