Item type |
SIG Technical Reports(1) |
公開日 |
2019-08-22 |
タイトル |
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タイトル |
Automated Essay Rewriting (AER): Grammatical Error Correction, Fluency Edits, and Beyond |
タイトル |
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言語 |
en |
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タイトル |
Automated Essay Rewriting (AER): Grammatical Error Correction, Fluency Edits, and Beyond |
言語 |
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言語 |
eng |
資源タイプ |
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資源タイプ識別子 |
http://purl.org/coar/resource_type/c_18gh |
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資源タイプ |
technical report |
著者所属 |
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RIKEN Center for Advanced Intelligence Project/Tohoku University |
著者所属 |
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Octanove Labs |
著者所属 |
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Allen Institute for Artificial Intelligence |
著者所属 |
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Future Corporation |
著者所属 |
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Tohoku University/RIKEN Center for Advanced Intelligence Project |
著者所属 |
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Tohoku University/RIKEN Center for Advanced Intelligence Project |
著者所属(英) |
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en |
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RIKEN Center for Advanced Intelligence Project / Tohoku University |
著者所属(英) |
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en |
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Octanove Labs |
著者所属(英) |
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en |
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Allen Institute for Artificial Intelligence |
著者所属(英) |
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en |
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Future Corporation |
著者所属(英) |
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en |
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Tohoku University / RIKEN Center for Advanced Intelligence Project |
著者所属(英) |
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en |
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Tohoku University / RIKEN Center for Advanced Intelligence Project |
著者名 |
Masato, Mita
Masato, Hagiwara
Keisuke, Sakaguchi
Tomoya, Mizumoto
Jun, Suzuki
Kentaro, Inui
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著者名(英) |
Masato, Mita
Masato, Hagiwara
Keisuke, Sakaguchi
Tomoya, Mizumoto
Jun, Suzuki
Kentaro, Inui
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論文抄録 |
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内容記述タイプ |
Other |
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内容記述 |
We propose the Automated Essay Rewriting (AER) task, where computer systems make automatic edits to argumentative essays to improve their quality. AER subsumes types of edits beyond single sentences such as coherence, cohesion, and style, which are not within the scope of traditional tasks such as grammatical error correction (GEC) and fluency edits. The quantitative and qualitative analyses of a corpus specifically designed for AER reveal that these edits account for almost half of edits made by professional proofreaders. We also discuss the challenges, issues, and future direction of AER by comparing with other tasks. |
論文抄録(英) |
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内容記述タイプ |
Other |
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内容記述 |
We propose the Automated Essay Rewriting (AER) task, where computer systems make automatic edits to argumentative essays to improve their quality. AER subsumes types of edits beyond single sentences such as coherence, cohesion, and style, which are not within the scope of traditional tasks such as grammatical error correction (GEC) and fluency edits. The quantitative and qualitative analyses of a corpus specifically designed for AER reveal that these edits account for almost half of edits made by professional proofreaders. We also discuss the challenges, issues, and future direction of AER by comparing with other tasks. |
書誌レコードID |
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収録物識別子タイプ |
NCID |
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収録物識別子 |
AN10115061 |
書誌情報 |
研究報告自然言語処理(NL)
巻 2019-NL-241,
号 24,
p. 1-5,
発行日 2019-08-22
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ISSN |
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収録物識別子タイプ |
ISSN |
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収録物識別子 |
2188-8779 |
Notice |
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SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc. |
出版者 |
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言語 |
ja |
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出版者 |
情報処理学会 |