@InProceedings{le-mallek-sadat:2016:WNUT,
  author    = {LE, Ngoc Tan  and  Mallek, Fatma  and  Sadat, Fatiha},
  title     = {UQAM-NTL: Named entity recognition in Twitter messages},
  booktitle = {Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {197--202},
  abstract  = {This paper describes our system used in the 2nd Workshop on Noisy
	User-generated Text (WNUT) shared task for Named Entity Recognition (NER) in
	Twitter, in conjunction with Coling 2016. Our system is based on supervised
	machine learning by applying Conditional Random Fields (CRF) to train two
	classifiers for two evaluations. The first evaluation aims at predicting the 10
	fine-grained types of named entities; while the second evaluation aims at
	predicting no type of named entities. The experimental results show that our
	method has significantly improved Twitter NER performance.},
  url       = {http://aclweb.org/anthology/W16-3926}
}