Mover: A Machine Learning Tool to Assist in the Reading and Writing of Technical Papers

Laurence Anthony, George V. Lashkia

研究成果: Article

22 引用 (Scopus)

抜粋

When faced with the tasks of reading and writing a complex technical paper, many nonnative scientists and engineers who have a solid background in English grammar and vocabulary lack an adequate knowledge of commonly used structural patterns at the discourse level. In this paper, we propose a novel computer software tool that can assist these people in the understanding and construction of technical papers, by automatically identifying the structure of writing in different fields and disciplines. The system is tested using research article abstracts and is shown to be a fast, accurate, and useful aid in the reading and writing process.

元の言語English
ページ(範囲)185-193
ページ数9
ジャーナルIEEE Transactions on Professional Communication
46
発行部数3
DOI
出版物ステータスPublished - 2003 9 1

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ASJC Scopus subject areas

  • Industrial relations
  • Electrical and Electronic Engineering

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