@InProceedings{ishigaki-takamura-okumura:2017:I17-1,
  author    = {Ishigaki, Tatsuya  and  Takamura, Hiroya  and  Okumura, Manabu},
  title     = {Summarizing Lengthy Questions},
  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     = {792--800},
  abstract  = {In this research, we propose the task of question summarization.
	We first analyzed question-summary pairs extracted from a Community Question
	Answering (CQA) site, and found that a proportion of questions cannot be
	summarized by extractive approaches but requires abstractive approaches.
	We created a dataset by regarding the question-title pairs posted on the CQA
	site as question-summary pairs.
	By using the data, we trained extractive and abstractive summarization models,
	and compared them based on ROUGE scores and manual evaluations.
	Our experimental results show an abstractive method using an encoder-decoder
	model with a copying mechanism achieves better scores for both ROUGE-2
	F-measure and the evaluations by human judges.},
  url       = {http://www.aclweb.org/anthology/I17-1080}
}