@InProceedings{camachocollados-navigli:2017:EACLshort,
  author    = {Camacho-Collados, Jose  and  Navigli, Roberto},
  title     = {BabelDomains: Large-Scale Domain Labeling of Lexical Resources},
  booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {223--228},
  abstract  = {In this paper we present BabelDomains, a unified resource which provides
	lexical items with information about domains of knowledge. We propose an
	automatic method that uses knowledge from various lexical resources, exploiting
	both distributional and graph-based clues, to accurately propagate domain
	information. We evaluate our methodology intrinsically on two lexical resources
	(WordNet and BabelNet), achieving a precision over 80% in both cases. Finally,
	we show the potential of BabelDomains in a supervised learning setting,
	clustering training data by domain for hypernym discovery.},
  url       = {http://www.aclweb.org/anthology/E17-2036}
}