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Plagiarism detection scheme based on Semantic Role Labeling

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6 Author(s)
Ahmed Hamza Osman ; Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia ; Naomie Salim ; Mohammed Salem Binwahlan ; Ssennoga Twaha
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Nowadays, 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.

Published in:

Information Retrieval & Knowledge Management (CAMP), 2012 International Conference on

Date of Conference:

13-15 March 2012