@inproceedings{lai-etal-2018-sunnynlp,
    title = "{SUNNYNLP} at {S}em{E}val-2018 Task 10: A Support-Vector-Machine-Based Method for Detecting Semantic Difference using Taxonomy and Word Embedding Features",
    author = "Lai, Sunny  and
      Leung, Kwong Sak  and
      Leung, Yee",
    editor = "Apidianaki, Marianna  and
      Mohammad, Saif M.  and
      May, Jonathan  and
      Shutova, Ekaterina  and
      Bethard, Steven  and
      Carpuat, Marine",
    booktitle = "Proceedings of the 12th International Workshop on Semantic Evaluation",
    month = jun,
    year = "2018",
    address = "New Orleans, Louisiana",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/S18-1118/",
    doi = "10.18653/v1/S18-1118",
    pages = "741--746",
    abstract = "We present SUNNYNLP, our system for solving SemEval 2018 Task 10: {\textquotedblleft}Capturing Discriminative Attributes{\textquotedblright}. Our Support-Vector-Machine(SVM)-based system combines features extracted from pre-trained embeddings and statistical information from Is-A taxonomy to detect semantic difference of concepts pairs. Our system is demonstrated to be effective in detecting semantic difference and is ranked 1st in the competition in terms of F1 measure. The open source of our code is coined SUNNYNLP."
}