@mastersthesis {henestrozaanguiano:tel-00860720,
	title = {Efficient large-context dependency parsing and correction with distributional lexical resources},
	year = {2013},
	school = {Universit{\'e} Paris-Diderot},
	type = {phdTheses},
	address = {Paris},
	keywords = {adaptation de domaine, analyse {\`a} base de transitions, analyse syntaxique, apprentissage semi-supervise, computational linguistics, dependency grammar, domain adaptation, grammaires de dependance, lexical resources, linguistique informatique, machines {\`a} vecteurs supports, ressources lexicales, semi-supervised learning, support vector machines, syntactic parsing, transition-based parsing},
	url = {https://tel.archives-ouvertes.fr/tel-00860720},
	author = {Henestroza Anguiano, Enrique}
}
@inproceedings {candito:hal-00659577,
	title = {{A Word Clustering Approach to Domain Adaptation: Effective Parsing of Biomedical Texts}},
	year = {2011},
	month = {Oct},
	address = {Dublin, Ireland},
	keywords = {biomedical texts, domain adaptation, statistical parsing},
	url = {https://hal.inria.fr/hal-00659577},
	author = {Marie Candito and Henestroza Anguiano, Enrique and Seddah, Djam{\'e}}
}
