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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Detalles Bibliográficos
Autores: Franco-Salvador, Marc, Gupta, Parth, Rosso, Paolo
Tipo de recurso: capítulo de libro
Fecha de publicación:2013
País:España
Institución: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
Acceso en línea:https://riunet.upv.es/handle/10251/49758
Access Level:acceso abierto
Palabra clave:Cross-language plagiarism detection
Textual similarity
Paraphrasing
Knowledge graphs
BabelNet
LENGUAJES Y SISTEMAS INFORMATICOS
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spelling Knowledge Graphs as Context Models: Improving the Detection of Cross-Language Plagiarism with ParaphrasingFranco-Salvador, MarcGupta, ParthRosso, PaoloCross-language plagiarism detectionTextual similarityParaphrasingKnowledge graphsBabelNetLENGUAJES Y SISTEMAS INFORMATICOSCross-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.The research has been carried out in the framework of the European Commission WIQ-EIIRSES (no. 269180) and DIANA-APPLICATIONS - Finding Hidden Knowledge in Texts:Applications (TIN2012-38603-C02-01) projects as well as the VLC/CAMPUS Microcluster on Multimodal Interaction in Intelligent Systems.Springer Verlag (Germany)Departamento de Sistemas Informáticos y ComputaciónEscuela Técnica Superior de Ingeniería InformáticaCentro de Investigación Pattern Recognition and Human Language TechnologyEuropean CommissionUniversitat de ValènciaMinisterio de Economía y CompetitividadRepositorio Institucional de la Universitat Politècnica de València Riunet20132013-01-01book parthttp://purl.org/coar/resource_type/c_3248VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/bookPartapplication/pdfhttps://riunet.upv.es/handle/10251/49758reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengEuropean Commission https://doi.org/10.13039/501100000780 FP7 269180 Web Information Quality Evaluation InitiativeMinisterio de Economía y Competitividad http://dx.doi.org/10.13039/501100003329 TIN2012-38603-C02-01 DIANA-APPLICATIONS: FINDING HIDDEN KNOWLEDGE IN TEXTS: APPLICATIONSopen accesshttp://purl.org/coar/access_right/c_abf2Reserva de todos los derechoshttp://rightsstatements.org/vocab/InC/1.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/497582026-06-13T07:49:27Z
dc.title.none.fl_str_mv Knowledge Graphs as Context Models: Improving the Detection of Cross-Language Plagiarism with Paraphrasing
title Knowledge Graphs as Context Models: Improving the Detection of Cross-Language Plagiarism with Paraphrasing
spellingShingle Knowledge Graphs as Context Models: Improving the Detection of Cross-Language Plagiarism with Paraphrasing
Franco-Salvador, Marc
Cross-language plagiarism detection
Textual similarity
Paraphrasing
Knowledge graphs
BabelNet
LENGUAJES Y SISTEMAS INFORMATICOS
title_short Knowledge Graphs as Context Models: Improving the Detection of Cross-Language Plagiarism with Paraphrasing
title_full Knowledge Graphs as Context Models: Improving the Detection of Cross-Language Plagiarism with Paraphrasing
title_fullStr Knowledge Graphs as Context Models: Improving the Detection of Cross-Language Plagiarism with Paraphrasing
title_full_unstemmed Knowledge Graphs as Context Models: Improving the Detection of Cross-Language Plagiarism with Paraphrasing
title_sort Knowledge Graphs as Context Models: Improving the Detection of Cross-Language Plagiarism with Paraphrasing
dc.creator.none.fl_str_mv Franco-Salvador, Marc
Gupta, Parth
Rosso, Paolo
author Franco-Salvador, Marc
author_facet Franco-Salvador, Marc
Gupta, Parth
Rosso, Paolo
author_role author
author2 Gupta, Parth
Rosso, Paolo
author2_role author
author
dc.contributor.none.fl_str_mv Departamento de Sistemas Informáticos y Computación
Escuela Técnica Superior de Ingeniería Informática
Centro de Investigación Pattern Recognition and Human Language Technology
European Commission
Universitat de València
Ministerio de Economía y Competitividad
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Cross-language plagiarism detection
Textual similarity
Paraphrasing
Knowledge graphs
BabelNet
LENGUAJES Y SISTEMAS INFORMATICOS
topic Cross-language plagiarism detection
Textual similarity
Paraphrasing
Knowledge graphs
BabelNet
LENGUAJES Y SISTEMAS INFORMATICOS
description 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.
publishDate 2013
dc.date.none.fl_str_mv 2013
2013-01-01
dc.type.none.fl_str_mv book part
http://purl.org/coar/resource_type/c_3248
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/bookPart
format bookPart
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/49758
url https://riunet.upv.es/handle/10251/49758
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv European Commission https://doi.org/10.13039/501100000780 FP7 269180 Web Information Quality Evaluation Initiative
Ministerio de Economía y Competitividad http://dx.doi.org/10.13039/501100003329 TIN2012-38603-C02-01 DIANA-APPLICATIONS: FINDING HIDDEN KNOWLEDGE IN TEXTS: APPLICATIONS
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer Verlag (Germany)
publisher.none.fl_str_mv Springer Verlag (Germany)
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300719

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