@inproceedings{almarwani-diab-2017-gw,
    title = "{GW}{\_}{QA} at {S}em{E}val-2017 Task 3: Question Answer Re-ranking on {A}rabic Fora",
    author = "Almarwani, Nada  and
      Diab, Mona",
    editor = "Bethard, Steven  and
      Carpuat, Marine  and
      Apidianaki, Marianna  and
      Mohammad, Saif M.  and
      Cer, Daniel  and
      Jurgens, David",
    booktitle = "Proceedings of the 11th International Workshop on Semantic Evaluation ({S}em{E}val-2017)",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/S17-2056/",
    doi = "10.18653/v1/S17-2056",
    pages = "344--348",
    abstract = "This paper describes our submission to SemEval-2017 Task 3 Subtask D, ``Question Answer Ranking in Arabic Community Question Answering''. In this work, we applied a supervised machine learning approach to automatically re-rank a set of QA pairs according to their relevance to a given question. We employ features based on latent semantic models, namely WTMF, as well as a set of lexical features based on string lengths and surface level matching. The proposed system ranked first out of 3 submissions, with a MAP score of 61.16{\%}."
}