@InProceedings{yao-EtAl:2017:INLG2017,
  author    = {Yao, Jin-ge  and  Zhang, Jianmin  and  Wan, Xiaojun  and  Xiao, Jianguo},
  title     = {Content Selection for Real-time Sports News Construction from Commentary Texts},
  booktitle = {Proceedings of the 10th International Conference on Natural Language Generation},
  month     = {September},
  year      = {2017},
  address   = {Santiago de Compostela, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {31--40},
  abstract  = {We study the task of constructing sports news report automatically from live
	commentary and focus on content selection. Rather than receiving every piece of
	text of a sports match before news construction, as in previous related work,
	we novelly verify the feasibility of a more challenging but more useful setting
	to generate news report on the fly by treating live text input as a stream.
	Specifically, we design various scoring functions to address different
	requirements of the task. The near submodularity of scoring functions makes it
	possible to adapt efficient greedy algorithms even in stream data settings.
	Experiments suggest that our proposed framework can already produce comparable
	results compared with previous work that relies on a supervised
	learning-to-rank model with heavy feature engineering.},
  url       = {http://www.aclweb.org/anthology/W17-3504}
}