Plagiarism Detection Scheme Based on Semantic Role Labeling

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dc.contributor.authorHamza Osman, Ahmed
dc.contributor.authorSalim, Naomie
dc.contributor.authorSalem Binwahlan, Mohammed
dc.contributor.authorJaya Kumar, Yogan
dc.contributor.authorAbuobieda, Albaraa
dc.contributor.authorSsennoga, Twaha
dc.date.accessioned2022-05-26T15:51:06Z
dc.date.available2022-05-26T15:51:06Z
dc.date.issued2012
dc.description.abstractNowadays, many documents are available on the internet and are easy to access. Due to this wide availability, users can easily create a new document by copying and pasting. Plagiarism occurs when the content is copied without permission or citation. This paper introduces a plagiarism detection technique based on the Semantic Role Labeling (SRL). The technique analyses and compares text based on the semantic allocation for each term inside the sentence. SRL is superior in generating arguments for each sentence semantically. In addition, experimental results on PAN-PC-09 data sets showed that our method outperforms the modern methods for plagiarism detection in terms of Recall, Precision and F-measure.en_US
dc.identifier.citationOsman, A. H., Salim, N., Binwahlan, M. S., Twaha, S., Kumar, Y. J., & Abuobieda, A. (2012, March). Plagiarism detection scheme based on Semantic Role Labeling. In 2012 international conference on Information Retrieval & Knowledge Management (pp. 30-33). IEEE.en_US
dc.identifier.urihttps://ieeexplore.ieee.org/abstract/document/6204978/
dc.identifier.urihttps://nru.uncst.go.ug/handle/123456789/3494
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectPlagiarism Detectionen_US
dc.subjectSemantic Similarityen_US
dc.subjectSemantic Roleen_US
dc.subjectArgumentsen_US
dc.titlePlagiarism Detection Scheme Based on Semantic Role Labelingen_US
dc.typeArticleen_US
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