@inproceedings{li-gaillat-2020-automatic,
    title = "Automatic detection of unexpected/erroneous collocations in learner corpus",
    author = "Li, Jen-Yu  and
      Gaillat, Thomas",
    editor = "Markantonatou, Stella  and
      McCrae, John  and
      Mitrovi{\'c}, Jelena  and
      Tiberius, Carole  and
      Ramisch, Carlos  and
      Vaidya, Ashwini  and
      Osenova, Petya  and
      Savary, Agata",
    booktitle = "Proceedings of the Joint Workshop on Multiword Expressions and Electronic Lexicons",
    month = dec,
    year = "2020",
    address = "online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2020.mwe-1.13/",
    pages = "101--106",
    abstract = "This research investigates the collocational errors made by English learners in a learner corpus. It focuses on the extraction of unexpected collocations. A system was proposed and implemented with open source toolkit. Firstly, the collocation extraction module was evaluated by a corpus with manually annotated collocations. Secondly, a standard collocation list was collected from a corpus of native speaker. Thirdly, a list of unexpected collocations was generated by extracting candidates from a learner corpus and discarding the standard collocations on the list. The overall performance was evaluated, and possible sources of error were pointed out for future improvement."
}