@InProceedings{king-hakimiparizi-cook:2018:S18-1,
  author    = {King, Milton  and  Hakimi Parizi, Ali  and  Cook, Paul},
  title     = {UNBNLP at SemEval-2018 Task 10: Evaluating unsupervised approaches to capturing discriminative attributes},
  booktitle = {Proceedings of The 12th International Workshop on Semantic Evaluation},
  month     = {June},
  year      = {2018},
  address   = {New Orleans, Louisiana},
  publisher = {Association for Computational Linguistics},
  pages     = {1013--1016},
  abstract  = {In this paper we present three unsupervised models for capturing discriminative attributes based on information from word embeddings, WordNet, and sentence-level word co-occurrence frequency. We show that, of these approaches, the simple approach based on word co-occurrence performs best. We further consider supervised and unsupervised approaches to combining information from these models, but these approaches do not improve on the word co-occurrence model.},
  url       = {http://www.aclweb.org/anthology/S18-1168}
}