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Article
Discourse classification into rhetorical functions for AWE feedback
CALICO Journal
  • Elena Cotos, Iowa State University
  • Nick Pendar, Skytree- The Machine Learning Company
Document Type
Article
Publication Version
Published Version
Publication Date
1-1-2016
Abstract
This paper reports on the development of the analysis engine for the Research Writing Tutor (RWT), an AWE program designed to provide genre and discipline-specific feedback on the functional units of research article discourse. Unlike traditional NLP-based applications that categorize complete documents, RWT’s analyzer categorizes every sentence in the text as both a communicative move and a rhetorical step. We describe the construction of a cascade of two support vector machine classifiers trained on a multi-disciplinary corpus of annotated Introduction texts. This work not only demonstrates the usefulness of NLP for automated genre analysis, but also paves the road for future AWE endeavors and forms of automated feedback that could facilitate construction of functional meaning in writing.
Comments

This is an article from CALICO Journal 33 (2016). Posted with permission.

Copyright Owner
CALICO Journal
Language
en
File Format
application/pdf
Citation Information
Elena Cotos and Nick Pendar. "Discourse classification into rhetorical functions for AWE feedback" CALICO Journal Vol. 33 (2016) p. 1 - 22
Available at: http://works.bepress.com/elena_cotos/8/