@InProceedings{hayashi-nagata:2017:EACLshort,
  author    = {Hayashi, Katsuhiko  and  Nagata, Masaaki},
  title     = {K-best Iterative Viterbi Parsing},
  booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {305--310},
  abstract  = {This paper presents an efficient and optimal parsing algorithm for
	probabilistic context-free grammars (PCFGs). To achieve faster parsing, our
	proposal employs a pruning technique to reduce unnecessary edges in the search
	space. The key is to conduct repetitively Viterbi inside and outside parsing,
	while gradually expanding the search space to efficiently compute heuristic
	bounds used for pruning. Our experimental results using the English Penn
	Treebank corpus show that the proposed algorithm is faster than the standard
	CKY parsing algorithm. In
	addition, we also show how to extend this algorithm to extract k-best Viterbi
	parse trees.},
  url       = {http://www.aclweb.org/anthology/E17-2049}
}