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With the arrival of digital era and Internet, the lack of information controlprovides an incentive for people to freely use any content available to them.Plagiarism occurs when users fail to credit the original owner for the contentreferred to, and such behavior leads to violation of intellectual property. Twomain approaches to plagiarism detection are fingerprinting and term occurrence;however, one common weakness shared by both approaches, especiallyfingerprinting, is the incapability to detect modified text plagiarism. Thisstudy proposes adoption of ROUGE and WordNet to plagiarism detection. Theformer includes ngram co-occurrence statistics, skip-bigram, and longest commonsubsequence (LCS), while the latter acts as a thesaurus and provides semanticinformation. N-gram co-occurrence statistics can detect verbatim copy andcertain sentence modification, skip-bigram and LCS are immune from textmodification such as simple addition or deletion of words, and WordNet mayhandle the problem of word substitution.

Plagiarism Detection using ROUGE and WordNet