@inproceedings{hatty-etal-2017-evaluating,
    title = "Evaluating the Reliability and Interaction of Recursively Used Feature Classes for Terminology Extraction",
    author = {H{\"a}tty, Anna  and
      Dorna, Michael  and
      Schulte im Walde, Sabine},
    editor = "Kunneman, Florian  and
      I{\~n}urrieta, Uxoa  and
      Camilleri, John J.  and
      Ardanuy, Mariona Coll",
    booktitle = "Proceedings of the Student Research Workshop at the 15th Conference of the {E}uropean Chapter of the Association for Computational Linguistics",
    month = apr,
    year = "2017",
    address = "Valencia, Spain",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/E17-4012/",
    pages = "113--121",
    abstract = "Feature design and selection is a crucial aspect when treating terminology extraction as a machine learning classification problem. We designed feature classes which characterize different properties of terms based on distributions, and propose a new feature class for components of term candidates. By using random forests, we infer optimal features which are later used to build decision tree classifiers. We evaluate our method using the ACL RD-TEC dataset. We demonstrate the importance of the novel feature class for downgrading termhood which exploits properties of term components. Furthermore, our classification suggests that the identification of reliable term candidates should be performed successively, rather than just once."
}