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Mover: a machine learning tool to assist in the reading and writing of technical papers

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Mover : a machine learning tool to assist in the reading and writing of technical papers. / Anthony, Laurence; Lashkia, George V.

In: IEEE Transactions on Professional Communication, Vol. 46, No. 3, 2003, p. 185-193.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Anthony, L & Lashkia, GV 2003, 'Mover: a machine learning tool to assist in the reading and writing of technical papers', IEEE Transactions on Professional Communication, vol. 46, no. 3, pp. 185-193. https://doi.org/10.1109/TPC.2003.816789

APA

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

Vancouver

Author

Anthony, Laurence ; Lashkia, George V. / Mover : a machine learning tool to assist in the reading and writing of technical papers. In: IEEE Transactions on Professional Communication. 2003 ; Vol. 46, No. 3. pp. 185-193.

Bibtex

@article{b452a954d48542aeb6ec3cc3eb90428f,
title = "Mover: a machine learning tool to assist in the reading and writing of technical papers",
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.",
author = "Laurence Anthony and Lashkia, {George V.}",
year = "2003",
doi = "10.1109/TPC.2003.816789",
language = "English",
volume = "46",
pages = "185--193",
journal = "IEEE Transactions on Professional Communication",
issn = "0361-1434",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "3",

}

RIS

TY - JOUR

T1 - Mover

T2 - a machine learning tool to assist in the reading and writing of technical papers

AU - Anthony, Laurence

AU - Lashkia, George V.

PY - 2003

Y1 - 2003

N2 - 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.

AB - 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.

U2 - 10.1109/TPC.2003.816789

DO - 10.1109/TPC.2003.816789

M3 - Journal article

VL - 46

SP - 185

EP - 193

JO - IEEE Transactions on Professional Communication

JF - IEEE Transactions on Professional Communication

SN - 0361-1434

IS - 3

ER -