@InProceedings{vandergoot-vannoord:2017:Short,
  author    = {van der Goot, Rob  and  van Noord, Gertjan},
  title     = {Parser Adaptation for Social Media by Integrating Normalization},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
  month     = {July},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {491--497},
  abstract  = {This work explores different approaches of using normalization for parser
	adaptation.  Traditionally, normalization is used as separate pre-processing
	step. We show that integrating the normalization model into the
	parsing algorithm is more beneficial. This way, multiple normalization
	candidates can be leveraged, which improves parsing performance on social
	media.
	We test this hypothesis by modifying the Berkeley parser; out-of-the-box it
	achieves an F1 score of 66.52.                          Our integrated approach
	reaches a
	significant
	improvement with an F1 score of 67.36, while using the best normalization
	sequence results in an F1 score of only 66.94.},
  url       = {http://aclweb.org/anthology/P17-2078}
}