Similarity Measurement Based on Author's Writing Styles for Academic Report Plagiarism Detection

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2020/02/01

タイトル(英語): Similarity Measurement Based on Author's Writing Styles for Academic Report Plagiarism Detection

著者名: Asako Ohno (Osaka Sangyo University), Takahiro Yamasaki (Osaka Sangyo University), Kin-ichiroh Tokiwa (Osaka Sangyo University)

著者名(英語): Asako Ohno (Osaka Sangyo University), Takahiro Yamasaki (Osaka Sangyo University), Kin-ichiroh Tokiwa (Osaka Sangyo University)

キーワード: plagiarism detection，writing style，author identification，academic report，hidden markov model，academic integrity

要約(英語): The number of cases of plagiarism is increasing as it becomes easier for students to obtain well-written reports from the Internet or to copy and paste the contents of their classmates' reports into their own. Consequently, student plagiarism is becoming a primary issue interfering with fair grading by teachers. Academic reports tend to contain common expressions or academic terms. To write a good report, students try to use popular expressions for academic reports. Thus, it is important for teachers to detect plagiarism through careful attention to coincidental similarities. There is another important issue to be addressed: Plagiarism detection causes psychological burdens for both teachers and students. In this study, we introduce a plagiarism detection method for academic reports written in Japanese involving different types of characters. We train a number of Hidden Markov Models called writing models and identify authors by their writing style.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.140 No.2 （2020）　特集：エネルギーデータを対象としたIoT，AI活用技術

本誌掲載ページ: 235-241 p

原稿種別: 論文／英語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/140/2/140_235/_article/-char/ja/