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arXiv 1702.030822017-02-10cs.CL

UsingWord Embedding for Cross-Language Plagiarism Detection

Compilatio；Univ. Grenoble Alpes（格勒诺布尔-阿尔卑斯大学）

J. Ferrero, F. Agnes, L. Besacier, D. Schwab

备注：: Accepted to EACL 2017 (short)

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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 F1 score of 89.15% for English-French similarity detection at chunk level (88.5% at sentence level) on a very challenging corpus.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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