@inproceedings{kwong-2020-translating,
    title = "Translating Collocations: The Need for Task-driven Word Associations",
    author = "Kwong, Oi Yee",
    editor = "Zock, Michael  and
      Chersoni, Emmanuele  and
      Lenci, Alessandro  and
      Santus, Enrico",
    booktitle = "Proceedings of the Workshop on the Cognitive Aspects of the Lexicon",
    month = dec,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2020.cogalex-1.14/",
    pages = "112--116",
    abstract = "Existing dictionaries may help collocation translation by suggesting associated words in the form of collocations, thesaurus, and example sentences. We propose to enhance them with task-driven word associations, illustrating the need by a few scenarios and outlining a possible approach based on word embedding. An example is given, using pre-trained word embedding, while more extensive investigation with more refined methods and resources is underway."
}