Plagiarism Detection using ROUGE and WordNet

Journal of Computing, Volume 2, Issue 3, March 2010 With the arrival of digital era and Internet, the lack of information control provides an incentive for people to freely use any content available to them. Plagiarism occurs when users fail to credit the original owner for the content referred to,...

Full description

Saved in:
Bibliographic Details
Main Authors Chen, Chien-Ying, Yeh, Jen-Yuan, Ke, Hao-Ren
Format Journal Article
LanguageEnglish
Published 22.03.2010
Subjects
Computer Science - Computation and Language
Computer Science - Other Computer Science
Online AccessGet full text

Cover

More Information
Summary:Journal of Computing, Volume 2, Issue 3, March 2010 With the arrival of digital era and Internet, the lack of information control provides an incentive for people to freely use any content available to them. Plagiarism occurs when users fail to credit the original owner for the content referred to, and such behavior leads to violation of intellectual property. Two main approaches to plagiarism detection are fingerprinting and term occurrence; however, one common weakness shared by both approaches, especially fingerprinting, is the incapability to detect modified text plagiarism. This study proposes adoption of ROUGE and WordNet to plagiarism detection. The former includes ngram co-occurrence statistics, skip-bigram, and longest common subsequence (LCS), while the latter acts as a thesaurus and provides semantic information. N-gram co-occurrence statistics can detect verbatim copy and certain sentence modification, skip-bigram and LCS are immune from text modification such as simple addition or deletion of words, and WordNet may handle the problem of word substitution.
DOI:10.48550/arxiv.1003.4065