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Determining and characterizing the reused text for plagiarism detection
José Fernando Sánchez Vega
ESAU VILLATORO TELLO
Manuel Montes y Gómez
Luis Villaseñor Pineda
Paolo Rosso
Acceso Abierto
Atribución-NoComercial-SinDerivadas
Plagiarism detection
Text reuse
Machine learning
Supervised classification
An important task in plagiarism detection is determining and measuring similar text portions between a given pair of documents. One of the main difficulties of this task resides on the fact that reused text is commonly modified with the aim of covering or camouflaging the plagiarism. Another difficulty is that not all similar text fragments are examples of plagiarism, since thematic coincidences also tend to pro- duce portions of similar text. In order to tackle these problems, we propose a novel method for detecting likely portions of reused text. This method is able to detect common actions performed by plagiarists such as word deletion, insertion and transposition, allowing to obtain plausible portions of reused text. We also propose representing the identified reused text by means of a set of features that denote its degree of plagiarism, relevance and fragmentation. This new representation aims to facilitate the recog- nition of plagiarism by considering diverse characteristics of the reused text during the classification phase. Experimental results employing a supervised classification strategy showed that the proposed method is able to outperform traditionally used approaches.
Elsevier Ltd.
2013
Artículo
Inglés
Estudiantes
Investigadores
Público en general
Sánchez. F., et al., (2013). Determining and characterizing the reused text for plagiarism detection, Expert Systems with Applications, Vol. 2013 (40): 1804–1813
CIENCIA DE LOS ORDENADORES
Versión aceptada
acceptedVersion - Versión aceptada
Aparece en las colecciones: Artículos de Ciencias Computacionales

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