@inproceedings{anick-etal-2014-identification,
    title = "Identification of Technology Terms in Patents",
    author = "Anick, Peter  and
      Verhagen, Marc  and
      Pustejovsky, James",
    editor = "Calzolari, Nicoletta  and
      Choukri, Khalid  and
      Declerck, Thierry  and
      Loftsson, Hrafn  and
      Maegaard, Bente  and
      Mariani, Joseph  and
      Moreno, Asuncion  and
      Odijk, Jan  and
      Piperidis, Stelios",
    booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)",
    month = may,
    year = "2014",
    address = "Reykjavik, Iceland",
    publisher = "European Language Resources Association (ELRA)",
    url = "https://aclanthology.org/L14-1551/",
    pages = "2008--2014",
    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."
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%0 Conference Proceedings
%T Identification of Technology Terms in Patents
%A Anick, Peter
%A Verhagen, Marc
%A Pustejovsky, James
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Loftsson, Hrafn
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14)
%D 2014
%8 May
%I European Language Resources Association (ELRA)
%C Reykjavik, Iceland
%F anick-etal-2014-identification
%X 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.
%U https://aclanthology.org/L14-1551/
%P 2008-2014
Markdown (Informal)
[Identification of Technology Terms in Patents](https://aclanthology.org/L14-1551/) (Anick et al., LREC 2014)
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).