@inproceedings{qi-etal-2017-scir,
    title = "{SCIR}-{QA} at {S}em{E}val-2017 Task 3: {CNN} Model Based on Similar and Dissimilar Information between Keywords for Question Similarity",
    author = "Qi, Le  and
      Zhang, Yu  and
      Liu, Ting",
    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/add-emnlp-2024-awards/S17-2049/",
    doi = "10.18653/v1/S17-2049",
    pages = "305--309",
    abstract = "We describe a method of calculating the similarity of questions in community QA. Question in cQA are usually very long and there are a lot of useless information about calculating the similarity of questions. Therefore,we implement a CNN model based on similar and dissimilar information between question`s keywords. We extract the keywords of questions, and then model the similar and dissimilar information between the keywords, and use the CNN model to calculate the similarity."
}