@InProceedings{khodak-EtAl:2017:SENSE2017,
  author    = {Khodak, Mikhail  and  Risteski, Andrej  and  Fellbaum, Christiane  and  Arora, Sanjeev},
  title     = {Automated WordNet Construction Using Word Embeddings},
  booktitle = {Proceedings of the 1st Workshop on Sense, Concept and Entity Representations and their Applications},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {12--23},
  abstract  = {We present a fully unsupervised method for automated construction of WordNets
	based upon recent advances in distributional representations of sentences and
	word-senses combined with readily available machine translation tools. The
	approach requires very few linguistic resources and is thus extensible to
	multiple target languages. To evaluate our method we construct two 600-word
	testsets for word-to-synset matching in French and Russian using native
	speakers and evaluate the performance of our method along with several other
	recent approaches. Our method exceeds the best language-specific and
	multi-lingual automated WordNets in F-score for both languages. The databases
	we construct for French and Russian, both languages without large publicly
	available manually constructed WordNets, will be publicly released along with
	the testsets.},
  url       = {http://www.aclweb.org/anthology/W17-1902}
}