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Understanding plagiarism linguistic patterns, textual features and detection methods (2011)

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by Salha M. Alzahrani , Naomie Salim , Ajith Abraham , Senior Member
Venue:IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Citations:19 - 3 self
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BibTeX

@ARTICLE{Alzahrani11understandingplagiarism,
    author = {Salha M. Alzahrani and Naomie Salim and Ajith Abraham and Senior Member},
    title = {Understanding plagiarism linguistic patterns, textual features and detection methods},
    journal = {IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews},
    year = {2011}
}

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Abstract

Abstract—Plagiarism can be of many different natures, ranging from copying texts to adopting ideas, without giving credit to its originator. This paper presents a new taxonomy of plagiarism that highlights differences between literal plagiarism and intelligent plagiarism, from the plagiarist’s behavioral point of view. The taxonomy supports deep understanding of different linguistic patterns in committing plagiarism, for example, changing texts into semantically equivalent but with different words and organization, shortening texts with concept generalization and specification, and adopting ideas and important contributions of others. Different textual features that characterize different plagiarism types are discussed. Systematic frameworks and methods of monolingual, extrinsic, intrinsic, and cross-lingual plagiarism detection are surveyed and correlated with plagiarism types, which are listed in the taxonomy. We conduct extensive study of state-of-the-art techniques for plagiarism detection, including character n-gram-based (CNG), vector-based (VEC), syntax-based

Keyphrases

detection method    textual feature    plagiarism linguistic pattern    literal plagiarism    state-of-the-art technique    different textual feature    abstract plagiarism    new taxonomy    systematic framework    plagiarism detection    plagiarist behavioral point    highlight difference    plagiarism type    extensive study    deep understanding    different linguistic pattern    different word    different plagiarism type    important contribution    cross-lingual plagiarism detection    intelligent plagiarism    many different nature    concept generalization   

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