@InProceedings{mamou-EtAl:2018:C18-2,
  author    = {Mamou, Jonathan  and  Pereg, Oren  and  Wasserblat, Moshe  and  Dagan, Ido  and  Goldberg, Yoav  and  Eirew, Alon  and  Green, Yael  and  Guskin, Shira  and  Izsak, Peter  and  Korat, Daniel},
  title     = {SetExpander: End-to-end Term Set Expansion Based on Multi-Context Term Embeddings},
  booktitle = {Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations},
  month     = {August},
  year      = {2018},
  address   = {Santa Fe, New Mexico},
  publisher = {Association for Computational Linguistics},
  pages     = {58--62},
  abstract  = {We present SetExpander, a corpus-based system for expanding a seed set of terms into a more complete set of terms that belong to the same semantic class. SetExpander implements an iterative end-to end workflow for term set expansion. It enables users to easily select a seed set of terms, expand it, view the expanded set, validate it, re-expand the validated set and store it, thus simplifying the extraction of domain-specific fine-grained semantic classes. SetExpander has been used for solving real-life use cases including integration in an automated recruitment system and an issues and defects resolution system.},
  url       = {http://www.aclweb.org/anthology/C18-2013}
}