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Features based text similarity detection

As the Internet help us cross cultural border by providing different information, plagiarism issue is bound to arise. As a result, plagiarism detection becomes more demanding in overcoming this issue. Different plagiarism detection tools have been developed based on various detection techniques. Now...

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Main Authors: Kok Kent, Chow, Salim, Naomie
Format: Article
Published: Academy Publisher 2010
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.utm.my/id/eprint/25940/
http://arxiv.org/pdf/1001.3487v1
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spelling my.utm.259402018-03-22T10:53:49Z http://eprints.utm.my/id/eprint/25940/ Features based text similarity detection Kok Kent, Chow Salim, Naomie QA75 Electronic computers. Computer science As the Internet help us cross cultural border by providing different information, plagiarism issue is bound to arise. As a result, plagiarism detection becomes more demanding in overcoming this issue. Different plagiarism detection tools have been developed based on various detection techniques. Nowadays, fingerprint matching technique plays an important role in those detection tools. However, in handling some large content articles, there are some weaknesses in fingerprint matching technique especially in space and time consumption issue. In this paper, we propose a new approach to detect plagiarism which integrates the use of fingerprint matching technique with four key features to assist in the detection process. These proposed features are capable to choose the main point or key sentence in the articles to be compared. Those selected sentence will be undergo the fingerprint matching process in order to detect the similarity between the sentences. Hence, time and space usage for the comparison process is reduced without affecting the effectiveness of the plagiarism detection. Academy Publisher 2010 Article PeerReviewed Kok Kent, Chow and Salim, Naomie (2010) Features based text similarity detection. Journal of Computing, 2 (1). pp. 53-57. ISSN 2151-9617 http://arxiv.org/pdf/1001.3487v1
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Kok Kent, Chow
Salim, Naomie
Features based text similarity detection
description As the Internet help us cross cultural border by providing different information, plagiarism issue is bound to arise. As a result, plagiarism detection becomes more demanding in overcoming this issue. Different plagiarism detection tools have been developed based on various detection techniques. Nowadays, fingerprint matching technique plays an important role in those detection tools. However, in handling some large content articles, there are some weaknesses in fingerprint matching technique especially in space and time consumption issue. In this paper, we propose a new approach to detect plagiarism which integrates the use of fingerprint matching technique with four key features to assist in the detection process. These proposed features are capable to choose the main point or key sentence in the articles to be compared. Those selected sentence will be undergo the fingerprint matching process in order to detect the similarity between the sentences. Hence, time and space usage for the comparison process is reduced without affecting the effectiveness of the plagiarism detection.
format Article
author Kok Kent, Chow
Salim, Naomie
author_facet Kok Kent, Chow
Salim, Naomie
author_sort Kok Kent, Chow
title Features based text similarity detection
title_short Features based text similarity detection
title_full Features based text similarity detection
title_fullStr Features based text similarity detection
title_full_unstemmed Features based text similarity detection
title_sort features based text similarity detection
publisher Academy Publisher
publishDate 2010
url http://eprints.utm.my/id/eprint/25940/
http://arxiv.org/pdf/1001.3487v1
_version_ 1643647633161453568
score 13.211869

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