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

Laurence Anthony; George V. Lashkia

doi:10.1109/TPC.2003.816789

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

Laurence Anthony, George V. Lashkia

創造理工学部

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
巻	46
発行部数	3
DOI	https://doi.org/10.1109/TPC.2003.816789
出版物ステータス	Published - 2003 9 1

フィンガープリント

ASJC Scopus subject areas

Industrial relations
Electrical and Electronic Engineering

これを引用

Anthony, L., & Lashkia, G. V. (2003). Mover: A Machine Learning Tool to Assist in the Reading and Writing of Technical Papers. IEEE Transactions on Professional Communication, 46(3), 185-193. https://doi.org/10.1109/TPC.2003.816789

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文献にアクセス

10.1109/TPC.2003.816789