@InProceedings{magnini-EtAl:2016:COLINGDEMO,
  author    = {Magnini, Bernardo  and  Minard, Anne-Lyse  and  Qwaider, Mohammed R. H.  and  Speranza, Manuela},
  title     = {TextPro-AL: An Active Learning Platform for Flexible and Efficient Production of Training Data for NLP Tasks},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {131--135},
  abstract  = {This paper presents TextPro-AL (Active Learning for Text Processing), a
	platform where human annotators can efficiently work to produce high quality
	training data for new domains and new languages exploiting Active Learning
	methodologies. TextPro-AL is a web-based application integrating four
	components: a machine learning based NLP pipeline, an annotation editor for
	task definition and text annotations,  an incremental re-training procedure
	based on active learning selection from a large pool of unannotated data, and a
	graphical visualization of the learning status of the system.},
  url       = {http://aclweb.org/anthology/C16-2028}
}