タイトル(別表記) A Study of Extracting Related Documents for Essay Evaluation Modules
フルテキストURL NLC2017-24.pdf
著者 泉仁 宏太| 竹内 孔一| 大野 雅幸| 田口 雅弘| 稲田 佳彦| 飯塚 誠也| 阿保 達彦| 上田 均|
抄録(別表記) We are developing an automatic Japanese essay-scoring system that is composed of 4 evaluation criteria, comprehensiveness, logical consistency, validity, spelling and grammar. In this paper, we discuss the most powerful approach to extract documents of Wikipedia that relates to the reference texts of the target essay theme for validity evaluation. The reason for using Wikipedia documents for evaluating validity of students’essays is that we assume that validity can be evaluated by the expanded discussions in Wikipedia documents that relates to the essay theme. Experimental results show that the skip-gram based word vector is the best approach to extract relating documents to reference texts among several keyword-based evaluation approaches.
キーワード 小論文の自動採点 (Automatic scoring of answers of essay-writing tests) 単語ベクトル (Word vector) Skip-gram Wikipedia
発行日 2017-09
出版物タイトル 電子情報通信学会技術研究報告. NLC, 言語理解とコミュニケーション
117巻
207号
出版者 電子情報通信学会
開始ページ 47
終了ページ 51
ISSN 09135685
NCID AA11524632
資料タイプ 学術雑誌論文
言語 Japanese
OAI-PMH Set 岡山大学
著作権者 copyright©2017 IEICE
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