A linguistic treatment for automatic external plagiarism detection
Plagiarism is the unauthorized use of the ideas, presentation of someone else's words or work as your own. This paper presents an External Plagiarism Detection System (EPDS), which employs a combination of the Semantic Role Labeling (SRL) technique, the semantic and syntactic information. Most...
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my.utm.767712018-05-31T09:28:00Z http://eprints.utm.my/id/eprint/76771/ A linguistic treatment for automatic external plagiarism detection Abdi, A. Shamsuddin, S. M. Idris, N. Alguliyev, R. M. Aliguliyev, R. M. QA75 Electronic computers. Computer science Plagiarism is the unauthorized use of the ideas, presentation of someone else's words or work as your own. This paper presents an External Plagiarism Detection System (EPDS), which employs a combination of the Semantic Role Labeling (SRL) technique, the semantic and syntactic information. Most of the available methods fail to capture the meaning in the comparison between a source document sentence and a suspicious document sentence when two sentences have same surface text. Therefore, it leads to incorrect or even unnecessary matching results. However, the proposed method is able to avoid selecting the source text sentence whose similarity with suspicious text sentence is high but its meaning is different. On the other hand, an author may change the sentence from: active to passive and vice versa; hence, the method also employed the SRL technique to tackle the aforementioned challenge. Furthermore, the method used the content word expansion approach to bridge the lexical gaps and identify the similar ideas that are expressed using different wording. The proposed method is able to detect different types of plagiarism such as the exact verbatim copying, paraphrasing, transformation of sentences, changing of word structure. As a result, the experimental results have displayed that the proposed method is able to improve the performance compared with the participating systems in PAN-PC-11 and other existing techniques. Elsevier B.V. 2017 Article PeerReviewed Abdi, A. and Shamsuddin, S. M. and Idris, N. and Alguliyev, R. M. and Aliguliyev, R. M. (2017) A linguistic treatment for automatic external plagiarism detection. Knowledge-Based Systems, 135 . pp. 135-146. ISSN 0950-7051 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028297936&doi=10.1016%2fj.knosys.2017.08.008&partnerID=40&md5=623d06724eaa73cd5ca7d0338c0613b3 DOI:10.1016/j.knosys.2017.08.008 |
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QA75 Electronic computers. Computer science Abdi, A. Shamsuddin, S. M. Idris, N. Alguliyev, R. M. Aliguliyev, R. M. A linguistic treatment for automatic external plagiarism detection |
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Plagiarism is the unauthorized use of the ideas, presentation of someone else's words or work as your own. This paper presents an External Plagiarism Detection System (EPDS), which employs a combination of the Semantic Role Labeling (SRL) technique, the semantic and syntactic information. Most of the available methods fail to capture the meaning in the comparison between a source document sentence and a suspicious document sentence when two sentences have same surface text. Therefore, it leads to incorrect or even unnecessary matching results. However, the proposed method is able to avoid selecting the source text sentence whose similarity with suspicious text sentence is high but its meaning is different. On the other hand, an author may change the sentence from: active to passive and vice versa; hence, the method also employed the SRL technique to tackle the aforementioned challenge. Furthermore, the method used the content word expansion approach to bridge the lexical gaps and identify the similar ideas that are expressed using different wording. The proposed method is able to detect different types of plagiarism such as the exact verbatim copying, paraphrasing, transformation of sentences, changing of word structure. As a result, the experimental results have displayed that the proposed method is able to improve the performance compared with the participating systems in PAN-PC-11 and other existing techniques. |
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Article |
author |
Abdi, A. Shamsuddin, S. M. Idris, N. Alguliyev, R. M. Aliguliyev, R. M. |
author_facet |
Abdi, A. Shamsuddin, S. M. Idris, N. Alguliyev, R. M. Aliguliyev, R. M. |
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Abdi, A. |
title |
A linguistic treatment for automatic external plagiarism detection |
title_short |
A linguistic treatment for automatic external plagiarism detection |
title_full |
A linguistic treatment for automatic external plagiarism detection |
title_fullStr |
A linguistic treatment for automatic external plagiarism detection |
title_full_unstemmed |
A linguistic treatment for automatic external plagiarism detection |
title_sort |
linguistic treatment for automatic external plagiarism detection |
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Elsevier B.V. |
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2017 |
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http://eprints.utm.my/id/eprint/76771/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028297936&doi=10.1016%2fj.knosys.2017.08.008&partnerID=40&md5=623d06724eaa73cd5ca7d0338c0613b3 |
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