Keyphrase Annotation with Graph Co-Ranking

Adrien Bougouin, Florian Boudin, Béatrice Daille


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.
Anthology ID:
C16-1277
Volume:
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
Month:
December
Year:
2016
Address:
Osaka, Japan
Editors:
Yuji Matsumoto, Rashmi Prasad
Venue:
COLING
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
2945–2955
Language:
URL:
https://aclanthology.org/C16-1277
DOI:
Bibkey:
Cite (ACL):
Adrien Bougouin, Florian Boudin, and Béatrice Daille. 2016. Keyphrase Annotation with Graph Co-Ranking. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 2945–2955, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
Keyphrase Annotation with Graph Co-Ranking (Bougouin et al., COLING 2016)
Copy Citation:
PDF:
https://aclanthology.org/C16-1277.pdf