@InProceedings{hazem-morin:2017:I17-1,
  author    = {Hazem, Amir  and  Morin, Emmanuel},
  title     = {Bilingual Word Embeddings for Bilingual Terminology Extraction from Specialized Comparable Corpora},
  booktitle = {Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)},
  month     = {November},
  year      = {2017},
  address   = {Taipei, Taiwan},
  publisher = {Asian Federation of Natural Language Processing},
  pages     = {685--693},
  abstract  = {Bilingual lexicon extraction from compa-
	rable corpora is constrained by the small
	amount                    of        available  data  when  dealing
	with specialized domains.  This aspect pe-
	nalizes the performance of distributional-
	based  approaches,  which  is  closely                    re-
	lated to the reliability of word’s cooccur-
	rence  counts  extracted  from                    comparable
	corpora. A solution to avoid this limitation
	is to associate external resources with the
	comparable corpus.  Since bilingual word
	embeddings have recently shown efficient
	models                    for  learning  bilingual            distributed
	representation                    of        words,        we              explore  dif-
	ferent word embedding models and show
	how a general-domain comparable corpus
	can enrich a specialized comparable cor-
	pus via neural networks},
  url       = {http://www.aclweb.org/anthology/I17-1069}
}