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

  • Marc Franco-Salvador
  • Parth Gupta
  • Paolo Rosso
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8173)


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.


Cross-language plagiarism detection textual similarity paraphrasing knowledge graphs BabelNet 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Marc Franco-Salvador
    • 1
    • 2
  • Parth Gupta
    • 1
  • Paolo Rosso
    • 1
  1. 1.Natural Language Engineering Lab - ELiRF, DSICUniversitat Politècnica de ValènciaValenciaSpain
  2. 2.Linguistic Computing Laboratory (LCL)Sapienza Università di RomaRomaItaly

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