@inproceedings{meftouh-etal-2019-smart,
    title = "The {SM}ar{T} Classifier for {A}rabic Fine-Grained Dialect Identification",
    author = "Meftouh, Karima  and
      Abidi, Karima  and
      Harrat, Salima  and
      Smaili, Kamel",
    editor = "El-Hajj, Wassim  and
      Belguith, Lamia Hadrich  and
      Bougares, Fethi  and
      Magdy, Walid  and
      Zitouni, Imed  and
      Tomeh, Nadi  and
      El-Haj, Mahmoud  and
      Zaghouani, Wajdi",
    booktitle = "Proceedings of the Fourth Arabic Natural Language Processing Workshop",
    month = aug,
    year = "2019",
    address = "Florence, Italy",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/W19-4633/",
    doi = "10.18653/v1/W19-4633",
    pages = "259--263",
    abstract = "This paper describes the approach adopted by the SMarT research group to build a dialect identification system in the framework of the Madar shared task on Arabic fine-grained dialect identification. We experimented several approaches, but we finally decided to use a Multinomial Naive Bayes classifier based on word and character ngrams in addition to the language model probabilities. We achieved a score of 67.73{\%} in terms of Macro accuracy and a macro-averaged F1-score of 67.31{\%}"
}