@inproceedings{mizrahi-etal-2020-coming,
    title = "{C}oming to {T}erms: {A}utomatic {F}ormation of {N}eologisms in {H}ebrew",
    author = "Mizrahi, Moran  and
      Yardeni Seelig, Stav  and
      Shahaf, Dafna",
    editor = "Cohn, Trevor  and
      He, Yulan  and
      Liu, Yang",
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/2020.findings-emnlp.442/",
    doi = "10.18653/v1/2020.findings-emnlp.442",
    pages = "4918--4929",
    abstract = "Spoken languages are ever-changing, with new words entering them all the time. However, coming up with new words (neologisms) today relies exclusively on human creativity. In this paper we propose a system to automatically suggest neologisms. We focus on the Hebrew language as a test case due to the unusual regularity of its noun formation. User studies comparing our algorithm to experts and non-experts demonstrate that our algorithm is capable of generating high-quality outputs, as well as enhance human creativity. More broadly, we seek to inspire more computational work around the topic of linguistic creativity, which we believe offers numerous unexplored opportunities."
}