Constructing an academic Thai plagiarism corpus for benchmarking plagiarism detection systems

Plagiarism is a major problem in the academic world. It does not only undermine the credibility of educational institutions, but also interrupts the processes of creating knowledge in the academic community. To lessen this problem, many plagiarism detection systems have been developed to detect p...

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Main Authors: Supawat Taerungruang,, Wirote Aroonmanakun,
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2018
Online Access:http://journalarticle.ukm.my/17615/1/23578-82995-1-PB.pdf
http://journalarticle.ukm.my/17615/
https://ejournal.ukm.my/gema/issue/view/1098
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spelling my-ukm.journal.176152021-11-22T06:21:11Z http://journalarticle.ukm.my/17615/ Constructing an academic Thai plagiarism corpus for benchmarking plagiarism detection systems Supawat Taerungruang, Wirote Aroonmanakun, Plagiarism is a major problem in the academic world. It does not only undermine the credibility of educational institutions, but also interrupts the processes of creating knowledge in the academic community. To lessen this problem, many plagiarism detection systems have been developed to detect plagiarized texts in academic works. In this paper, we describe the design and process in creating an academic Thai plagiarism corpus. This corpus is necessary for training and testing plagiarism detection systems for Thai. In order to make this corpus a comprehensive representation of plagiarism, the data has been divided into various types based on the degree of the linguistic mechanisms used in plagiarism. Data compiled in our corpus comes through two main methods: manually created by participants and automatically generated by a program. After the corpus is created, its validity is verified by using three measurements: a measurement of similarity between suspicious texts at the character level, a measurement of similarity between suspicious texts at the word level, and a comparison of different types of data compiled in the corpus based on the similarity measured. The results of the analyses indicate that the corpus created by the proposed methods is effective in training and testing plagiarism detection systems. Penerbit Universiti Kebangsaan Malaysia 2018-08 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/17615/1/23578-82995-1-PB.pdf Supawat Taerungruang, and Wirote Aroonmanakun, (2018) Constructing an academic Thai plagiarism corpus for benchmarking plagiarism detection systems. GEMA ; Online Journal of Language Studies, 18 (3). pp. 186-202. ISSN 1675-8021 https://ejournal.ukm.my/gema/issue/view/1098
institution Universiti Kebangsaan Malaysia
building Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
language English
description Plagiarism is a major problem in the academic world. It does not only undermine the credibility of educational institutions, but also interrupts the processes of creating knowledge in the academic community. To lessen this problem, many plagiarism detection systems have been developed to detect plagiarized texts in academic works. In this paper, we describe the design and process in creating an academic Thai plagiarism corpus. This corpus is necessary for training and testing plagiarism detection systems for Thai. In order to make this corpus a comprehensive representation of plagiarism, the data has been divided into various types based on the degree of the linguistic mechanisms used in plagiarism. Data compiled in our corpus comes through two main methods: manually created by participants and automatically generated by a program. After the corpus is created, its validity is verified by using three measurements: a measurement of similarity between suspicious texts at the character level, a measurement of similarity between suspicious texts at the word level, and a comparison of different types of data compiled in the corpus based on the similarity measured. The results of the analyses indicate that the corpus created by the proposed methods is effective in training and testing plagiarism detection systems.
format Article
author Supawat Taerungruang,
Wirote Aroonmanakun,
spellingShingle Supawat Taerungruang,
Wirote Aroonmanakun,
Constructing an academic Thai plagiarism corpus for benchmarking plagiarism detection systems
author_facet Supawat Taerungruang,
Wirote Aroonmanakun,
author_sort Supawat Taerungruang,
title Constructing an academic Thai plagiarism corpus for benchmarking plagiarism detection systems
title_short Constructing an academic Thai plagiarism corpus for benchmarking plagiarism detection systems
title_full Constructing an academic Thai plagiarism corpus for benchmarking plagiarism detection systems
title_fullStr Constructing an academic Thai plagiarism corpus for benchmarking plagiarism detection systems
title_full_unstemmed Constructing an academic Thai plagiarism corpus for benchmarking plagiarism detection systems
title_sort constructing an academic thai plagiarism corpus for benchmarking plagiarism detection systems
publisher Penerbit Universiti Kebangsaan Malaysia
publishDate 2018
url http://journalarticle.ukm.my/17615/1/23578-82995-1-PB.pdf
http://journalarticle.ukm.my/17615/
https://ejournal.ukm.my/gema/issue/view/1098
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score 13.160551