@InProceedings{mnasri-dechalendar-ferret:2017:I17-2,
  author    = {mnasri, maali  and  de Chalendar, Ga\"{e}l  and  Ferret, Olivier},
  title     = {Taking into account Inter-sentence Similarity for Update Summarization},
  booktitle = {Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)},
  month     = {November},
  year      = {2017},
  address   = {Taipei, Taiwan},
  publisher = {Asian Federation of Natural Language Processing},
  pages     = {204--209},
  abstract  = {Following Gillick and Favre (2009), a lot of work about extractive
	summarization has modeled this task by associating two contrary constraints:
	one aims at maximizing the coverage of the summary with respect to its
	information content while the other represents its size limit. In this context,
	the notion of redundancy is only implicitly taken into account. In this
	article, we extend the framework defined by Gillick and Favre (2009) by
	examining how and to what extent integrating semantic sentence similarity into
	an update summarization system can improve its results. We show more precisely
	the impact of this strategy through evaluations performed on DUC 2007 and TAC
	2008 and 2009 datasets.},
  url       = {http://www.aclweb.org/anthology/I17-2035}
}