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.
@article{arxiv.1702.03082,
title = {UsingWord Embedding for Cross-Language Plagiarism Detection},
author = {J. Ferrero and F. Agnes and L. Besacier and D. Schwab},
journal= {arXiv preprint arXiv:1702.03082},
year = {2017}
}