@inproceedings{ding-etal-2019-ynu-dyx,
    title = "{YNU}{\_}{DYX} at {S}em{E}val-2019 Task 9: A Stacked {B}i{LSTM} for Suggestion Mining Classification",
    author = "Ding, Yunxia  and
      Zhou, Xiaobing  and
      Zhang, Xuejie",
    editor = "May, Jonathan  and
      Shutova, Ekaterina  and
      Herbelot, Aurelie  and
      Zhu, Xiaodan  and
      Apidianaki, Marianna  and
      Mohammad, Saif M.",
    booktitle = "Proceedings of the 13th International Workshop on Semantic Evaluation",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/S19-2223/",
    doi = "10.18653/v1/S19-2223",
    pages = "1272--1276",
    abstract = "In this paper we describe a deep-learning system that competed as SemEval 2019 Task 9-SubTask A: Suggestion Mining from Online Reviews and Forums. We use Word2Vec to learn the distributed representations from sentences. This system is composed of a Stacked Bidirectional Long-Short Memory Network (SBiLSTM) for enriching word representations before and after the sequence relationship with context. We perform an ensemble to improve the effectiveness of our model. Our official submission results achieve an F1-score 0.5659."
}