@InProceedings{lin-EtAl:2017:BioNLP17,
  author    = {Lin, Chen  and  Miller, Timothy  and  Dligach, Dmitriy  and  Bethard, Steven  and  Savova, Guergana},
  title     = {Representations of Time Expressions for Temporal Relation Extraction with Convolutional Neural Networks},
  booktitle = {BioNLP 2017},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada,},
  publisher = {Association for Computational Linguistics},
  pages     = {322--327},
  abstract  = {Token sequences are often used as the input for Convolutional Neural Networks
	(CNNs) in natural language processing. However, they might not be an ideal
	representation for time expressions, which are long, highly varied, and
	semantically complex. We describe a method for representing time expressions
	with single pseudo-tokens for CNNs. With this method, we establish a new
	state-of-the-art result for a clinical temporal relation extraction task.},
  url       = {http://www.aclweb.org/anthology/W17-2341}
}