Autor:	Ferrero, J., Agnes, F., Besacier, L., Schwab, D.
Rok vydání:	2017
Předmět:	Computer Science - Computation and Language
Druh dokumentu:	Working Paper
Popis:	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. Comment: Accepted to EACL 2017 (short)
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1702.03082 Zobrazit plný text záznamu View this record from Arxiv