@InProceedings{kajiwara-komachi-mochihashi:2017:I17-1,
  author    = {Kajiwara, Tomoyuki  and  Komachi, Mamoru  and  Mochihashi, Daichi},
  title     = {MIPA: Mutual Information Based Paraphrase Acquisition via Bilingual Pivoting},
  booktitle = {Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)},
  month     = {November},
  year      = {2017},
  address   = {Taipei, Taiwan},
  publisher = {Asian Federation of Natural Language Processing},
  pages     = {80--89},
  abstract  = {We present a pointwise mutual information (PMI)-based approach to formalize
	paraphrasability and propose a variant of PMI, called MIPA, for the paraphrase
	acquisition.
	Our paraphrase acquisition method first acquires lexical paraphrase pairs by
	bilingual pivoting and then reranks them by PMI and distributional similarity.
	The complementary nature of information from bilingual corpora and from
	monolingual corpora makes the proposed method robust.
	Experimental results show that the proposed method substantially outperforms
	bilingual pivoting and distributional similarity themselves in terms of metrics
	such as MRR, MAP, coverage, and Spearman's correlation.},
  url       = {http://www.aclweb.org/anthology/I17-1009}
}