@InProceedings{albogamy-ramsay:2016:WNUT,
  author    = {Albogamy, Fahad  and  Ramsay, Allan},
  title     = {Unsupervised Stemmer for Arabic Tweets},
  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     = {78--84},
  abstract  = {Stemming is an essential processing step in a wide range of high level text
	processing applications such as information extraction, machine translation and
	sentiment analysis. It is used to reduce words to their stems. Many stemming
	algorithms have been developed for Modern Standard Arabic (MSA). Although
	Arabic tweets and MSA are closely related and share many characteristics, there
	are substantial differences between them in lexicon and syntax. In this paper,
	we introduce a light Arabic stemmer for Arabic tweets. Our results show
	improvements over the performance of a number of well-known stemmers for
	Arabic.},
  url       = {http://aclweb.org/anthology/W16-3912}
}