DocumentCode
775411
Title
Mover: a machine learning tool to assist in the reading and writing of technical papers
Author
Anthony, Laurence ; Lashkia, George V.
Author_Institution
Dept. of Inf. & Comput. Eng., Okayama Univ. of Sci., Japan
Volume
46
Issue
3
fYear
2003
Firstpage
185
Lastpage
193
Abstract
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.
Keywords
intelligent tutoring systems; learning (artificial intelligence); technical presentation; word processing; English grammar; Mover; discourse analysis; information technology; machine learning tool; research article abstracts; technical paper reading; technical paper writing; vocabulary; Abstracts; Information technology; Knowledge engineering; Machine learning; Software tools; Solids; Supervised learning; System testing; Vocabulary; Writing;
fLanguage
English
Journal_Title
Professional Communication, IEEE Transactions on
Publisher
ieee
ISSN
0361-1434
Type
jour
DOI
10.1109/TPC.2003.816789
Filename
1227591
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