@inproceedings{ismail-etal-2022-bonc,
    title = "{B}o{NC}: Bag of N-Characters Model for Word Level Language Identification",
    author = "Ismail, Shimaa  and
      K. Gallab, Mai  and
      Nayel, Hamada",
    editor = "Chakravarthi, Bharathi Raja  and
      Murugappan, Abirami  and
      Chinnappa, Dhivya  and
      Hane, Adeep  and
      Kumeresan, Prasanna Kumar  and
      Ponnusamy, Rahul",
    booktitle = "Proceedings of the 19th International Conference on Natural Language Processing (ICON): Shared Task on Word Level Language Identification in Code-mixed Kannada-English Texts",
    month = dec,
    year = "2022",
    address = "IIIT Delhi, New Delhi, India",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2022.icon-wlli.7/",
    pages = "34--37",
    abstract = "This paper describes the model submitted by NLP{\_}BFCAI team for Kanglish shared task held at ICON 2022. The proposed model used a very simple approach based on the word representation. Simple machine learning classification algorithms, Random Forests, Support Vector Machines, Stochastic Gradient Descent and Multi-Layer Perceptron have been imple- mented. Our submission, RF, securely ranked fifth among all other submissions."
}