Identification of Technology Terms in Patents

Peter Anick, Marc Verhagen, James Pustejovsky


Abstract
Natural language analysis of patents holds promise for the development of tools designed to assist analysts in the monitoring of emerging technologies. One component of such tools is the identification of technology terms. We describe an approach to the discovery of technology terms using supervised machine learning and evaluate its performance on subsets of patents in three languages: English, German, and Chinese.
Anthology ID:
L14-1551
Volume:
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Month:
May
Year:
2014
Address:
Reykjavik, Iceland
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
2008–2014
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/701_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Peter Anick, Marc Verhagen, and James Pustejovsky. 2014. Identification of Technology Terms in Patents. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 2008–2014, Reykjavik, Iceland. European Language Resources Association (ELRA).
Cite (Informal):
Identification of Technology Terms in Patents (Anick et al., LREC 2014)
Copy Citation:
PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/701_Paper.pdf