@inproceedings{pais-mitrofan-2021-assessing,
    title = "Assessing multiple word embeddings for named entity recognition of professions and occupations in health-related social media",
    author = "Pais, Vasile  and
      Mitrofan, Maria",
    editor = "Magge, Arjun  and
      Klein, Ari  and
      Miranda-Escalada, Antonio  and
      Al-garadi, Mohammed Ali  and
      Alimova, Ilseyar  and
      Miftahutdinov, Zulfat  and
      Farre-Maduell, Eulalia  and
      Lopez, Salvador Lima  and
      Flores, Ivan  and
      O'Connor, Karen  and
      Weissenbacher, Davy  and
      Tutubalina, Elena  and
      Sarker, Abeed  and
      Banda, Juan M  and
      Krallinger, Martin  and
      Gonzalez-Hernandez, Graciela",
    booktitle = "Proceedings of the Sixth Social Media Mining for Health ({\#}SMM4H) Workshop and Shared Task",
    month = jun,
    year = "2021",
    address = "Mexico City, Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2021.smm4h-1.27/",
    doi = "10.18653/v1/2021.smm4h-1.27",
    pages = "128--130",
    abstract = "This paper presents our contribution to the ProfNER shared task. Our work focused on evaluating different pre-trained word embedding representations suitable for the task. We further explored combinations of embeddings in order to improve the overall results."
}