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

Abstract

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.