Plagiarism detection using graph-based representation
Plagiarism of material from the Internet is a widespread and growing problem. Several methods used to detect the plagiarism and similarity between the source document and suspected documents such as fingerprint based on character or n-gram. In this paper, we discussed a new method to detect the plag...
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Journal of Computing
2010
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my.utm.380302017-06-12T01:48:16Z http://eprints.utm.my/id/eprint/38030/ Plagiarism detection using graph-based representation Osman, Ahmed Hamza Salim, Naomie Binwahlan, Mohammed Salem QA75 Electronic computers. Computer science Plagiarism of material from the Internet is a widespread and growing problem. Several methods used to detect the plagiarism and similarity between the source document and suspected documents such as fingerprint based on character or n-gram. In this paper, we discussed a new method to detect the plagiarism based on graph representation; however, Preprocessing for each document is required such as breaking down the document into its constituent sentences. Segmentation of each sentence into separated terms and stop word removal. We build the graph by grouping each sentence terms in one node, the resulted nodes are connected to each other based on order of sentence within the document, all nodes in graph are also connected to top level node” Topic Signature “. Topic signature node is formed by extracting the concepts of each sentence terms and grouping them in such node. The main advantage of the proposed method is the topic signature which is main entry for the graph is used as quick guide to the relevant nodes. which should be considered for the comparison between source documents and suspected one. We believe the proposed method can achieve a good performance in terms of effectiveness and efficiency. Journal of Computing 2010-04 Article PeerReviewed Osman, Ahmed Hamza and Salim, Naomie and Binwahlan, Mohammed Salem (2010) Plagiarism detection using graph-based representation. Journal of Computing, 2 (4). pp. 36-41. ISSN 2151-9617 http://arxiv.org/ftp/arxiv/papers/1004/1004.4449.pdf |
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QA75 Electronic computers. Computer science Osman, Ahmed Hamza Salim, Naomie Binwahlan, Mohammed Salem Plagiarism detection using graph-based representation |
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Plagiarism of material from the Internet is a widespread and growing problem. Several methods used to detect the plagiarism and similarity between the source document and suspected documents such as fingerprint based on character or n-gram. In this paper, we discussed a new method to detect the plagiarism based on graph representation; however, Preprocessing for each document is required such as breaking down the document into its constituent sentences. Segmentation of each sentence into separated terms and stop word removal. We build the graph by grouping each sentence terms in one node, the resulted nodes are connected to each other based on order of sentence within the document, all nodes in graph are also connected to top level node” Topic Signature “. Topic signature node is formed by extracting the concepts of each sentence terms and grouping them in such node. The main advantage of the proposed method is the topic signature which is main entry for the graph is used as quick guide to the relevant nodes. which should be considered for the comparison between source documents and suspected one. We believe the proposed method can achieve a good performance in terms of effectiveness and efficiency. |
format |
Article |
author |
Osman, Ahmed Hamza Salim, Naomie Binwahlan, Mohammed Salem |
author_facet |
Osman, Ahmed Hamza Salim, Naomie Binwahlan, Mohammed Salem |
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Osman, Ahmed Hamza |
title |
Plagiarism detection using graph-based representation
|
title_short |
Plagiarism detection using graph-based representation
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title_full |
Plagiarism detection using graph-based representation
|
title_fullStr |
Plagiarism detection using graph-based representation
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Plagiarism detection using graph-based representation
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plagiarism detection using graph-based representation |
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Journal of Computing |
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2010 |
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http://eprints.utm.my/id/eprint/38030/ http://arxiv.org/ftp/arxiv/papers/1004/1004.4449.pdf |
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