@InProceedings{kesarwani-EtAl:2017:LaTeCH-CLfL,
  author    = {Kesarwani, Vaibhav  and  Inkpen, Diana  and  Szpakowicz, Stan  and  Tanasescu, Chris},
  title     = {Metaphor Detection in a Poetry Corpus},
  booktitle = {Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {1--9},
  abstract  = {Metaphor is indispensable in poetry. It showcases the poet's creativity, and
	contributes to the overall emotional pertinence of the poem while honing its
	specific rhetorical impact. Previous work on metaphor detection relies on
	either rule-based or statistical models, none of them applied to poetry. Our
	method focuses on metaphor detection in a poetry corpus. It combines rule-based
	and statistical models (word embeddings) to develop a new classification
	system. Our system has achieved a precision of 0.759 and a recall of 0.804 in
	identifying one type of metaphor in poetry.},
  url       = {http://www.aclweb.org/anthology/W17-2201}
}