@InProceedings{bougouin-boudin-daille:2016:COLING,
  author    = {Bougouin, Adrien  and  Boudin, Florian  and  Daille, Beatrice},
  title     = {Keyphrase Annotation with Graph Co-Ranking},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {2945--2955},
  abstract  = {Keyphrase annotation is the task of identifying textual units that represent
	the main content of a document. Keyphrase annotation is either carried out by
	extracting the most important phrases from a document, keyphrase extraction, or
	by assigning entries from a controlled domain-specific vocabulary, keyphrase
	assignment. Assignment methods are generally more reliable. They provide
	better-formed keyphrases, as well as keyphrases that do not occur in the
	document. But they are often silent on the contrary of extraction methods that
	do not depend on manually built resources. This paper proposes a new method to
	perform both keyphrase extraction and keyphrase assignment in an integrated and
	mutual reinforcing manner. Experiments have been carried out on datasets
	covering different domains of humanities and social sciences. They show
	statistically significant improvements compared to both keyphrase extraction
	and keyphrase assignment state-of-the art methods.},
  url       = {http://aclweb.org/anthology/C16-1277}
}