@inproceedings{mykowiecka-etal-2016-recognition,
    title = "Recognition of non-domain phrases in automatically extracted lists of terms",
    author = "Mykowiecka, Agnieszka  and
      Marciniak, Malgorzata  and
      Rychlik, Piotr",
    editor = "Drouin, Patrick  and
      Grabar, Natalia  and
      Hamon, Thierry  and
      Kageura, Kyo  and
      Takeuchi, Koichi",
    booktitle = "Proceedings of the 5th International Workshop on Computational Terminology (Computerm2016)",
    month = dec,
    year = "2016",
    address = "Osaka, Japan",
    publisher = "The COLING 2016 Organizing Committee",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/W16-4703/",
    pages = "12--20",
    abstract = "In the paper, we address the problem of recognition of non-domain phrases in terminology lists obtained with an automatic term extraction tool. We focus on identification of multi-word phrases that are general terms and discourse function expressions. We tested several methods based on domain corpora comparison and a method based on contexts of phrases identified in a large corpus of general language. We compared the results of the methods to manual annotation. The results show that the task is quite hard as the inter-annotator agreement is low. Several tested methods achieved similar overall results, although the phrase ordering varied between methods. The most successful method with the precision about 0.75 at the half of the tested list was the context based method using a modified contextual diversity coefficient."
}