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Communication Dans Un Congrès Année : 2017

Using Word Embedding for Cross-Language Plagiarism Detection

Résumé

This paper proposes to use distributed representation of words (word embeddings) in cross-language textual similarity detection. The main contributions of this paper are the following: (a) we introduce new cross-language similarity detection methods based on distributed representation of words; (b) we combine the different methods proposed to verify their complementarity and finally obtain an overall F 1 score of 89.15% for English-French similarity detection at chunk level (88.5% at sentence level) on a very challenging corpus.
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Dates et versions

hal-01502146 , version 1 (05-04-2017)

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Jérémy Ferrero, Frédéric Agnès, Laurent Besacier, Didier Schwab. Using Word Embedding for Cross-Language Plagiarism Detection. EACL 2017, Apr 2017, Valence, Spain. pp.415 - 421. ⟨hal-01502146⟩
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