@InProceedings{king-cook:2017:SENSE2017,
  author    = {King, Milton  and  Cook, Paul},
  title     = {Supervised and unsupervised approaches to measuring usage similarity},
  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     = {47--52},
  abstract  = {Usage similarity (USim) is an approach to determining word meaning in context
	that does not rely on a sense inventory. Instead, pairs of usages of a target
	lemma are rated on a scale. In this paper we propose unsupervised approaches to
	USim based on embeddings for words, contexts, and sentences, and achieve
	state-of-the-art results over two USim datasets. We further consider supervised
	approaches to USim, and find that although they outperform unsupervised
	approaches, they are unable to generalize to lemmas that are unseen in the
	training data.},
  url       = {http://www.aclweb.org/anthology/W17-1906}
}