@InProceedings{kawahara-EtAl:2017:IWPT,
  author    = {Kawahara, Daisuke  and  Hayashibe, Yuta  and  Morita, Hajime  and  Kurohashi, Sadao},
  title     = {Automatically Acquired Lexical Knowledge Improves Japanese Joint Morphological and Dependency Analysis},
  booktitle = {Proceedings of the 15th International Conference on Parsing Technologies},
  month     = {September},
  year      = {2017},
  address   = {Pisa, Italy},
  publisher = {Association for Computational Linguistics},
  pages     = {1--10},
  abstract  = {This paper presents a joint model for morphological and
	dependency analysis based on automatically acquired lexical
	knowledge. This model takes advantage of rich lexical knowledge to
	simultaneously resolve word segmentation, POS, and
	dependency ambiguities. In our experiments on Japanese, we show the
	effectiveness of our joint
	model over conventional pipeline models.},
  url       = {http://www.aclweb.org/anthology/W17-6301}
}