@InProceedings{qin-wang-kim:2017:Long,
  author    = {Qin, Kechen  and  Wang, Lu  and  Kim, Joseph},
  title     = {Joint Modeling of Content and Discourse Relations in Dialogues},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  month     = {July},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {974--984},
  abstract  = {We present a joint modeling approach to identify salient discussion points in
	spoken meetings as well as to label the discourse relations between speaker
	turns. A variation of our model is also discussed when discourse relations are
	treated as latent variables. Experimental results on two popular meeting
	corpora show that our joint model can outperform state-of-the-art approaches
	for both phrase-based content selection and discourse relation prediction
	tasks. We also evaluate our model on predicting the consistency among team
	members' understanding of their group decisions. Classifiers trained with
	features constructed from our model achieve significant better predictive
	performance than the state-of-the-art.},
  url       = {http://aclweb.org/anthology/P17-1090}
}