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
- 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:
- 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)
- PDF:
- http://www.lrec-conf.org/proceedings/lrec2014/pdf/701_Paper.pdf