Treffer: Automatic keyphrase extraction from scientific articles

Title:
Automatic keyphrase extraction from scientific articles
Source:
Language resources and evaluation. 47(3):723-742
Publisher Information:
Dordrecht: Springer, 2013.
Publication Year:
2013
Physical Description:
print, 2 p.1/2
Original Material:
INIST-CNRS
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Department of Computing and Information Systems, The University of Melbourne, Melbourne, Australia
Pingar, Auckland, New Zealand
School of Computing, National University of Singapore, Singapore, Singapore
ISSN:
1574-020X
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Linguistics

FRANCIS
Accession Number:
edscal.27674716
Database:
PASCAL Archive

Weitere Informationen

This paper describes the organization and results of the automatic keyphrase extraction task held at the Workshop on Semantic Evaluation 2010 (SemEval-2010). The keyphrase extraction task was specifically geared towards scientific articles. Systems were automatically evaluated by matching their extracted keyphrases against those assigned by the authors as well as the readers to the same documents. We outline the task, present the overall ranking of the submitted systems, and discuss the improvements to the state-of-the-art in keyphrase extraction.