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Discover Computing
Erschienen in: Discover Computing 4-5/2021

14.07.2021

Using word semantic concepts for plagiarism detection in text documents

verfasst von: Chia-Yang Chang, Shie-Jue Lee, Chih-Hung Wu, Chih-Feng Liu, Ching-Kuan Liu

Erschienen in: Discover Computing | Ausgabe 4-5/2021

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Abstract

Plagiarism is a common problem in the modern age. With the advance of Internet, it is more and more convenient to access other people’s writings or publications. When someone uses the content of a text in an undesirable way, plagiarism may occur. Plagiarism infringes the intellectual property rights, so it is a serious problem nowadays. However, detecting plagiarism effectively is a challenging work. Traditional methods, like vector space model or bag-of-words, are short of providing a good solution due to the incapability of handling the semantics of words satisfactorily. In this paper, we propose a new method for plagiarism detection. We use Word2vec to transform the words into word vectors which are able to reveal the semantic relationship among different words. Through word vectors, words are clustered into concepts. Then documents and their paragraphs are represented in terms of concepts, and plagiarism detection can be done more effectively. A number of experiments are conducted to demonstrate the good performance of our proposed method.
Vorheriger Artikel Pseudo relevance feedback optimization
Nächster Artikel Strong natural language query generation

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Metadaten
Titel
Using word semantic concepts for plagiarism detection in text documents
verfasst von
Chia-Yang Chang
Shie-Jue Lee
Chih-Hung Wu
Chih-Feng Liu
Ching-Kuan Liu
Publikationsdatum
14.07.2021
Verlag
Springer Netherlands
Erschienen in
Discover Computing / Ausgabe 4-5/2021
Print ISSN: 2948-2984
Elektronische ISSN: 2948-2992
DOI
https://doi.org/10.1007/s10791-021-09394-4

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