Knowledge Graphs as Context Models: Improving the Detection of Cross-Language Plagiarism with Paraphrasing

Cross-language plagiarism detection attempts to identify and extract automatically plagiarism among documents in different languages. Plagiarized fragments can be translated verbatim copies or may alter their structure to hide the copying, which is known as paraphrasing and is more difficult to dete...

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Detalhes bibliográficos
Autores: Franco-Salvador, Marc, Gupta, Parth, Rosso, Paolo
Formato: capítulo de livro
Fecha de publicación:2013
País:España
Recursos:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/49758
Acesso em linha:https://riunet.upv.es/handle/10251/49758
Access Level:acceso abierto
Palavra-chave:Cross-language plagiarism detection
Textual similarity
Paraphrasing
Knowledge graphs
BabelNet
LENGUAJES Y SISTEMAS INFORMATICOS
Descrição
Resumo:Cross-language plagiarism detection attempts to identify and extract automatically plagiarism among documents in different languages. Plagiarized fragments can be translated verbatim copies or may alter their structure to hide the copying, which is known as paraphrasing and is more difficult to detect. In order to improve the paraphrasing detection, we use a knowledge graph-based approach to obtain and compare context models of document fragments in different languages. Experimental results in German-English and Spanish-English cross-language plagiarism detection indicate that our knowledge graph-based approach offers a better performance compared to other state-of-the-art models.