@inproceedings{alqahtani-yannakoudakis-2022-authorship,
    title = "Authorship Verification for {A}rabic Short Texts Using {A}rabic Knowledge-Base Model ({A}ra{KB})",
    author = "Alqahtani, Fatimah  and
      Yannakoudakis, Helen",
    editor = "Bouamor, Houda  and
      Al-Khalifa, Hend  and
      Darwish, Kareem  and
      Rambow, Owen  and
      Bougares, Fethi  and
      Abdelali, Ahmed  and
      Tomeh, Nadi  and
      Khalifa, Salam  and
      Zaghouani, Wajdi",
    booktitle = "Proceedings of the Seventh Arabic Natural Language Processing Workshop (WANLP)",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, United Arab Emirates (Hybrid)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/2022.wanlp-1.19/",
    doi = "10.18653/v1/2022.wanlp-1.19",
    pages = "205--213",
    abstract = "Arabic is a Semitic language, considered to be one of the most complex languages in the world due to its unique composition and complex linguistic features. It consequently causes challenges for verifying the authorship of Arabic texts, requiring extensive research and development. This paper presents a new knowledge-based model to enhance Natural Language Understanding and thereby improve authorship verification performance. The proposed model provided promising results that would benefit the Arabic research for different Natural Language Processing tasks."
}